AI Memory | UAIX | Universal Artificial Intelligence Exchange

How to use this page

Use this page for durable AI project memory, supported starter configurations, dynamic canonical-template downloads, and the boundary between portable UAI memory packets and deeper LLM Wiki knowledge.

Memory path

AI Memory Package Wizard .uai File Guide Canonical AI Memory Using UAI Packages With An LLM Wiki

Durable AI Memory

Build compact project memory without turning history into truth

Start with the wizard when you need a usable package. Use AI Memory for accepted current context, include the launch-baseline required files, and fill local Totem/Taboo values only when a human or owner has provided them. Use an LLM Wiki or research wiki for broader background that still needs review before promotion.

Bundle

One source for samples and ZIP

Starter ZIPs are generated from canonical templates, generated manifests, and the same resolved samples rendered on the page so download drift is not possible.

Pattern

Project Handoff makes memory operational

AGENTS.md, .uai/readme.human, and .uai files give the next assistant a predictable load path before edits begin, without loading old research by default.

Launch-Baseline Required Files

Identity, world-context, Totem, and Taboo files are required

Generated .uai/identity.uai, .uai/world-context.uai, .uai/totem.uai, .uai/taboo.uai, and .uai/short-term-memory.uai files are required for every launch-baseline UAIX memory or handoff package. Project/developer packages and code-bearing assistant packages also require .uai/coding-standards.uai and .uai/next-recursive-prompt.uai. next-recursive-prompt.uai is not required for agents that don't deal with any coding. Its stored plan is used for continuation or directly related requests, not as a replacement for current user instruction. Related active intake supersedes or expands the stored loop and still requires project work. When no human-supplied values are entered, those anchor files explain what belongs there and do not infer the project-specific anchors.

File Guide

Every package file has a declared required scope

Use the .uai File Guide to verify universal required, profile-required, content-triggered required, configuration-specific required, and out-of-scope file handling before relying on a package.

Depth

LLM Wiki stays expansive

Use wiki memory for research, source summaries, and long internal documentation, then promote accepted facts into the compact handoff bundle.

Context Budget

Archive before slimming

When hot files grow too large, preserve pre-slim snapshots in cold memory with hashes and summaries, then keep only current truth in AI Memory.

Memory path

AI Memory Package WizardBuild the startup packet, system profile, receiver brief, universal required files, profile-required files, content-triggered required files, configuration-specific required files, manifest overlay, copy-paste files, LLM Wiki plan required for LLM Wiki configuration, readiness checks, and canonical ZIP links..uai File GuideClosed required-file-set guide for every published .uai memory file.Canonical AI MemoryLayer raw sources, durable wiki memory, derived graph projections, compact packets, and handoff transfer without blurring authority.Using UAI Packages With An LLM WikiPractical routing between compact packages and deeper wiki memory.Talisman SystemRare protected-anchor governance for persistent Totem and Taboo anchors.Context Budget GuideKeep hot handoff files small while preserving long research in cold memory.Project HandoffEngineering pattern for AI Memory files.Agent File HandoffDropped-file intake before broad work.ReportsLLM Wiki comparison background.RoadmapCurrent and planned tooling boundary.

Alias routeRequested entry path

/AI_Memory -> /es-us/ai-memory/

The requested /AI_Memory path redirects to the canonical locale-prefixed AI Memory page while preserving the clean public route rule.

What AI Memory Means In UAIX

UAI AI Memory is a lightweight, portable, file-based standard for durable context. It gives humans and AI agents a reviewable packet of project memory instead of relying on private chat history, hidden model settings, one vendor account, or a stale folder of notes.

AI Memory is not a general knowledge base. It is the compact operating memory a future actor should load before acting: project purpose, current state, constraints, decisions, next actions, owners, trust boundaries, maintenance rules, and targeted checks.

Context budget: keep AI Memory hot and small. Long research, old progress detail, pre-slim handoff snapshots, and deep rationale should live in an LLM Wiki or AIWikis-style cold memory layer with source summaries, hashes, and dated logs. Promote only the reviewed current conclusion back into the AI Memory packet.

Canonical AI Memory

Use Canonical AI Memory when you need the layer map behind the packet: raw sources, reviewed LLM Wiki memory, derived graph projections, compact UAI AI Memory, Project Handoff transfer context, and the execution agent that still has to obey local rules.

Fastest Practical Path

Most readers should start with the AI Memory Package Wizard. It turns the current supported presets into a reviewable startup packet, receiver brief, system profile, manifest overlay, wiki plan required for LLM Wiki configuration, copyable file deck, and canonical ZIP link without claiming hosted import, repository writes, automatic sync, SDK, CLI, certification, or endorsement.

Rare protected-anchor governance belongs on the Talisman System page, not in the normal wizard flow. Use it only when a complicated, persistent, multi-actor ecosystem needs protected totem.uai and taboo.uai anchors, external enforcement, no-op talk-back, audit evidence, and rollback.

Why Unstructured AI Memory Fails

Unstructured memory fails because it mixes old chats, generated summaries, wiki notes, screenshots, logs, and roadmap guesses without saying what is current or binding. The next agent may miss a red line, believe an obsolete claim, leak sensitive material, or run the wrong checks because the project never named its memory contract.

No front door: the agent cannot tell where to begin.
No lifecycle: working state, transfer packets, decisions, onboarding notes, and audit evidence age differently.
No trust boundary: internal-only material can be handed to an outside vendor or autonomous agent by accident.
No canonical source: visible examples, downloadable ZIPs, and docs drift because sample files are copied in several places.

Why File-Based Memory Works

File-based memory is boring in the best way. It can be reviewed in a pull request, zipped for a handoff, redacted before external sharing, loaded by different agents, archived with a release, and tested for drift. UAIX uses plain text and deterministic manifests so people can inspect what an AI is about to treat as context.

AI Memory Taxonomy

UAIX now treats Project AI Memory as the ongoing working-memory configuration and Project Handoff as a subtype of AI Memory for transfer. Additional configurations exist only when they have a different lifecycle, trust boundary, or consumption pattern. Team Memory and Product Memory are documented as views over existing bundles, while certification-style or regulated-data memory is deferred until the public evidence and safety process exist.

Choose the right AI Memory configuration

These supported starter bundles are presets over one canonical file-template registry. Shared files come from the same template IDs; bundle-specific guidance is added through metadata and overlays.

Configuration	Use when	Lifecycle and trust boundary	Download
Project AI Memory `project-ai-memory`	Use when a project is active and context must persist across many AI sessions without turning the bundle into a full knowledge base.	Lifecycle: Maintained continuously; current-state and next-action files change often, decisions and constraints change carefully. Trust: Internal or controlled collaboration by default. Review before sharing externally or giving to an autonomous agent.	uai-ai-memory-starter.zip
Project Handoff `project-handoff`	Use when the next actor must take over a project safely and needs current state, constraints, decisions, checks, and ownership context.	Lifecycle: Prepared before transfer, reviewed at acceptance, and updated when responsibility or support boundaries change. Trust: Can be internal or external, but external handoffs must be sanitized and approved before sharing.	uai-project-handoff-starter.zip
Agent Session Memory `agent-session-memory`	Use when an agent or tool needs to resume a task with enough state to continue without replaying a whole chat transcript.	Lifecycle: Created for a run or task, updated frequently, then merged into project memory or archived when the task closes. Trust: Often operational and sensitive. Keep permissions, tool access, blocked actions, and cleanup state explicit.	uai-agent-session-memory-starter.zip
Onboarding Memory `onboarding-memory`	Use when the first job is orientation rather than ownership transfer, incident review, or deep rationale capture.	Lifecycle: Reviewed before each onboarding cohort or external introduction; kept concise and introductory. Trust: Usually shareable after review, but remove internal strategy, customer data, credentials, and privileged operations.	uai-onboarding-memory-starter.zip
Decision Memory `decision-memory`	Use when rationale and tradeoffs matter more than current task status.	Lifecycle: Append-first and review-heavy; reversals should explain what changed rather than erase history. Trust: Contains internal strategy when the source bundle records it. Review before exposing externally or to agents with broad write permissions.	uai-decision-memory-starter.zip
Client or Vendor Handoff Memory `external-handoff-memory`	Use when a client, vendor, partner, or outside agent needs enough context to continue work without receiving internal-only memory.	Lifecycle: Prepared as an export, redacted, approved, shared, and archived with a dated changelog entry. Trust: Strict external boundary. Remove secrets, credentials, private customer data, legal strategy, internal pricing, and unsupported claims.	uai-external-handoff-memory-starter.zip
Incident or Audit Memory `incident-audit-memory`	Use when facts, timestamps, mitigations, owners, evidence links, and follow-up commitments need to travel together.	Lifecycle: Opened during review, updated as evidence is confirmed, closed with follow-up owners and a retained audit trail. Trust: Potentially sensitive. Sanitize customer data, security details, credentials, legal material, and private evidence before external sharing.	uai-incident-audit-memory-starter.zip
LLM Wiki Export Memory `llm-wiki-export-memory`	Use when a large internal wiki needs a small, reviewable, portable packet for a project, handoff, onboarding, or agent task.	Lifecycle: Generated from reviewed wiki material, checked against source citations, then promoted or discarded after use. Trust: Wiki material is background until reviewed. Cite sources, flag uncertainty, and redact private material before export.	uai-llm-wiki-export-memory-starter.zip
Office Assistant Memory `office-assistant-memory`	Use when an AI supports office administration without making the package primarily a software project handoff.	Lifecycle: Maintained continuously; updated when preferences, contacts, workflows, recurring tasks, boundaries, or authority change. Trust: Often private or internal. Minimize personal data, credentials, financial information, HR details, legal content, and private communications.	uai-office-assistant-memory-starter.zip
Executive Assistant Memory `executive-assistant-memory`	Use when priorities, people, meetings, decisions, and follow-through need durable assistant context.	Lifecycle: Continuously maintained with frequent updates to priorities, people, commitments, and communication rules. Trust: Highly sensitive. Requires strong redaction and authority boundaries before sharing.	uai-executive-assistant-memory-starter.zip
Personal Assistant Memory `personal-assistant-memory`	Use when privacy and freshness matter more than project history.	Lifecycle: Continuously maintained; privacy and freshness are more important than project history. Trust: Private by default. Avoid unnecessary sensitive personal data.	uai-personal-assistant-memory-starter.zip
AI Chatbot Friend Memory `chatbot-friend-memory`	Use when social memory and relationship boundaries are the central assistant context.	Lifecycle: Continuously maintained; relationship boundaries and consent rules are stable while interests and current-life context change over time. Trust: Private and consent-bound. Must include boundaries that prevent manipulation, dependency reinforcement, identity deception, unsupported professional authority claims, and unsupported memory claims.	uai-chatbot-friend-memory-starter.zip
Companion AI Memory `companion-memory`	Use when the package needs durable continuity without pretending the assistant is human or a replacement for professional help.	Lifecycle: Continuously maintained with frequent review of boundaries, crisis guidance, consent, and user preferences. Trust: Private, sensitive, and safety-bound. Keep support boundaries explicit.	uai-companion-memory-starter.zip
Tutor or Coach Memory `tutor-coach-memory`	Use when learning progress and coaching boundaries matter more than repository state.	Lifecycle: Updated after learning sessions, milestones, assessments, topic changes, or goal changes. Trust: Educational or coaching context. Avoid sensitive records unless explicitly reviewed and necessary.	uai-tutor-coach-memory-starter.zip
Creative Partner Memory `creative-partner-memory`	Use when style, canon, constraints, assets, audience, or creative direction need to travel together.	Lifecycle: Updated when style, canon, constraints, assets, audience, or creative direction changes. Trust: May contain private drafts, unreleased work, IP-sensitive ideas, brand strategy, or client material.	uai-creative-partner-memory-starter.zip
Household Assistant Memory `household-assistant-memory`	Use when home context, recurring routines, and privacy boundaries need durable assistant memory.	Lifecycle: Updated when routines, household members, constraints, vendors, schedules, or safety rules change. Trust: Private household memory. Minimize addresses, children data, health details, financial data, and access codes.	uai-household-assistant-memory-starter.zip
Customer or Front-Desk Assistant Memory `customer-front-desk-memory`	Use when public-facing or semi-public assistant memory needs public claims, source material, privacy, and escalation boundaries.	Lifecycle: Updated when public hours, services, policies, contacts, escalation paths, forms, scripts, or boundaries change. Trust: Public-facing or semi-public. Must not expose internal-only notes, customer private data, credentials, legal/security details, or unsupported claims.	uai-customer-front-desk-memory-starter.zip
General Non-Project AI Memory `general-non-project-ai-memory`	Use when no specific non-project assistant preset matches but the package still needs portable assistant memory.	Lifecycle: Maintained as the assistant role, user preferences, boundaries, recurring context, and active memory change. Trust: Determined by declared sensitivity and assistant role; private by default until reviewed.	uai-general-non-project-ai-memory-starter.zip

Views and presets over supported bundles

Team Memory: A lightweight shared team view over Project AI Memory plus owner and onboarding records. Model this as a view until UAIX has stronger role, permission, and multi-project guidance.
Product Memory: A durable product or feature-area view over project state, roadmap, decisions, and constraints. Model this as a view because the underlying files are the same as Project AI Memory plus Decision Memory.

Deferred configurations

Certification Memory: Evidence packet for formal certification or endorsement workflows. Deferred because UAIX does not currently publish certification, endorsement, or hosted validation support.
Regulated Data Memory: Memory that intentionally carries restricted personal, customer, legal, or compliance-sensitive material. Deferred until secure storage, redaction, access-control, and approval processes are outside the starter-bundle boundary.

Use the AI Memory Package Wizard when one supported starter configuration should become a package model, populated system profile, receiver brief, startup packet, manifest overlay, copy-paste file deck, Agent File Handoff plan required for Agent File Handoff configuration, LLM Wiki memory-plan file required for LLM Wiki configuration, readiness review, and canonical ZIP download.

Which Configuration To Choose

Situation	Use	Why
An active project needs continuity across AI sessions.	Project AI Memory	It keeps current state, constraints, decisions, next actions, and agent instructions alive without becoming a full wiki.
Ownership, execution, or responsibility is moving.	Project Handoff	It packages the transfer brief, acceptance criteria, owners, constraints, and verification plan.
An agent run was interrupted or must resume later.	Agent Session Memory	It keeps task-local state short-lived and prevents a whole chat transcript from becoming project truth.
A new human, contractor, stakeholder, or agent needs a curated start.	Onboarding Memory	It emphasizes overview, glossary, owners, first actions, and safe boundaries.
Rationale matters more than status.	Decision Memory	It preserves tradeoffs, rejected options, reversals, and open questions.
A client, vendor, or outside agent needs context.	Client or Vendor Handoff Memory	It adds redaction and approval guidance around a stricter external trust boundary.
An incident or audit needs a portable packet.	Incident or Audit Memory	It keeps timeline, evidence references, decisions, mitigations, owners, and follow-up together.
A deep wiki needs a portable snapshot.	LLM Wiki Export Memory	It exports reviewed wiki material into a compact packet without letting the wiki override project truth.
The organization needs durable, searchable institutional knowledge.	LLM Wiki	It is stronger for deep internal documentation, source synthesis, long-lived research, and broad knowledge accumulation.
A complicated, persistent, multi-actor ecosystem needs protected Totem and Taboo anchor governance.	Talisman System	It keeps protected-anchor change requests behind no-op behavior, human review, audit evidence, rollback, and external controls.

Project AI Memory And Project Handoff

Project Handoff is a subtype of UAI AI Memory. AI Memory is the broad standard: durable AI-readable context. Project Handoff is the transfer pattern: read the front door, load the selected files, summarize current truth, confirm constraints, name intended touchpoints, and name targeted checks before broad work.

For a small project, Project AI Memory and Project Handoff share overlapping required files by profile. For a larger organization, Project AI Memory stays alive during everyday work, while Project Handoff is prepared and reviewed when responsibility moves.

Inspect The Project AI Memory Starter

The visible files below are rendered from the same canonical template registry used by every supported bundle preset. The generated manifest is included in the ZIP and displayed with the other files so readers can inspect bundle ID, use case, lifecycle, trust boundary, file list, template IDs, and checksums.

30 files uai-ai-memory-starter.zip Bundle ID project-ai-memory Manifest fingerprint 183fe1ae78fa62bf

.uai/exports/manifest.json

Code example

{
    "bundle_id": "project-ai-memory",
    "name": "Project AI Memory",
    "description": "Ongoing working memory for an active project that needs durable context across humans, models, agents, and sessions.",
    "intended_use_case": "Use when a project is active and context must persist across many AI sessions without turning the bundle into a full knowledge base.",
    "lifecycle": "Maintained continuously; current-state and next-action files change often, decisions and constraints change carefully.",
    "download_filename": "uai-ai-memory-starter.zip",
    "display_order": 10,
    "trust_boundary_notes": "Internal or controlled collaboration by default. Review before sharing externally or giving to an autonomous agent.",
    "package_family_id": "project-developer-memory",
    "package_family_name": "Project / Developer Memory",
    "assistant_role": "",
    "assistant_relationship_type": "",
    "audience_model": "",
    "assistant_capability_summary": "",
    "included_files": [
        ".uai/identity.uai",
        ".uai/world-context.uai",
        ".uai/totem.uai",
        ".uai/taboo.uai",
        ".uai/short-term-memory.uai",
        ".uai/README.md",
        "AGENTS.md",
        ".uai/readme.human",
        ".uai/overview.uai",
        ".uai/current-state.uai",
        ".uai/open-questions.uai",
        ".uai/next-actions.uai",
        ".uai/risk-register.uai",
        ".uai/owners.uai",
        ".uai/agent-instructions.uai",
        ".uai/changelog.uai",
        ".uai/deployment-memory-and-test-report.uai",
        ".uai/context.uai",
        ".uai/stack.uai",
        ".uai/architecture.uai",
        ".uai/constraints.uai",
        ".uai/progress.uai",
        ".uai/operations.uai",
        ".uai/test-plan.uai",
        ".uai/style.uai",
        ".uai/coding-standards.uai",
        ".uai/decisions.uai",
        ".uai/memory.uai",
        ".uai/next-recursive-prompt.uai"
    ],
    "file_set_rule": "A UAIX package file is a universal required file, profile-required file, content-triggered required file, configuration-specific required file, or out-of-scope file. Files required by package facts, selected profile, declared capabilities, detected contents, selected configuration, user-provided memory, imported memory, generated artifacts, or visiting-agent self-assessment are required for that explicit package condition.",
    "standards_authority": "https://uaix.org/",
    "declared_package_profiles": [
        "project-ai-memory"
    ],
    "universal_required_files": [
        ".uai/identity.uai",
        ".uai/world-context.uai",
        ".uai/totem.uai",
        ".uai/taboo.uai",
        ".uai/short-term-memory.uai"
    ],
    "profile_required_file_sets": [
        {
            "profile": "project-ai-memory",
            "requirement": "Required for Project AI Memory packages",
            "files": [
                ".uai/README.md",
                "AGENTS.md",
                ".uai/readme.human",
                ".uai/overview.uai",
                ".uai/current-state.uai",
                ".uai/open-questions.uai",
                ".uai/next-actions.uai",
                ".uai/risk-register.uai",
                ".uai/owners.uai",
                ".uai/agent-instructions.uai",
                ".uai/changelog.uai",
                ".uai/deployment-memory-and-test-report.uai",
                ".uai/context.uai",
                ".uai/stack.uai",
                ".uai/architecture.uai",
                ".uai/constraints.uai",
                ".uai/progress.uai",
                ".uai/operations.uai",
                ".uai/test-plan.uai",
                ".uai/style.uai",
                ".uai/coding-standards.uai",
                ".uai/decisions.uai",
                ".uai/memory.uai",
                ".uai/next-recursive-prompt.uai"
            ]
        }
    ],
    "content_triggered_required_file_sets": [
        {
            "rule_id": "coding_standards",
            "requirement": "Required when code, automation, executable workflow, or code-like artifacts are present.",
            "matched_signals": [
                "project_or_developer_profile",
                "code_like_artifacts"
            ],
            "files": [
                ".uai/coding-standards.uai"
            ]
        },
        {
            "rule_id": "next_recursive_prompt",
            "requirement": "next-recursive-prompt.uai is required for agents that deal with code, automation, executable workflows, or code-like artifacts. It is not required for agents that don't deal with any coding.",
            "matched_signals": [
                "project_or_developer_profile",
                "code_like_artifacts"
            ],
            "files": [
                ".uai/next-recursive-prompt.uai"
            ]
        }
    ],
    "detected_requirement_signals": [
        "project_or_developer_profile",
        "code_like_artifacts"
    ],
    "required_files_effective": [
        ".uai/identity.uai",
        ".uai/world-context.uai",
        ".uai/totem.uai",
        ".uai/taboo.uai",
        ".uai/short-term-memory.uai",
        ".uai/README.md",
        "AGENTS.md",
        ".uai/readme.human",
        ".uai/overview.uai",
        ".uai/current-state.uai",
        ".uai/open-questions.uai",
        ".uai/next-actions.uai",
        ".uai/risk-register.uai",
        ".uai/owners.uai",
        ".uai/agent-instructions.uai",
        ".uai/changelog.uai",
        ".uai/deployment-memory-and-test-report.uai",
        ".uai/context.uai",
        ".uai/stack.uai",
        ".uai/architecture.uai",
        ".uai/constraints.uai",
        ".uai/progress.uai",
        ".uai/operations.uai",
        ".uai/test-plan.uai",
        ".uai/style.uai",
        ".uai/coding-standards.uai",
        ".uai/decisions.uai",
        ".uai/memory.uai",
        ".uai/next-recursive-prompt.uai"
    ],
    "not_required_files_with_reasons": [],
    "closed_required_file_policy": "UAIX package files are universal required, profile-required for an explicit package family, profile, mode, or package type, content-triggered required for detected contents or declared capabilities, configuration-specific required for selected configurations, or out of scope with a recorded reason.",
    "out_of_scope_rule": "A file outside the universal required set and outside declared package profiles is out of scope for this package.",
    "shared_files": [
        ".uai/identity.uai",
        ".uai/world-context.uai",
        ".uai/totem.uai",
        ".uai/taboo.uai",
        ".uai/short-term-memory.uai",
        ".uai/README.md",
        "AGENTS.md",
        ".uai/readme.human",
        ".uai/overview.uai",
        ".uai/current-state.uai",
        ".uai/open-questions.uai",
        ".uai/next-actions.uai",
        ".uai/risk-register.uai",
        ".uai/owners.uai",
        ".uai/agent-instructions.uai",
        ".uai/changelog.uai",
        ".uai/deployment-memory-and-test-report.uai",
        ".uai/context.uai",
        ".uai/stack.uai",
        ".uai/architecture.uai",
        ".uai/constraints.uai",
        ".uai/progress.uai",
        ".uai/operations.uai",
        ".uai/test-plan.uai",
        ".uai/style.uai",
        ".uai/coding-standards.uai",
        ".uai/decisions.uai",
        ".uai/memory.uai",
        ".uai/next-recursive-prompt.uai"
    ],
    "bundle_specific_files": [],
    "configuration_sections": [
        "Add wiki links only when deeper memory exists and is reviewed before promotion."
    ],
    "overlays": [
        "Use the shared README and AGENTS.md templates with Project AI Memory labels and ongoing-maintenance guidance."
    ],
    "files": [
        {
            "path": ".uai/identity.uai",
            "template_id": "uai-identity",
            "source": "template:uai-identity@1",
            "bytes": 2216,
            "sha256": "1987d3b153f917f5dc8b820cfe0bf025a53576b3344496d98cbb4ed3301562b3"
        },
        {
            "path": ".uai/world-context.uai",
            "template_id": "uai-world-context",
            "source": "template:uai-world-context@1",
            "bytes": 1834,
            "sha256": "a0b763015d6800eb606f7271c2cdc4ca3e2b3b0877dcd2e53ddb79885755418e"
        },
        {
            "path": ".uai/totem.uai",
            "template_id": "uai-totem",
            "source": "template:uai-totem@1",
            "bytes": 622,
            "sha256": "73f32acef19fc9f06d2dba2744412d1468595b896255906eed940baa4ad7a3c1"
        },
        {
            "path": ".uai/taboo.uai",
            "template_id": "uai-taboo",
            "source": "template:uai-taboo@1",
            "bytes": 654,
            "sha256": "b4b0393c2ea14e375d36d84dc80955ea094a2aee9b3b833feb184247287e3a33"
        },
        {
            "path": ".uai/short-term-memory.uai",
            "template_id": "uai-short-term-memory",
            "source": "template:uai-short-term-memory@1",
            "bytes": 2316,
            "sha256": "15de4d3faa1558bf0f8be29c81d62402d964238626b89e2c06eff7473c1a8bbd"
        },
        {
            "path": ".uai/README.md",
            "template_id": "readme",
            "source": "template:readme@1",
            "bytes": 2042,
            "sha256": "d62a69b5b5d70ced5407600308cb5f7e4d6f6aa4fa5ba8e2206095e906ad61b4"
        },
        {
            "path": "AGENTS.md",
            "template_id": "agents-md",
            "source": "template:agents-md@1",
            "bytes": 1858,
            "sha256": "0b69e407008a8bcb34bd7ac7cca7c21fb8e1d3cedc89e38b0f39804b38dbd7ef"
        },
        {
            "path": ".uai/readme.human",
            "template_id": "readme-human",
            "source": "template:readme-human@1",
            "bytes": 1139,
            "sha256": "ae057765145681fda25012a9dbe705a1bb05cf6e7bc6638a86e6db6e52664aed"
        },
        {
            "path": ".uai/overview.uai",
            "template_id": "project-overview",
            "source": "template:project-overview@1",
            "bytes": 492,
            "sha256": "39fa87d6ddcfd5060afdc9f223e3978d25544d43d6f6be690c01245ef03305ac"
        },
        {
            "path": ".uai/current-state.uai",
            "template_id": "current-state",
            "source": "template:current-state@1",
            "bytes": 325,
            "sha256": "ea4124581f681c39c21f55f4a6172a1af2b48a13cb4a44d6951cfe63fb4c1462"
        },
        {
            "path": ".uai/open-questions.uai",
            "template_id": "open-questions",
            "source": "template:open-questions@1",
            "bytes": 382,
            "sha256": "629fc8106161f23b5da9027a55078d16e9663ac44202ace5507fca766f260195"
        },
        {
            "path": ".uai/next-actions.uai",
            "template_id": "next-actions",
            "source": "template:next-actions@1",
            "bytes": 376,
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        },
        {
            "path": ".uai/risk-register.uai",
            "template_id": "risks-and-constraints",
            "source": "template:risks-and-constraints@1",
            "bytes": 830,
            "sha256": "8a35af3386d1f81160692a0691f31f6d80de71311ddbdeb55caa5fdf102da03b"
        },
        {
            "path": ".uai/owners.uai",
            "template_id": "contacts-and-owners",
            "source": "template:contacts-and-owners@1",
            "bytes": 283,
            "sha256": "472c67e2d4bab2608eca127209ff669b692495d2e96326a63aeb305d5da6f54f"
        },
        {
            "path": ".uai/agent-instructions.uai",
            "template_id": "agent-instructions",
            "source": "template:agent-instructions@1",
            "bytes": 1019,
            "sha256": "3945d08995ae18cb968beda0ca131f477e1ec594f3575e973a361305e5bc1944"
        },
        {
            "path": ".uai/changelog.uai",
            "template_id": "changelog",
            "source": "template:changelog@1",
            "bytes": 175,
            "sha256": "8a1d064f7d02294329200521e29d6d5dc0961a9ba5fd44fa21e75b2af5dd2016"
        },
        {
            "path": ".uai/deployment-memory-and-test-report.uai",
            "template_id": "deployment-report",
            "source": "template:deployment-report@1",
            "bytes": 935,
            "sha256": "dab28315ed510def2557450642658e7cec5de4d8a61ea7fc7c10ed9d165ad732"
        },
        {
            "path": ".uai/context.uai",
            "template_id": "uai-context",
            "source": "template:uai-context@1",
            "bytes": 285,
            "sha256": "aa289be70b0aabadcab8d7a60fc906ddf465f7392580a9be278570cd45788661"
        },
        {
            "path": ".uai/stack.uai",
            "template_id": "uai-stack",
            "source": "template:uai-stack@1",
            "bytes": 204,
            "sha256": "29f47ec11930fc90ba3c7ce77f37ae7b0638c12fd21a11ee897e93a366aea6f5"
        },
        {
            "path": ".uai/architecture.uai",
            "template_id": "uai-architecture",
            "source": "template:uai-architecture@1",
            "bytes": 278,
            "sha256": "403282c4d3df335be44b4237bb258fcfb060f79569ff4ad3c1ba0959eee29d85"
        },
        {
            "path": ".uai/constraints.uai",
            "template_id": "uai-constraints",
            "source": "template:uai-constraints@1",
            "bytes": 520,
            "sha256": "f0e8cd1948b215fae8fc97681c8348391b7d1a47a04444e1b936f716efd36853"
        },
        {
            "path": ".uai/progress.uai",
            "template_id": "uai-progress",
            "source": "template:uai-progress@1",
            "bytes": 188,
            "sha256": "c47bf1fe21e9b1ca62d0c33de793f052252b499fcf78f9228ee1253a97e1fc50"
        },
        {
            "path": ".uai/operations.uai",
            "template_id": "uai-operations",
            "source": "template:uai-operations@1",
            "bytes": 323,
            "sha256": "223ce4881883ee576721885162e6948285be16ad277fb4b95618aca87e2d85af"
        },
        {
            "path": ".uai/test-plan.uai",
            "template_id": "uai-test-plan",
            "source": "template:uai-test-plan@1",
            "bytes": 395,
            "sha256": "087ac4dfc7daf2d0628cb5fc1c5079030f57024cc618f2d5ac37d0590c903322"
        },
        {
            "path": ".uai/style.uai",
            "template_id": "uai-style",
            "source": "template:uai-style@1",
            "bytes": 331,
            "sha256": "b130ec2dbd3e0f3626cc145bc758fd7e4ce4b18c2502960608de5513f20f3209"
        },
        {
            "path": ".uai/coding-standards.uai",
            "template_id": "uai-coding-standards",
            "source": "template:uai-coding-standards@1",
            "bytes": 2047,
            "sha256": "9e82c8ea5fdf8b95459824cb503a505155e40301a729281d8fabfb9ea630da42"
        },
        {
            "path": ".uai/decisions.uai",
            "template_id": "uai-decisions",
            "source": "template:uai-decisions@1",
            "bytes": 150,
            "sha256": "7d5dca211562cbd843d0428ea3d5cceadb4c58967363caaefa6a41f34bea0286"
        },
        {
            "path": ".uai/memory.uai",
            "template_id": "uai-memory",
            "source": "template:uai-memory@1",
            "bytes": 1161,
            "sha256": "3ee2bc2965c6676d1dd0ecfeb500d3fb3bc2012f70a3e85ec70d94c120c057e6"
        },
        {
            "path": ".uai/next-recursive-prompt.uai",
            "template_id": "uai-next-recursive-prompt",
            "source": "template:uai-next-recursive-prompt@1",
            "bytes": 8367,
            "sha256": "20dbf651b0a9a030c4078094d368bb21c75bac34411b0ab45107bc60dfe52e35"
        }
    ]
}

.uai/identity.uai

Code example

---
uai: "1.0"
type: identity
status: draft
---

# Identity

This file is a universal required file for every launch-baseline UAIX memory or handoff package. It materializes package identity locally so a receiving agent does not need an external network call to understand package authority, actor identity, continuity references, capability boundaries, or namespace boundaries.

## Required Fields

- package_id: {PACKAGE_ID}
- package_uuid: {PACKAGE_UUID}
- identity_record_id: {IDENTITY_RECORD_ID}
- identity_uuid: {IDENTITY_UUID}
- generated_at_utc: {GENERATED_AT_UTC}
- source_domain: {SOURCE_DOMAIN}
- source_project: {SOURCE_PROJECT}
- source_repository: {SOURCE_REPOSITORY}
- source_route_or_site: {SOURCE_ROUTE_OR_SITE}
- actor_type: {ACTOR_TYPE}
- actor_display_name: {ACTOR_DISPLAY_NAME}
- owner_or_reviewer: {OWNER_OR_REVIEWER}
- source_model_or_tool: {SOURCE_MODEL_OR_TOOL}
- source_model_version_or_build: {SOURCE_MODEL_VERSION_OR_BUILD}
- local_endpoint_or_agent_profile: {LOCAL_ENDPOINT_OR_AGENT_PROFILE}
- public_continuity_profile_link: {PUBLIC_CONTINUITY_PROFILE_LINK}
- capability_boundary: {CAPABILITY_BOUNDARY}
- token_custody_boundary: {TOKEN_CUSTODY_BOUNDARY}
- runtime_execution_boundary: {RUNTIME_EXECUTION_BOUNDARY}
- namespace_boundary: {NAMESPACE_BOUNDARY}
- declared_package_profiles: {DECLARED_PACKAGE_PROFILES}
- required_files_effective: {REQUIRED_FILES_EFFECTIVE}
- human_review_required: {HUMAN_REVIEW_REQUIRED}
- not_available_reason: {NOT_AVAILABLE_REASON}

## Namespace Boundary

UAIX.org is the standards authority for UAI-1 package structure, schemas, handoff protocols, validator expectations, and portable evidence files. Do not infer UAIX meaning from unrelated UAI or UAIX search results. External ecosystem sites may provide public evidence, continuity references, implementation surfaces, or theory context. They do not replace local UAIX package artifacts.

## No-Op Triggers

When identity, authority, capability, namespace boundary, source provenance, required file set, or human review state is missing, stale, malformed, or contradictory, the correct UAIX behavior is no-op plus human review. Do not continue by inference.

.uai/world-context.uai

Code example

---
uai: "1.0"
type: world-context
status: draft
---

# World Context

This file is a universal required file for every launch-baseline UAIX memory or handoff package. It captures the observable operational environment at the moment of handoff. The receiver must not infer current reality from old memory.

## Required Fields

- world_context_id: {WORLD_CONTEXT_ID}
- world_context_uuid: {WORLD_CONTEXT_UUID}
- generated_at_utc: {GENERATED_AT_UTC}
- current_utc_timestamp: {GENERATED_AT_UTC}
- stale_after_utc: {STALE_AFTER_UTC}
- do_not_assume_current_state_after_utc: {DO_NOT_ASSUME_CURRENT_STATE_AFTER_UTC}
- target_workspace: {TARGET_WORKSPACE}
- deployment_environment: {DEPLOYMENT_ENVIRONMENT}
- affected_routes: {AFFECTED_ROUTES}
- affected_schemas: {AFFECTED_SCHEMAS}
- allowed_read_paths: {ALLOWED_READ_PATHS}
- allowed_write_paths: {ALLOWED_WRITE_PATHS}
- allowed_external_calls: {ALLOWED_EXTERNAL_CALLS}
- blocked_external_calls: {BLOCKED_EXTERNAL_CALLS}
- validation_expectations: {VALIDATION_EXPECTATIONS}
- test_expectations: {TEST_EXPECTATIONS}
- no_op_triggers: {NO_OP_TRIGGERS}
- human_review_required: {HUMAN_REVIEW_REQUIRED}
- not_available_reason: {NOT_AVAILABLE_REASON}

## Observable Environment

Record branch, route, schema, deployment target, source-document, file-intake, date/time, safety-critical, telemetry, and external-system constraints that affect this handoff. Memory is not current reality. A path mention is not workspace authority. A model's confidence is not provenance.

## No-Op Triggers

When target workspace, temporal freshness, world-context, environmental constraints, evidence, namespace boundary, or required file set is missing, stale, malformed, or contradictory, the correct UAIX behavior is no-op plus human review. Do not continue by inference.

.uai/totem.uai

Code example

---
uai: "1.0"
type: totem
status: draft
---

# Totem

This file is a universal required file for every launch-baseline UAIX memory or handoff package. It holds human-supplied positive anchors, purpose, charter language, and values the receiving agent should preserve while staying inside source authority and evidence boundaries.

## Human-Supplied Anchors

- {NOT_AVAILABLE_REASON}

## Update Rule

Only promote reviewed, owner-supplied positive anchors. If no project-specific values have been supplied, treat this file as an explanatory placeholder and continue with the rest of the package read order.

.uai/taboo.uai

Code example

---
uai: "1.0"
type: taboo
status: draft
---

# Taboo

This file is a universal required file for every launch-baseline UAIX memory or handoff package. It holds human-supplied hard boundaries, blocked actions, and no-op triggers the receiving agent must respect.

## Human-Supplied Boundaries

- {NOT_AVAILABLE_REASON}

## No-Op Rule

If a requested action conflicts with human-supplied values in this file, public support boundaries, source authority, identity, capability, world-context, or domain lane boundaries, stop broad execution, summarize the conflict, and request human review. Do not rewrite boundaries to make an action pass.

.uai/short-term-memory.uai

Code example

---
uai: "1.0"
type: short-term-memory
status: draft
---

# Short-Term Memory

This is the compact current working memory for the project. Keep it inside `.uai/` with the other typed UAI records so future agents have one predictable folder to load.

## Current Focus

- Current task:
- Current blocker:
- Current owner:
- Current evidence ledger:

## Required Read Set

- `AGENTS.md`
- `.uai/identity.uai`
- `.uai/world-context.uai`
- `.uai/totem.uai`
- `.uai/taboo.uai`
- `.uai/startup-packet.uai`
- `.uai/system-profile.uai`
- `.uai/receiver-brief.uai`
- `.uai/index.md`
- `.uai/context.uai`
- `.uai/constraints.uai`
- `.uai/progress.uai`
- `.uai/operations.uai`
- `.uai/test-plan.uai`
- `.uai/coding-standards.uai`
- `.uai/decisions.uai`
- `.uai/memory.uai`

## Hygiene Rule

Use `.uai/archives/`, `.uai/`, and `.uai/exports/` as the default generated package shape. Do not create a separate memory folder, wiki folder, or random handoff `.md` files by default. If legacy non-.uai memory, wiki-memory folders, or stray notes already exist, review them, move useful current facts into `.uai/short-term-memory.uai` or the right typed `.uai/*.uai` record, preserve durable reviewed history in the named long-term wiki/archive or `.uai/archives/` evidence, record what moved, then remove or clearly retire the mistaken path so it cannot keep steering agents.

## Principles Traceability

Principle-bearing changes must be classified as current public operating principle, governance-review principle, planned principle, or research-track principle before they affect public trust, AI Memory, agent communication, capability description, handoff structure, privacy, accessibility, analytics, or support claims. Use UAIX Principles Charter at `https://uaix.org/en-us/governance/principles/`, Principles Role Guidance at `https://uaix.org/en-us/governance/principles-role-guidance/`, `docs/governance/principles-traceability-matrix.md`, and `docs/templates/principles-impact-assessment.md`.

This principles layer is governance and release-review evidence. It is not certification, endorsement, legal recognition, runtime control, SDK or CLI support, hosted import validation, automatic sync, security operations, consent center, policy office, or proof of UAI-1 conformance.

.uai/README.md

Code example

# Project AI Memory

This starter bundle is a UAI AI Memory configuration. It keeps portable, human-readable context in files that another person, team, or AI agent can inspect before acting.

## Bundle Purpose

Ongoing working memory for an active project that needs durable context across humans, models, agents, and sessions.

## Use This When

Use when a project is active and context must persist across many AI sessions without turning the bundle into a full knowledge base.

## Lifecycle

Maintained continuously; current-state and next-action files change often, decisions and constraints change carefully.

## Trust Boundary

Internal or controlled collaboration by default. Review before sharing externally or giving to an autonomous agent.

## Included Files

- `.uai/identity.uai`
- `.uai/world-context.uai`
- `.uai/totem.uai`
- `.uai/taboo.uai`
- `.uai/short-term-memory.uai`
- `.uai/README.md`
- `AGENTS.md`
- `.uai/readme.human`
- `.uai/overview.uai`
- `.uai/current-state.uai`
- `.uai/open-questions.uai`
- `.uai/next-actions.uai`
- `.uai/risk-register.uai`
- `.uai/owners.uai`
- `.uai/agent-instructions.uai`
- `.uai/changelog.uai`
- `.uai/deployment-memory-and-test-report.uai`
- `.uai/context.uai`
- `.uai/stack.uai`
- `.uai/architecture.uai`
- `.uai/constraints.uai`
- `.uai/progress.uai`
- `.uai/operations.uai`
- `.uai/test-plan.uai`
- `.uai/style.uai`
- `.uai/coding-standards.uai`
- `.uai/decisions.uai`
- `.uai/memory.uai`
- `.uai/next-recursive-prompt.uai`

## Maintenance Rule

Update the files that changed because project truth changed. Do not turn this bundle into a dump of old chats, private notes, raw logs, or unreviewed generated summaries.

## Review Before Sharing

- Remove secrets, credentials, private keys, tokens, and raw customer data.
- Remove internal-only strategy unless the recipient is approved for it.
- Keep support, security, legal, compliance, certification, and endorsement claims tied to public evidence.
- Make uncertain or unreviewed material explicit.

AGENTS.md

Code example

# My Project AI Memory

This file is the front door for AI work in this repository. Read it first, then load the listed `.uai` and `.uai/exports` files before planning or editing.

## Handoff Summary

- This project uses UAI AI Memory so future work does not depend on private chat history.
- The active bundle configuration is `project-ai-memory`: Ongoing working memory for an active project that needs durable context across humans, models, agents, and sessions.
- Confirmed operating truth belongs in these files, canonical docs, code, tests, release notes, or public records.
- LLM Wiki, old chats, generated summaries, and dropped files are background until reviewed and promoted.

## Loaded Context

@memory[.uai/context.uai]
@memory[.uai/constraints.uai]
@memory[.uai/memory.uai]
@memory[.uai/exports/manifest.json]

## Required First Response

Before broad work, the next AI should:

1. Read this file completely.
2. Read `.uai/readme.human`.
3. Load every file listed in Loaded Context.
4. Summarize the project, current state, and immediate task in 3-5 bullets.
5. Confirm constraints, trust boundaries, secrets handling, and destructive-operation limits.
6. Name the files, routes, services, docs, or data it expects to touch.
7. Name the targeted checks it expects to run, or explain why a check cannot run.

If a required file is missing, unreadable, circular, or contradictory, stop and report that before editing.

## Do Not Change Without Explicit Approval

- Do not use destructive filesystem or git operations.
- Do not expose secrets, credentials, customer data, or unapproved private material.
- Do not widen support, certification, compliance, security, or endorsement claims without evidence.
- Do not treat generated output, old chats, dropped files, or wiki notes as current truth until promoted.

.uai/readme.human

Code example

# My Project Human Briefing

Updated: YYYY-MM-DD

This file is for humans working with AI on this project. It explains what the AI sees, protects, and needs clarified. It does not override `AGENTS.md`, `.uai/constraints.uai`, system instructions, repository rules, laws, policies, or the human's current request.

## What You Need To Know

- The AI reads root `AGENTS.md` first, then this file inside `.uai/`, then the listed context files.
- This bundle is `Project AI Memory`.
- The trust boundary is: Internal or controlled collaboration by default. Review before sharing externally or giving to an autonomous agent.

## Things The AI Will Defend

- Current support boundaries.
- Private data, secrets, credentials, and customer trust.
- Existing user work in the tree.
- Review and targeted checks before public claims widen.

## Things Humans Should Make Explicit

- Whether the task may touch production, public docs, billing, legal language, security posture, or irreversible data.
- Whether the AI should update durable memory after the change.
- Which checks are required before the work is considered done.

.uai/overview.uai

Code example

# Project Overview

## Purpose

Describe what the project exists to do, who it serves, and what outcome matters most.

## Current Scope

- In scope:
- Out of scope:
- Current public or operational surface:

## Source Of Truth

- Code:
- Docs:
- Machine artifacts:
- Release notes or changelog:

## Success Criteria

- A new human or AI can understand the project without private chat history.
- Claims are tied to evidence.
- Constraints are visible before work begins.

.uai/current-state.uai

Code example

# Current State

## What Is True Now

- Live or supported now:
- Experimental now:
- Planned but not supported:

## Recently Changed

- YYYY-MM-DD:

## Active Work

- Current focus:
- Active owner:
- Targeted checks:

## Stale Or Risky Context

List anything that should not be trusted without rechecking.

.uai/open-questions.uai

Code example

# Open Questions

Use this file for questions that should block, steer, or qualify future work.

| Question | Why It Matters | Owner | Needed By | Status |
|---|---|---|---|---|
|  |  |  |  | open |

## Escalation Rule

If a question affects safety, privacy, legal commitments, public support claims, production data, or destructive operations, stop and ask before acting.

.uai/next-actions.uai

Code example

# Next Actions

Keep this file current and actionable. Remove completed work or move meaningful completions to `.uai/changelog.uai`.

## Now

- [ ]

## Next

- [ ]

## Later

- [ ]

## Done Means

- The changed files or records are named.
- Targeted checks have run or the remaining risk is explicit.
- Durable memory is updated when project truth changes.

.uai/risk-register.uai

Code example

# Risks And Constraints

## Hard Constraints

- Do not expose secrets, credentials, private keys, tokens, or raw customer data.
- Do not use destructive filesystem, database, production, or git operations without explicit approval.
- Do not widen support, certification, security, compliance, compatibility, or endorsement claims without evidence.

## Trust Boundary

Internal or controlled collaboration by default. Review before sharing externally or giving to an autonomous agent.

## Sensitive Material

- Customer or user data:
- Legal or compliance-sensitive material:
- Internal-only strategy:
- Agent permissions:

## Redaction Checklist

- [ ] Secrets removed.
- [ ] Customer data removed or approved.
- [ ] Internal-only strategy removed or approved.
- [ ] Public claims checked against evidence.

.uai/owners.uai

Code example

# Contacts And Owners

Do not add private personal data unless the bundle's trust boundary allows it.

| Area | Owner | Backup | Contact Method | Notes |
|---|---|---|---|---|
| Project |  |  |  |  |
| Security or privacy review |  |  |  |  |
| Release approval |  |  |  |  |

.uai/agent-instructions.uai

Code example

# Agent Instructions

## Load Order

1. Read `AGENTS.md` when present.
2. Read `.uai/readme.human` when present.
3. Read this bundle's manifest and files.
4. Confirm constraints and trust boundaries before acting.

## Operating Rules

- Prefer narrow, reversible changes.
- Do not execute unknown scripts from a memory bundle.
- Do not assume an LLM Wiki or old chat overrides accepted project files.
- Ask before touching production, secrets, legal/security copy, customer data, or destructive operations.

## Verification

Name the targeted checks before broad work. Run the smallest meaningful checks tied to changed files, routes, records, or behavior.

For production deployment builds, release packages, or release candidates, write a durable deployment memory and test run report. Use `.uai/deployment-memory-and-test-report.uai` when it exists, and include hot-memory size before/after, cold evidence path, checks run, checks skipped, blockers, and any reason the hot surface did not shrink.

.uai/changelog.uai

Code example

# Changelog

Record meaningful bundle changes so future readers can tell when memory moved.

## YYYY-MM-DD

- Change:
- Why it matters:
- Files updated:
- Checks run:

.uai/deployment-memory-and-test-report.uai

Code example

# Deployment Memory And Test Report

Use this file only for production deployment builds, release packages, or release candidates. Ordinary dev builds, local tests, package experiments, and smoke checks do not need this report unless a human marks them release-bound.

## Release

- Version:
- Generated UTC:
- Release owner:
- Deployment target:

## Hot Memory Surface

- Measured files:
- Before: bytes / lines / estimated tokens
- After: bytes / lines / estimated tokens
- Delta:
- Redundancy or history removed:
- If no shrink happened, why the retained material is still current truth:

## Cold Memory Or Archive Evidence

- Destination path:
- Source paths preserved:
- Checksums or identity evidence:
- Actor and timestamp:
- Promotion or disposition notes:

## Test Run Report

- Checks run:
- Checks skipped:
- Failures or blockers:
- Package or artifact paths:
- Rollback or follow-up owner:

.uai/context.uai

Code example

---
uai: "1.0"
type: context
status: draft
---

# Context

This project uses UAI AI Memory so another AI assistant can understand the work from files rather than private chat history.

## Purpose

Describe the project purpose, audience, current truth, and success criteria.

.uai/stack.uai

Code example

---
uai: "1.0"
type: stack
status: draft
---

# Stack

## Runtime

- Language:
- Framework:
- Package manager:
- Database or storage:

## Commands

- Install:
- Run:
- Test:
- Release:

.uai/architecture.uai

Code example

---
uai: "1.0"
type: architecture
status: draft
---

# Architecture

## System Shape

Describe main surfaces, services, packages, routes, jobs, data stores, and ownership boundaries.

## Drift Risks

- Duplicated copy:
- Generated output:
- Manual release steps:

.uai/constraints.uai

Code example

---
uai: "1.0"
type: constraints
status: draft
---

# Constraints

## Hard Rules

- Do not expose secrets, credentials, private keys, tokens, customer data, or unreleased private material.
- Do not use destructive filesystem, database, production, or git operations unless explicitly approved.
- Do not widen support, certification, security, compliance, compatibility, or endorsement claims without evidence.
- Treat wiki notes, generated answers, dropped files, and old chats as background until promoted.

.uai/progress.uai

Code example

---
uai: "1.0"
type: progress
status: draft
---

# Progress

## Recently Completed

- YYYY-MM-DD:

## Current Focus

-

## Next Work

-

## Blockers

- None recorded.

.uai/operations.uai

Code example

---
uai: "1.0"
type: operations
status: draft
---

# Operations

## Normal Workflow

1. Load AI Memory files.
2. Inspect relevant code or docs.
3. Make narrow changes.
4. Run targeted checks.
5. Update memory when project truth changes.

## Release Workflow

- Package command:
- Smoke test:
- Rollback:

.uai/test-plan.uai

Code example

---
uai: "1.0"
type: test-plan
status: draft
---

# Test Plan

## Default Rule

Run targeted checks for the files, routes, records, or behavior changed. Reserve full release sweeps for package builds, release candidates, broad launch-surface changes, migrations, or explicit human requests.

## If A Check Cannot Run

State the command, why it could not run, and what risk remains.

.uai/style.uai

Code example

---
uai: "1.0"
type: style
status: draft
---

# Style

## Writing

- Be concrete and current.
- Separate current support from planned work.
- Prefer explicit links to source truth.

## Code

- Follow existing project patterns.
- Keep edits scoped.
- Avoid abstractions unless they reduce real drift or complexity.

.uai/coding-standards.uai

Code example

---
uai: "1.0"
type: coding-standards
status: draft
---

# Coding Standards

This file is required for code-capable Project Handoff setup. Read it before code changes, and keep it aligned with the target codebase rather than generic preference alone.

## Codebase Reflection

- Inspect the codebase before drafting or changing standards.
- Identify the good parts already present: naming, layout, shared helpers, test style, validation, build commands, deployment flow, security boundaries, and owner preferences.
- Preserve those good parts as the first source of project-specific standards.
- If the project is new, create an initial standard from the selected language, framework, package manager, test runner, deployment target, and owner instructions.

## Required Defaults

- Prefer DRY design and do not repeat yourself when a shared helper, registry, template, fixture, or typed record can remove real duplication.
- Apply "once and only once": each business rule, route definition, schema shape, version value, support claim, validation rule, and deployment fact should have one canonical owner whenever practical.
- Apply SOLID principles by default: single-purpose units, extension without risky rewrites, substitutable contracts, narrow interfaces, and dependency direction that keeps policy decoupled from implementation details.
- Keep changes scoped, reversible, and aligned with existing architecture.
- Use structured APIs, parsers, and framework helpers instead of brittle string manipulation when available.

## Automated Testing

Automated testing is required no matter what language or framework the project uses. Record unit, integration, smoke, lint, type, format, route, package, or deployment checks in `.uai/test-plan.uai`.

For each code change, run targeted automated checks for the touched behavior. If no harness exists, create or document the smallest repeatable automated check before relying on manual verification. If a check cannot run, record the command, reason, and residual risk.

.uai/decisions.uai

Code example

---
uai: "1.0"
type: decisions
status: draft
---

# Decisions

Record accepted decisions, why they were made, and what would cause a reversal.

.uai/memory.uai

Code example

---
uai: "1.0"
type: memory
status: draft
---

# AI Memory

AI Memory is durable, reviewable context that lets a future AI continue useful work without relying on private chat history.

## Bundle Configuration

- Bundle: Project AI Memory
- Use case: Use when a project is active and context must persist across many AI sessions without turning the bundle into a full knowledge base.
- Trust boundary: Internal or controlled collaboration by default. Review before sharing externally or giving to an autonomous agent.

## UAI AI Memory And LLM Wiki

Use UAI AI Memory for compact, portable working packets. Use an LLM Wiki for deep, long-lived internal documentation. Use both when a durable knowledge base needs a reviewed export, handoff packet, onboarding packet, audit packet, or agent-ready task context.

## Promotion Rule

1. Capture raw knowledge in notes, wiki pages, or source documents.
2. Review for accuracy, ownership, privacy, and support boundaries.
3. Promote accepted project truth into AI Memory, canonical docs, code, tests, release notes, or roadmap state.
4. Keep unreviewed material out of governing instructions.

.uai/next-recursive-prompt.uai

Code example

{
  "uai_version": "1.0",
  "profile": "uaix.next-recursive-prompt.v1",
  "schema_version": 1,
  "scope": {
    "scope_id": "{{PACKAGE_SLUG}}",
    "scope_path": ".",
    "local_uai_root": ".uai/",
    "code_scope": true,
    "scope_basis": ["code", "automation", "executable-workflow", "code-like-artifact"],
    "requirement_rule": "next-recursive-prompt.uai is required for agents that deal with code, automation, executable workflows, or code-like artifacts. It is not required for agents that don't deal with any coding.",
    "out_of_scope_rule": "next-recursive-prompt.uai is not required for agents that don't deal with any coding.",
    "source_boundary": "Derived from authoritative package files. This record is not a second source of truth."
  },
  "lifecycle": {
    "status": "active",
    "generated_at_utc": "{GENERATED_AT_UTC}",
    "valid_until_utc": "{VALID_UNTIL_UTC}",
    "attempt": 1,
    "supersedes_checksum": ""
  },
  "activation_policy": {
    "activation_rule": "Use the stored next_loop plan when the user indicates continuation or resume intent, including keep going, continue, do the next thing, resume, proceed, or use the next recursive prompt.",
    "relevance_review_rule": "When a new user request directly relates to the stored next_loop, review this file for useful plan ideas before discarding or superseding it.",
    "intake_precedence_rule": "For packages using Agent File Handoff, active Content or Improvement files that relate to the current prompt supersede or expand the stored next_loop. Intake must still lead to concrete project work, hot-memory update, ledger evidence, and archive movement or a recorded keep-active reason.",
    "current_instruction_rule": "When the user provides a specific unrelated instruction, current user instruction governs the turn and overwrites the stored next-loop plan.",
    "regeneration_rule": "After accepted work, update authoritative .uai records first, then regenerate .uai/next-recursive-prompt.uai from those records.",
    "non_activation_examples": ["A new unrelated feature request.", "A direct request to inspect, test, deploy, or explain a different target.", "A human correction that changes the work objective."]
  },
  "objective": {
    "task_id": "{TASK_ID}",
    "summary": "{CURRENT_GOAL}",
    "priority": "{PRIORITY}",
    "done_criteria": ["{SUCCESS_EVIDENCE}", "Authoritative .uai records are updated before this derived file is regenerated.", "No secrets, raw traces, or unreviewed cold-memory claims are copied into hot memory."]
  },
  "authoritative_refs": {
    "agents_md": "AGENTS.md",
    "readme_human": ".uai/readme.human",
    "identity": ".uai/identity.uai",
    "world_context": ".uai/world-context.uai",
    "totem": ".uai/totem.uai",
    "taboo": ".uai/taboo.uai",
    "short_term_memory": ".uai/short-term-memory.uai",
    "startup_packet": ".uai/startup-packet.uai",
    "system_profile": ".uai/system-profile.uai",
    "receiver_brief": ".uai/receiver-brief.uai",
    "coding_standards": ".uai/coding-standards.uai",
    "stack": ".uai/stack.uai",
    "architecture": ".uai/architecture.uai",
    "context": ".uai/context.uai",
    "constraints": ".uai/constraints.uai",
    "progress": ".uai/progress.uai",
    "current_state": ".uai/current-state.uai",
    "decisions": ".uai/decisions.uai",
    "next_actions": ".uai/next-actions.uai",
    "test_plan": ".uai/test-plan.uai",
    "manifest": ".uai/exports/manifest.json"
  },
  "resume_context": {
    "current_truth_summary": ["Use .uai/short-term-memory.uai for current truth.", "Use this file only to resume the next loop quickly after authoritative memory has been read.", "If this summary conflicts with authoritative refs, stop and regenerate this file from those refs."],
    "recent_changes": [],
    "active_blockers": [],
    "why_now": "A code-bearing package needs a compact next-loop resume artifact after authoritative files have been loaded."
  },
  "next_loop": {
    "mode": "implement-then-verify",
    "first_response_contract": {
      "must_report": ["loaded context", "hard constraints", "expected touchpoints", "targeted checks"],
      "max_bullets": 6
    },
    "prompt": "Continue from this UAIX package when the user asks to continue, keep going, do the next thing, resume, or gives a directly related request. Read authoritative_refs first, treat .uai/next-recursive-prompt.uai as derived hot-memory only, use relevant plan ideas, and enumerate active File Handoff intake; related intake supersedes or expands the stored loop and still requires project work before archive movement. Perform the next safe work chunk, run targeted checks, update .uai memory, regenerate this file from authoritative records, and provide the next recursive prompt. If the user gives a specific unrelated request, follow the current user instruction and regenerate this file after accepted work.",
    "ordered_steps": [
      "Read AGENTS.md and required .uai files named in authoritative_refs.",
      "Review .uai/next-recursive-prompt.uai for relevant ideas when the current request continues, resumes, or directly relates to the stored next loop.",
      "When Agent File Handoff is enabled, enumerate active Content and Improvement files; related intake supersedes or expands this next loop and must produce project work before archive movement.",
      "Verify workspace, identity, world context, Totem, Taboo, constraints, coding standards, stack, architecture, current state, and test plan.",
      "Process active intake before unrelated work when file handoff is enabled.",
      "Implement the smallest safe improvement that advances the stated objective.",
      "Run targeted automated checks and record skipped checks with reasons.",
      "Update short-term memory, progress, test plan, and this derived next-recursive prompt.",
      "Report changed files, tests, blockers, and the next recursive work prompt."
    ],
    "if_blocked": {
      "action": "emit-blocked-state",
      "required_updates": [".uai/progress.uai", ".uai/current-state.uai", ".uai/next-actions.uai", ".uai/next-recursive-prompt.uai"],
      "human_escalation_reason_template": "State the blocker, the safe next step, and the precise approval or evidence needed."
    }
  },
  "checks": {
    "required": ["PHP lint for touched PHP files", "JS syntax check for touched browser assets", "JSON/XML parse for touched machine records", "Playwright or rendered-route checks for touched wizard UI when available", "git diff --check"],
    "not_required_for_this_scope": [],
    "last_known_results": []
  },
  "writeback_policy": {
    "authority_rule": "Derived hot-memory resume artifact; not a second source of truth. Authoritative .uai records win on conflict. Regenerate from authoritative handoff files after meaningful work.",
    "must_update_before_success": [".uai/short-term-memory.uai", ".uai/progress.uai", ".uai/test-plan.uai", ".uai/intake-outcome-ledger.uai when file handoff is enabled", ".uai/next-recursive-prompt.uai"],
    "update_decisions_if_changed": ".uai/decisions.uai",
    "never_copy_into_hot_files": ["raw traces", "secrets", "private customer data", "large tool logs", "unreviewed cold-memory claims"],
    "conflict_rule": "Authoritative .uai records win on conflict. Regenerate this file from authoritative handoff files before using it again."
  },
  "security": {
    "approval_required_for": ["production deploy", "destructive repository operations", "schema boundary changes", "public support-claim widening"],
    "no_op_triggers": ["missing_authoritative_ref", "stale_constraints", "integrity_mismatch", "scope_conflict", "conflict_with_human_instruction", "conflict_with_repository_policy"],
    "escalation_triggers": ["support boundary would widen", "runtime behavior would be implied", "non-coding package would be made to look code-required", "code-bearing package lacks required coding memory"],
    "local_policy_wins": true
  },
  "cold_memory": {
    "refs": []
  },
  "provenance": {
    "trigger": "starter-template",
    "generated_by": "UAIX AI Memory starter template",
    "runtime_id": "",
    "issued_at_utc": "{GENERATED_AT_UTC}"
  },
  "integrity": {
    "canonicalization": "canonical-json",
    "yaml_mirror_allowed": false,
    "checksum": "sha256:{RECEIVER_COMPUTES_AFTER_WRITE}",
    "source_digests": [],
    "signatures": []
  }
}

What Belongs In AI Memory

Project overview, current state, decisions, open questions, next actions, risks, constraints, owners, glossary, and agent instructions.
Root AGENTS.md plus local memory files such as .uai/readme.human when agents need a predictable load path.
Typed .uai files when the project needs explicit context, stack, architecture, constraints, progress, operations, test planning, style, decisions, or memory rules.
Links to deeper docs or LLM Wiki pages only when those sources are reviewed and clearly marked as background or promoted truth.

What Should Not Be Included

Secrets, credentials, private keys, tokens, connection strings, or unreviewed production logs.
Raw customer, patient, employee, or user data unless a secure approved process exists.
Private legal analysis, internal-only strategy, pricing, security details, or unsupported support claims.
Old chats, generated summaries, dropped files, and LLM Wiki pages treated as truth without review.
Executable payloads that a future agent might run without human approval.

Privacy And Trust Boundaries

Choose the bundle by trust boundary, not by name alone. Internal Project AI Memory can carry more operational detail than an external handoff. Agent Session Memory records tool permissions when the profile requires them and temporary work state that should be archived quickly. External Handoff, Incident/Audit, and LLM Wiki Export packets need redaction, approval, and clear source notes before sharing.

Review secrets and credentials before every share.
Minimize customer or user data.
Mark internal-only strategy and legal material.
Name agent permissions and blocked actions.
Prefer sanitized exports over raw internal memory.

Maintenance Model

AI Memory is not a dumping ground. Keep high-churn files current and keep durable files stable. .uai/CURRENT_STATE.md and .uai/NEXT_ACTIONS.md can change often. .uai/DECISIONS.md should be append-first or carefully revised. .uai/RISKS_AND_CONSTRAINTS.md and .uai/AGENT_INSTRUCTIONS.md should be reviewed whenever permissions, production boundaries, support claims, or safety posture change. .uai/CHANGELOG.md should explain meaningful bundle updates.

Run a context diet when the packet starts carrying old history. Preserve the pre-slim version in cold memory first, record the source path, final path, checksum, actor, time, and disposition, then shorten the active file to current truth plus a pointer.

How Agents Consume AI Memory

Read the manifest and front-door files before acting.
Load only the files required by the bundle and current task.
Report missing, circular, contradictory, unreadable, or oversized memory before broad work.
Summarize current truth, constraints, intended touchpoints, and checks before editing.
Treat LLM Wiki, old chat, generated summaries, and dropped files as background until reviewed and promoted.

Site, Solution, Or Workspace Placement

For one WordPress site, keep the local .uai/ folder at the individual site root and use root AGENTS.md as the entry point. For one Visual Studio solution, keep .uai/ beside the real .sln or .slnx file, then explicitly register every generated .uai file as solution items so they appear in Solution Explorer. A physical folder on disk is not enough by itself. In both cases .uai/readme.human and typed .uai records stay inside the local memory folder.

For classic .sln files, that means adding a .uai solution folder with a ProjectSection(SolutionItems) entry for each generated file. After the solution file is updated, verify every referenced .uai path exists and reload Visual Studio if the solution was already open.

Use project-level .uai/ folders inside a Visual Studio solution only when projects have independent ownership, release, or handoff boundaries. In that rarer shape, a solution-level workspace.uai can coordinate those project folders; otherwise the more common coordinator is a higher-level workspace or organization workspace.uai that routes across multiple solutions.

For multiple WordPress sites or Visual Studio solutions in one ecosystem, use workspace.uai as the only UAI memory file outside local .uai/ folders. Each selected site or solution AGENTS.md should point to both that coordinator and its own local .uai/ folder, and the agent should resolve the explicit human domain, route, repository, solution, or path before loading local memory. The selected target’s hot memory loads; sibling .uai bundles stay unloaded unless the task explicitly asks for cross-target source routing, authority comparison, package coordination, or archive preservation.

If the package will steer deployment, include a workspace instruction surface that names the deployment owner, shared version policy, publish folders, install targets, checksum or rollback evidence, and any mixed-stack differences. A workspace where WordPress sites use consistent theme/plugin upload folders but .NET solutions deploy differently should say that in workspace.uai instead of leaving future agents to infer it from filenames.

Before relying on a remembered absolute coordinator path, verify the coordinator file exists and that the selected registry root plus AGENTS.md path resolve. If a pointer is stale, locate workspace.uai only far enough to confirm the intended router, repair or report the stale path, and never silently fall back to the current shell directory when the human named another target.

This prevents the current shell directory from silently winning over a named site such as LLMWikis.org, UAIX.org, AIWikis.org, or another related workspace root.

How Humans Review And Approve Memory

Humans should be able to review the same files the AI will load. Before sharing a bundle or using it to steer an autonomous agent, check ownership, dates, stale claims, sensitive data, trust boundaries, and whether planned work is clearly separated from current support. Ask the AI to name exactly which memory files changed and why.

UAIX AI Memory And LLM Wiki

LLM Wiki is not required by UAI specs or standards. UAIX supports it as a deep-memory strategy required for LLM Wiki configuration because teams that already use one need different package-shaping choices, source boundaries, and promotion rules.

UAIX AI Memory and LLM Wiki solve different memory problems. UAIX AI Memory is a portable working packet for continuity, handoffs, onboarding, external collaboration, audits, quick exports, and agent-ready context. LLMWikis.org represents the stronger pattern for deep, long-lived internal documentation and durable organizational knowledge.

Mature organizations may use both: LLM Wiki as the durable internal knowledge base, and UAIX AI Memory bundles as portable snapshots, working context, onboarding exports, handoff packets, audit packets, or agent-run context.

When To Use UAIX AI Memory

Use Project AI Memory when a project is active and context needs to persist across sessions.
Use Project Handoff when ownership, execution, or responsibility is moving.
Use Agent Session Memory when an AI agent needs resumable task context.
Use Onboarding Memory when a human or agent needs a curated starting point.
Use Decision Memory when rationale and tradeoffs matter more than status.

When To Use LLM Wiki

Use LLM Wiki when the organization needs deep, durable, searchable institutional knowledge.
Use it for long source summaries, research trails, comparisons, policy background, and internal education.
Keep it informative rather than governing until accepted facts are promoted into AI Memory, docs, code, tests, release notes, roadmap state, or public evidence.

When To Use Both

Use both when a durable knowledge base needs portable working packets. The LLM Wiki remains expansive; the AI Memory bundle remains decisive. If the decisive bundle starts growing like a wiki, archive the old detail and keep only the accepted current state. For the practical operating path, read Using UAI Packages With An LLM Wiki and Project Handoff Context Budget. For the longer rationale, read LLM Wiki vs. UAIX Project Handoff and LLM Wiki and UAIX Project Handoff.

How Samples, Manifests, And ZIPs Stay Synchronized

Rendered sample files, bundle manifests, download links, and generated ZIPs all resolve through the same canonical registry. There are no stale static starter ZIP assets and no ZIP-only sample files. If a shared file belongs to multiple bundles, it is selected by the same template ID. If a bundle needs variation, the variation is an explicit parameter, selected section, or overlay recorded in the manifest.

Public Route And Alias

The canonical UAIX page for this topic is /en-us/ai-memory/. The requested /AI_Memory entry path redirects here as the search-friendly entry alias while canonical UAIX public routes remain clean, locale-prefixed paths.

Agent Communication Operating Model

Agent runtimes execute. UAIX records the reviewed communication, memory, trust, evidence, and handoff boundary.

Use Agent Communication Operating Model when a human operator, coding agent, AI agent, or runtime implementer needs portable identity, intent, context, acknowledgement, status, blocker, memory proposal, validation evidence, correction, final report, or handoff records. The matching machine-readable assets are published through Schemas, Registry, Examples, and the Validator.

UAIX does not provide automatic sync, hosted messaging, runtime orchestration, official adapters, repository write execution, certification authority, or hosted import mechanisms.
Carcinus.org is a separate runtime/orchestrator example that may consume UAIX records. UAIX.org does not implement Carcinus runtime behavior and does not execute Carcinus workflows.
LocalEndPoint and other runtimes may consume the published UAIX records as external consumers; UAIX.org does not implement their project-specific runtime features.
Durable memory proposals stay separate from task execution records. Do not promote temporary endpoint statuses, session tokens, write tokens, beta platform instructions, local error traces, private keys, or API credentials.

Build compact project memory without turning history into truth

One source for samples and ZIP

Project Handoff makes memory operational

Identity, world-context, Totem, and Taboo files are required

Every package file has a declared required scope

LLM Wiki stays expansive

Archive before slimming

Validator-backed proof path

What AI Memory Means In UAIX#

Canonical AI Memory#

Fastest Practical Path#

Why Unstructured AI Memory Fails#

Why File-Based Memory Works#

AI Memory Taxonomy#

Choose the right AI Memory configuration#

Views and presets over supported bundles#

Deferred configurations#

Which Configuration To Choose#

Project AI Memory And Project Handoff#

Inspect The Project AI Memory Starter#

Project AI Memory#

What Belongs In AI Memory#

What Should Not Be Included#

Privacy And Trust Boundaries#

Maintenance Model#

How Agents Consume AI Memory#

Site, Solution, Or Workspace Placement#

How Humans Review And Approve Memory#

UAIX AI Memory And LLM Wiki#

When To Use UAIX AI Memory#

When To Use LLM Wiki#

When To Use Both#

How Samples, Manifests, And ZIPs Stay Synchronized#

Public Route And Alias#

Related UAIX Records#

Agent Communication Operating Model#

What AI Memory Means In UAIX

Canonical AI Memory

Fastest Practical Path

Why Unstructured AI Memory Fails

Why File-Based Memory Works

AI Memory Taxonomy

Choose the right AI Memory configuration

Views and presets over supported bundles

Deferred configurations

Which Configuration To Choose

Project AI Memory And Project Handoff

Inspect The Project AI Memory Starter

Project AI Memory

What Belongs In AI Memory

What Should Not Be Included

Privacy And Trust Boundaries

Maintenance Model

How Agents Consume AI Memory

Site, Solution, Or Workspace Placement

How Humans Review And Approve Memory

UAIX AI Memory And LLM Wiki

When To Use UAIX AI Memory

When To Use LLM Wiki

When To Use Both

How Samples, Manifests, And ZIPs Stay Synchronized

Public Route And Alias

Related UAIX Records

Agent Communication Operating Model