# aionforge-memory - Doramagic AI Context Pack

> Positioning: a pre-install experience and judgment asset. It helps the host AI get off to a good start, but it does not mean the project has already been installed, run, or validated.

## Sufficiency Principle

- **Sufficiency over compression**: The AI Context Pack should be sufficient for the host AI to understand the project's value, capability boundaries, entrypoints, risks, and evidence sources before starting work; it may be layered, but it does not aim for the shortest possible summary.
- **Compression policy**: Compress only noise and duplication, never context that affects judgment or the quality of the work.

## How the Host AI Should Use This

You are reading the AI Context Pack that Doramagic compiled for aionforge-memory. Treat it as pre-work context: help the user understand who it fits, what it can do, how to start, what must be verified after install, and where the risks are. Do not claim that you have already installed, run, or executed the target project.

## Claim Consumption Rules

- **Fact source**: Repo Evidence + Claim/Evidence Graph; the Human Wiki only supplies salience, terminology, and narrative structure.
- **Minimum status for a fact**: `supported`
- `supported`: May be used as a project fact, but the answer must cite the claim_id and evidence path.
- `weak`: Usable only as a low-confidence lead; the user must be asked to keep verifying.
- `inferred`: Usable only for risk notes or open questions; must not be packaged as a project fact.
- `unverified`: Must not be used as fact; state clearly that evidence is insufficient.
- `contradicted`: Must show the conflicting sources and must not force a single version on the user's behalf.

## Who It Fits Best

- **Developers already using host AIs such as Claude/Codex/Cursor/Gemini**: The README or plugin config mentions multiple host AIs. Evidence: `README.md` Claim: `clm_0003` supported 0.86
- **Users who want to bring professional workflows into a host AI**: The repo contains Skill documents. Evidence: `plugins/aionforge-memory/skills/memory-bootstrap/SKILL.md`, `plugins/aionforge-memory/skills/memory-capture/SKILL.md`, `plugins/aionforge-memory/skills/memory-loop/SKILL.md`, `plugins/aionforge-memory/skills/memory-maintenance/SKILL.md` et al. Claim: `clm_0004` supported 0.86

## What It Can Do

- **AI Skill / Agent Instruction Asset Library** (Previewable before install): The project contains Skill or Agent instruction files that a host AI can read, useful for bringing professional workflows into hosts like Claude, Codex, or Cursor. Evidence: `plugins/aionforge-memory/skills/memory-bootstrap/SKILL.md`, `plugins/aionforge-memory/skills/memory-capture/SKILL.md`, `plugins/aionforge-memory/skills/memory-loop/SKILL.md`, `plugins/aionforge-memory/skills/memory-maintenance/SKILL.md` et al. Claim: `clm_0001` supported 0.86
- **Multi-Host Install and Distribution** (Verify after install): The project contains plugin or marketplace configuration, indicating it targets install and distribution across one or more AI hosts. Evidence: `.agents/plugins/marketplace.json`, `.claude-plugin/marketplace.json`, `.cursor-plugin/marketplace.json`, `plugins/aionforge-memory/.claude-plugin/plugin.json` et al. Claim: `clm_0002` supported 0.86

## How to Start

- No stable Quick Start command in the project evidence; this should be left empty rather than fabricated by Doramagic.

## Continue-or-Stop Decision Card

- **Current recommendation**: Sandbox trial only
- **Why**: The project has signals of install commands, host configuration, or local writes; do not go straight into your primary environment—trial it in isolation first.

### 30-Second Read

- **What to do now**: Sandbox trial only
- **Minimum safe next step**: Run Prompt Preview first; if you still want to install, trial only in an isolated environment
- **Do not trust yet**: Real output quality cannot be trusted before install.
- **Continuing will touch**: Host AI configuration, Local environment or project files, Host AI context

### What You Can Trust Now

- **Target-audience signal: Developers already using host AIs such as Claude/Codex/Cursor/Gemini** (supported): Backed by a supported claim or project evidence, but that still is not the same as real install results. Evidence: `README.md` Claim: `clm_0003` supported 0.86
- **Target-audience signal: Users who want to bring professional workflows into a host AI** (supported): Backed by a supported claim or project evidence, but that still is not the same as real install results. Evidence: `plugins/aionforge-memory/skills/memory-bootstrap/SKILL.md`, `plugins/aionforge-memory/skills/memory-capture/SKILL.md`, `plugins/aionforge-memory/skills/memory-loop/SKILL.md`, `plugins/aionforge-memory/skills/memory-maintenance/SKILL.md` et al. Claim: `clm_0004` supported 0.86
- **Capability exists: AI Skill / Agent Instruction Asset Library** (supported): You can trust that the project contains signals of this capability; whether it fits your specific task still needs trial or after-install verification. Evidence: `plugins/aionforge-memory/skills/memory-bootstrap/SKILL.md`, `plugins/aionforge-memory/skills/memory-capture/SKILL.md`, `plugins/aionforge-memory/skills/memory-loop/SKILL.md`, `plugins/aionforge-memory/skills/memory-maintenance/SKILL.md` et al. Claim: `clm_0001` supported 0.86
- **Capability exists: Multi-Host Install and Distribution** (supported): You can trust that the project contains signals of this capability; whether it fits your specific task still needs trial or after-install verification. Evidence: `.agents/plugins/marketplace.json`, `.claude-plugin/marketplace.json`, `.cursor-plugin/marketplace.json`, `plugins/aionforge-memory/.claude-plugin/plugin.json` et al. Claim: `clm_0002` supported 0.86

### What You Cannot Trust Yet

- **Real output quality cannot be trusted before install.** (unverified): Prompt Preview can only show how it guides you; it cannot prove result quality in the real project.
- **Host AI version compatibility cannot be trusted before install.** (unverified): Host loading rules and version differences across Claude, Cursor, Codex, Gemini, and others must be verified in a real environment.
- **That it will not pollute your existing host AI's behavior cannot be trusted directly.** (inferred): Skill, plugin, and AGENTS/CLAUDE/GEMINI instructions may change the host AI's default behavior. Evidence: `.agents/plugins/marketplace.json`, `.claude-plugin/marketplace.json`, `.cursor-plugin/marketplace.json`, `AGENTS.md` et al.
- **Safe rollback cannot be assumed by default.** (unverified): Unless the project clearly provides uninstall and recovery instructions, verify in an isolated environment first.
- **After a real install, is it compatible with the user's current host AI version?** (unverified): Compatibility can only be verified in the actual host environment. Evidence: `.agents/plugins/marketplace.json`, `.claude-plugin/marketplace.json`, `.cursor-plugin/marketplace.json`, `plugins/aionforge-memory/.claude-plugin/plugin.json` et al.
- **Does the project's output quality meet the user's specific task?** (unverified): The pre-install preview can only show flow and boundaries; it cannot replace real evaluation.

### What Continuing Will Touch

- **Host AI configuration**: The plugin, Skill, or rule-loading config of hosts like Claude/Codex/Cursor/Gemini/OpenCode. Why: Host configuration changes how the AI works afterward and may conflict with the user's existing rules. Evidence: `.agents/plugins/marketplace.json`, `.claude-plugin/marketplace.json`, `.cursor-plugin/marketplace.json`, `AGENTS.md` et al.
- **Local environment or project files**: Install results, plugin caches, project config, or local dependency directories. Why: The write scope and rollback path cannot be proven before install and need isolated verification. Evidence: `.agents/plugins/marketplace.json`, `.claude-plugin/marketplace.json`, `.cursor-plugin/marketplace.json`, `plugins/aionforge-memory/.claude-plugin/plugin.json` et al.
- **Host AI context**: The AI Context Pack, Prompt Preview, Skill routing, risk rules, and project facts. Why: Importing context affects the host AI's later judgment, so avoid packaging unverified items as facts.

### Minimum Safe Next Steps

- **Run Prompt Preview first**: Use a pre-install interactive trial to judge whether the way of working fits; it needs no authorization or environment change. (applies when: Applies to any project, especially when output quality is unknown.)
- **Trial-install only in an isolated directory or a test account**: Avoid letting install commands pollute your primary host AI, real projects, or home directory. (applies when: When there are signals of command execution, plugin config, or local writes.)
- **Back up your host AI configuration first**: Skill, plugin, and rule files may change the default behavior of Claude/Cursor/Codex. (applies when: When there is a plugin manifest, a Skill, or a host rule entrypoint.)
- **After install, verify just one minimal task**: Verify loading, compatibility, output quality, and rollback first, then decide whether to use it deeply. (applies when: When moving from a trial into a real workflow.)

### Exit Plan

- **Preserve the pre-install state**: Record the original host config and project state so you can later judge whether it is recoverable.
- **Be ready to remove the host plugin / Skill / rule entrypoint**: If behavior is off after the trial install, you can restore the host AI to its pre-trial state.
- **Record the install commands and written paths**: Without clear uninstall instructions, you at least need to know which directories or configs to clean up manually.
- **If there is no rollback path, do not enter your primary environment**: No rollback is a blocker before continuing; do not proceed on trust or luck.

## What Can Only Be Previewed

- Explain who the project fits and what it can do
- Demonstrate a typical conversation flow based on project docs
- Help the user decide whether it is worth installing or researching further

## What Must Be Verified After Install

- Actually installing the Skill, plugin, or CLI
- Running scripts, modifying local files, or accessing external services
- Verifying real output quality, performance, and compatibility

## Boundary & Risk Decision Card

- **Mistaking the pre-install preview for a real run**: The user may overestimate how much configuration, permission, and compatibility verification the project has already done. Mitigation: Clearly separate prompt_preview_can_do from runtime_required. Claim: `clm_0005` inferred 0.45
- **Host AI plugin or Skill rule conflicts**: New rules may change how the user's existing host AI behaves. Mitigation: Inspect the plugin manifest and Skill files before installing, and test in isolation if needed. Evidence: `.agents/plugins/marketplace.json`, `.claude-plugin/marketplace.json`, `.cursor-plugin/marketplace.json`, `plugins/aionforge-memory/.claude-plugin/plugin.json` et al. Claim: `clm_0006` supported 0.86
- **To confirm**: After a real install, is it compatible with the user's current host AI version?. Why: Compatibility can only be verified in the actual host environment.
- **To confirm**: Does the project's output quality meet the user's specific task?. Why: The pre-install preview can only show flow and boundaries; it cannot replace real evaluation.

## Pre-Work Working Context

### Loading Order

- First read how_to_use.host_ai_instruction to establish the boundaries of this pre-install judgment asset.
- Read claim_graph_summary to confirm facts come from the Claim/Evidence Graph, not the Human Wiki narrative.
- Then read intended_users, capabilities, and quick_start_candidates to judge whether the user is a match.
- When you need to carry out a concrete task, check role_skill_index first, then evidence_index.
- For real install, file modification, network access, performance, or compatibility questions, turn to risk_card and boundaries.runtime_required.

### Task Routes

- **AI Skill / Agent Instruction Asset Library**: Use role_skill_index / evidence_index to help the user pick a usable role, Skill, or workflow first. Boundary: Can be experienced via a pre-install Prompt. Evidence: `plugins/aionforge-memory/skills/memory-bootstrap/SKILL.md`, `plugins/aionforge-memory/skills/memory-capture/SKILL.md`, `plugins/aionforge-memory/skills/memory-loop/SKILL.md`, `plugins/aionforge-memory/skills/memory-maintenance/SKILL.md` et al. Claim: `clm_0001` supported 0.86
- **Multi-Host Install and Distribution**: State that this is an after-install capability first, then give a pre-install checklist. Boundary: Must be verified after a real install or run. Evidence: `.agents/plugins/marketplace.json`, `.claude-plugin/marketplace.json`, `.cursor-plugin/marketplace.json`, `plugins/aionforge-memory/.claude-plugin/plugin.json` et al. Claim: `clm_0002` supported 0.86

### Context Scale

- Total files: 522
- Important-file coverage: 40/522
- Evidence index entries: 79
- Role / Skill entries: 6

### Handling Insufficient Evidence

- **missing_evidence**: State that evidence is insufficient and ask the user for the target file, a README section, or after-install verification records; do not fill in facts.
- **out_of_scope_request**: State that the task is beyond the current AI Context Pack's evidence scope and suggest the user check the Human Manual or verify after a real install.
- **runtime_request**: Provide a pre-install checklist and command sources, but do not run commands for the user or claim they have been run.
- **source_conflict**: Show the conflicting sources side by side, mark them as unverified, and do not force a single version.

## Prompt Recipes

### Fit assessment

- Goal: Judge whether this project fits the user's current task.
- Expected output: A fit conclusion, key reasons, evidence citations, what can be previewed before install, what must be verified after install, and a next-step recommendation.

```text
Based on the AI Context Pack for aionforge-memory, ask me 3 necessary questions first, then judge whether it fits my task. The answer must cover: who it fits, what it can do, what it cannot do, whether it is worth installing, and where the evidence comes from. Every project fact must cite evidence_refs, source_paths, or a claim_id.
```

### Pre-install experience

- Goal: Let the user feel the core workflow before installing, while avoiding packaging the preview as real capability or a marketing promise.
- Expected output: An experience script with boundary labels, an after-install verification checklist, and a cautious recommendation; with no real-run promises or strong marketing language.

```text
Treat aionforge-memory as a pre-install experience asset, not an already-installed tool or a real runtime environment.

Output exactly four parts:
1. Ask me 3 necessary questions first.
2. Give an "experience script": use the three labels [Previewable before install], [Must verify after install], and [Insufficient evidence] to show how it might guide the workflow.
3. Give an after-install verification checklist: list which capabilities can only be confirmed after a real install, real host loading, and a real project run.
4. Give a cautious recommendation: only "worth researching/trialing further", "add information before deciding", or "not recommended to continue"; do not endorse the project.

Hard boundaries:
- Do not claim you have installed, run, executed tests, modified files, or produced real results.
- Do not write promise-like phrasing such as "auto-adapts", "guarantees passing", "perfect fit", or "strongly recommend installing".
- If you describe how it works after install, you must use a conditional such as "if installed successfully and the host loads the Skill correctly, it might...".
- The experience script may only be written as "example lines / hypothetical flow": use "might ask / might suggest / might show", not "has written, has generated, has passed, is running, is generating".
- Prompt Preview does not hand out install commands; if the user is ready to trial, only prompt them to read Quick Start and the Risk Card first and to verify in an isolated environment.
- Every project fact must come from a supported claim, evidence_refs, or source_paths; inferred/unverified items can only be risks or open questions.

```

### Role / Skill selection

- Goal: Pick the best-matching asset from the project's roles or Skills.
- Expected output: A list of candidate roles or Skills, each with an applicable scenario, evidence paths, risk boundary, and whether after-install verification is needed.

```text
Read role_skill_index and recommend 3-5 of the most relevant roles or Skills for my target task. For each recommendation, state the applicable scenario, likely output, risk boundary, and evidence_refs.
```

### Risk pre-check

- Goal: Identify environment, permission, rule-conflict, and quality risks before installing or adopting.
- Expected output: A checklist of environment, permission, dependency, license, host-conflict, quality risk, and unknown items.

```text
Based on risk_card, boundaries, and quick_start_candidates, give me a pre-install risk pre-check list. Do not run commands for me; only explain what I should check, why, and what impact a failure would have.
```

### Host AI kickoff instruction

- Goal: Turn the project context into a host AI instruction for the start of a conversation.
- Expected output: A pre-work instruction with clear boundaries and clear evidence citations, suitable to copy to a host AI.

```text
Based on the AI Context Pack for aionforge-memory, generate a pre-work instruction I can paste to my host AI. This instruction must obey not_runtime=true and must not claim the project has been installed, run, or produced real results.
```

## Role / Skill Index

- Indexed 6 role / Skill / project-doc entries.

- **memory-bootstrap** (skill): One-time setup that lays a foundational Aionforge Memory substrate for a fresh project — resolve identity, seed conventions and architecture decisions as captures, stand up a work-item backlog skeleton, and verify recall. Use when a project's memory is empty or new, or when the user asks to set up, bootstrap, initialize, or seed project memory. Activation hint: When the user's task is highly relevant to the workflow described by “memory-bootstrap”, use it for a pre-install experience first, then decide whether to install. Evidence: `plugins/aionforge-memory/skills/memory-bootstrap/SKILL.md`
- **memory-capture** (skill): Capture durable Aionforge Memory records for decisions, user preferences, project facts, release outcomes, validation results, handoffs, corrections, and reusable failure patterns. Use proactively during substantial work and whenever the user asks to remember or update memory. Activation hint: When the user's task is highly relevant to the workflow described by “memory-capture”, use it for a pre-install experience first, then decide whether to install. Evidence: `plugins/aionforge-memory/skills/memory-capture/SKILL.md`
- **memory-loop** (skill): Use Aionforge Memory as the working substrate for a multi-step task. Trigger for implementation, debugging, review, release, planning, incidents, handoffs, or any session where prior context and durable follow-up matter. Activation hint: When the user's task is highly relevant to the workflow described by “memory-loop”, use it for a pre-install experience first, then decide whether to install. Evidence: `plugins/aionforge-memory/skills/memory-loop/SKILL.md`
- **memory-maintenance** (skill): Inspect, consolidate, audit, forget, or restore Aionforge Memory. Use when the user asks about memory health, backlog, provenance, stale records, corrections, deletion, restoration, or why a memory was recalled. Activation hint: When the user's task is highly relevant to the workflow described by “memory-maintenance”, use it for a pre-install experience first, then decide whether to install. Evidence: `plugins/aionforge-memory/skills/memory-maintenance/SKILL.md`
- **memory-recall** (skill): Search Aionforge Memory before planning, answering, coding, review, debugging, release, or continuation work. Use proactively whenever prior decisions, user preferences, project facts, failures, or handoffs could change the answer. Activation hint: When the user's task is highly relevant to the workflow described by “memory-recall”, use it for a pre-install experience first, then decide whether to install. Evidence: `plugins/aionforge-memory/skills/memory-recall/SKILL.md`
- **work-tracking** (skill): Track tasks, blockers, TODOs, plans, and follow-ups as durable Aionforge Memory work items. Use proactively when a multi-step task, backlog, plan, or handoff appears, and whenever the user mentions tasks, status, or what is left to do. Work items are persistent and status-tracked, distinct from decaying memory episodes. Activation hint: When the user's task is highly relevant to the workflow described by “work-tracking”, use it for a pre-install experience first, then decide whether to install. Evidence: `plugins/aionforge-memory/skills/work-tracking/SKILL.md`

## Evidence Index

- Indexed 79 evidence entries.

- **Documentation** (documentation): System documentation for Aionforge Memory — how the pieces work and how to use them. This is reference and guides, not planning or changelogs. Evidence: `docs/README.md`
- **Agent Guide for Aionforge Memory** (documentation): Aionforge Memory is a Rust long-term memory layer for AI agents. It stores episodes, facts, notes, skills, bad patterns, core memory, and audit events in selene-db , then retrieves relevant context with lexical anchors, vector search, graph traversal, recency, importance, and trust signals. Evidence: `AGENTS.md`
- **Quick Start** (documentation): Long-term memory for AI agents, built on selene-db. Evidence: `README.md`
- **Third-party data licenses** (documentation): Full license texts and attribution for the third-party datasets vendored as test fixtures in this repository. The data itself and its curation/provenance record live next to the test that uses it: crates/aionforge-security/tests/corpus/ see that directory's PROVENANCE.md . Evidence: `third-party-data/README.md`
- **aionforge-eval tools** (documentation): On-demand tooling for the retrieval-quality eval harness. These are dev tools, not part of any shipped artifact and not run in CI. Evidence: `crates/aionforge-eval/tools/README.md`
- **Aionforge Memory Plugin** (documentation): This plugin packages six small Agent Skills for an existing Aionforge Memory MCP server: Evidence: `plugins/aionforge-memory/README.md`
- **The bi-temporal model** (documentation): Every fact in Aionforge Memory carries two independent clocks. One records when the thing was true in the world; the other records when the substrate came to believe it. Keeping the two apart is what lets a recall answer "what is true now," "what was true last March," and "what did we think we knew on the day we acted" without any of those questions stepping on the others. Evidence: `docs/bi-temporal-model.md`
- **Aionforge Memory data model** (documentation): Public reference for how Aionforge Memory stores, derives, recalls, and removes memory. Evidence: `docs/data-model.md`
- **Getting started** (documentation): This guide is the shortest path from a fresh checkout to a local Aionforge Memory process that a Rust host or MCP client can use. For subsystem details, follow the links in the docs index README.md . Evidence: `docs/getting-started.md`
- **Honest scope and deferred work** (documentation): Aionforge Memory is an exemplar-based memory substrate. It stores episodes, facts, notes, skills, bad patterns, identity blocks, and audit events; retrieves them with native lexical, vector, graph, temporal, trust, and recency signals; and renders recall as untrusted data for a host model. It is not a training system, not a fine-tuning loop, and not an autonomous model router. Evidence: `docs/honest-scope.md`
- **Identifiers** (documentation): Every node Aionforge stores — an episode, a fact, a note, a skill, an audit event — carries a stable id . An id is a UUID , stored as selene-db's native 16-byte UUID value not a string , so it indexes and compares as a UUID at the storage layer. Evidence: `docs/identifiers.md`
- **Contributing to Aionforge Memory** (documentation): Thanks for helping build a long-term memory layer for AI agents. This guide is the human onramp; AGENTS.md AGENTS.md is the authoritative reference for the crate layering, core invariants, and exact gate commands. When the two could drift, AGENTS.md wins — this file links to it rather than restating it. Evidence: `CONTRIBUTING.md`
- **Memory Bootstrap** (skill_instruction): Requires an enabled Aionforge Memory MCP server. Evidence: `plugins/aionforge-memory/skills/memory-bootstrap/SKILL.md`
- **Memory Capture** (skill_instruction): Requires an enabled Aionforge Memory MCP server. Evidence: `plugins/aionforge-memory/skills/memory-capture/SKILL.md`
- **Memory Loop** (skill_instruction): Requires an enabled Aionforge Memory MCP server. Evidence: `plugins/aionforge-memory/skills/memory-loop/SKILL.md`
- **Memory Maintenance** (skill_instruction): Requires an enabled Aionforge Memory MCP server. Evidence: `plugins/aionforge-memory/skills/memory-maintenance/SKILL.md`
- **Memory Recall** (skill_instruction): Requires an enabled Aionforge Memory MCP server. Evidence: `plugins/aionforge-memory/skills/memory-recall/SKILL.md`
- **Work Tracking** (skill_instruction): Requires an enabled Aionforge Memory MCP server. Evidence: `plugins/aionforge-memory/skills/work-tracking/SKILL.md`
- **Marketplace** (structured_config): { "name": "aionforge-plugins", "owner": { "name": "Aionforge Labs", "url": "https://github.com/jscott3201" }, "metadata": { "description": "Aionforge agent plugins." }, "plugins": { "name": "aionforge-memory", "source": "./plugins/aionforge-memory", "description": "Agent skills for using an externally configured Aionforge Memory MCP server as durable project memory.", "version": "0.3.0", "author": { "name": "Aionforge Labs" }, "homepage": "https://github.com/jscott3201/aionforge-memory/tree/development/plugins/aionforge-memory", "repository": "https://github.com/jscott3201/aionforge-memory", "license": "MIT OR Apache-2.0", "keywords": "memory", "mcp", "agent-skills", "retrieval" , "category… Evidence: `.claude-plugin/marketplace.json`
- **Marketplace** (structured_config): { "name": "aionforge-plugins", "owner": { "name": "Aionforge Labs" }, "metadata": { "description": "Aionforge agent plugins." }, "plugins": { "name": "aionforge-memory", "source": "plugins/aionforge-memory", "description": "Agent skills for using an externally configured Aionforge Memory MCP server as durable project memory.", "version": "0.3.0", "author": { "name": "Aionforge Labs" }, "homepage": "https://github.com/jscott3201/aionforge-memory/tree/development/plugins/aionforge-memory", "repository": "https://github.com/jscott3201/aionforge-memory", "license": "MIT OR Apache-2.0", "keywords": "memory", "mcp", "agent-skills", "retrieval" , "category": "Productivity", "skills": "skills/" } } Evidence: `.cursor-plugin/marketplace.json`
- **Marketplace** (structured_config): { "name": "aionforge-plugins", "interface": { "displayName": "Aionforge Plugins" }, "plugins": { "name": "aionforge-memory", "source": { "source": "local", "path": "./plugins/aionforge-memory" }, "policy": { "installation": "AVAILABLE", "authentication": "ON INSTALL" }, "category": "Productivity" } } Evidence: `.agents/plugins/marketplace.json`
- **Plugin** (structured_config): { "name": "aionforge-memory", "displayName": "Aionforge Memory", "version": "0.3.0", "description": "Agent skills for using an externally configured Aionforge Memory MCP server as durable project memory.", "author": { "name": "Aionforge Labs", "url": "https://github.com/jscott3201" }, "homepage": "https://github.com/jscott3201/aionforge-memory/tree/development/plugins/aionforge-memory", "repository": "https://github.com/jscott3201/aionforge-memory", "license": "MIT OR Apache-2.0", "keywords": "memory", "mcp", "agent-skills", "retrieval" , "skills": "./skills/" } Evidence: `plugins/aionforge-memory/.claude-plugin/plugin.json`
- **Plugin** (structured_config): { "name": "aionforge-memory", "version": "0.3.0+codex.20260618154505", "description": "Agent skills for using an externally configured Aionforge Memory MCP server as durable project memory.", "author": { "name": "Aionforge Labs", "url": "https://github.com/jscott3201" }, "homepage": "https://github.com/jscott3201/aionforge-memory/tree/development/plugins/aionforge-memory", "repository": "https://github.com/jscott3201/aionforge-memory", "license": "MIT OR Apache-2.0", "keywords": "memory", "mcp", "agent-skills", "retrieval" , "skills": "./skills/", "interface": { "displayName": "Aionforge Memory", "shortDescription": "Durable memory workflows for agent sessions", "longDescription": "Use Aion… Evidence: `plugins/aionforge-memory/.codex-plugin/plugin.json`
- **Plugin** (structured_config): { "name": "aionforge-memory", "version": "0.3.0", "description": "Agent skills for using an externally configured Aionforge Memory MCP server as durable project memory.", "author": { "name": "Aionforge Labs" }, "homepage": "https://github.com/jscott3201/aionforge-memory/tree/development/plugins/aionforge-memory", "repository": "https://github.com/jscott3201/aionforge-memory", "license": "MIT OR Apache-2.0", "keywords": "memory", "mcp", "agent-skills", "retrieval" , "skills": "./skills/", "rules": "./rules/" } Evidence: `plugins/aionforge-memory/.cursor-plugin/plugin.json`
- **Plugin** (structured_config): { "name": "aionforge-memory", "description": "Agent skills for using an externally configured Aionforge Memory MCP server as durable project memory.", "version": "0.3.0", "author": { "name": "Aionforge Labs", "url": "https://github.com/jscott3201" }, "homepage": "https://github.com/jscott3201/aionforge-memory/tree/development/plugins/aionforge-memory", "repository": "https://github.com/jscott3201/aionforge-memory", "license": "MIT OR Apache-2.0", "keywords": "memory", "mcp", "agent-skills", "retrieval" , "skills": "skills/" } Evidence: `plugins/aionforge-memory/plugin.json`
- **Agent nudges across editors** (documentation): The Aionforge Memory plugin keeps memory in the task loop — recall before substantial work, capture durable facts as they land, and track tasks as work items. How that nudge is delivered depends on the editor: Evidence: `docs/agent-nudges.md`
- **Apple container** (documentation): Apple's container runtime can run the OCI image published for Aionforge Memory. It is a local macOS path for Apple silicon machines; release publishing still uses GHCR and the existing Docker/buildx workflow. Evidence: `docs/apple-container.md`
- **Attestation and quorum promotion** (documentation): A memory written in one team's namespace stays there until other agents vouch for it. Quorum promotion is the one path a team fact takes to the shared global namespace, and it is gated: a fact promotes only after enough independent agents sign an attestation for it and the substrate's confidence in it clears a threshold. Demotion is the reverse, and it never destroys the original. Evidence: `docs/attestation-and-promotion.md`
- **The audit subgraph** (documentation): Every governance operation the substrate performs — promotions, demotions, attestations, reliability updates, consolidation decisions, refused writes — leaves an AuditEvent row. Together those rows are the audit subgraph: the forensic record of what the system did and why, queryable by subject, by kind, and in time order. Evidence: `docs/audit-subgraph.md`
- **Capture** (documentation): Capture is the write path. When an agent produces a turn — a user message, an assistant reply, a tool result — capture is what turns that raw text into a stored episode. It runs on the hot path, in millisecond time, and it is deliberately thin: it filters the content, decides whether the turn is worth keeping, attaches just enough provenance to prove who wrote it, and commits. Everything that takes real thought — clustering, summarizing, recomputing importance, drawing links — is left to consolidation consolidation.md , which runs behind the path and never blocks it. Evidence: `docs/capture.md`
- **Concurrent merge** (documentation): When several agents write to the same shared memory, their writes have to come together into one consistent state. Aionforge does this without a separate replication engine: every write lands in one serialized graph, and the consolidation pass decides how concurrent assertions about the same thing resolve. The rule that governs that resolution is built so the outcome does not depend on the order the writes happened to be processed in. Evidence: `docs/concurrent-merge.md`
- **Consolidation** (documentation): Consolidation is the slow, asynchronous side of memory. Capture writes a raw episode and returns; some time later, a background worker reads that episode and derives the durable knowledge from it — the facts, the entities, the contradictions, the summaries. The two halves are deliberately split. Capture stays on a fast, narrow path; the expensive thinking happens off to the side, on its own schedule, where it can take its time and recover from a crash without ever holding up a write. Evidence: `docs/consolidation.md`
- **Core memory** (documentation): Core blocks are the identity tier: the agent's stable self-description persona , its standing promises commitment , and its inviolable constraints redline . They are the most strongly protected memories in the substrate, because they are the ones an attacker — or a slowly drifting agent — would most like to rewrite. Evidence: `docs/core-memory.md`
- **The merge model CRDTs** (documentation): When several agents write to one shared memory, the writes have to settle into a single consistent state, and they have to settle the same way no matter what order they were processed in. The literature for that problem is conflict-free replicated data types CRDTs : data types whose merge is commutative, associative, and idempotent, so replicas that have seen the same set of updates agree regardless of delivery order. Evidence: `docs/crdt-model.md`
- **Cross-family consolidation guard** (documentation): How the substrate keeps a consolidating model from condensing its own family's writing 07 §3, M6.T01 . Behavioral traits transmit through model-mediated condensation when the model doing the condensing shares a base model with the writers whose content it reads — mixing unrelated data reduces the effect but does not eliminate it, and a cross-family condenser suppresses it. So any consolidation rule that calls inference must verify before each model call that the consolidating family differs from the writers' families. The guard is substrate policy over the inference seam: today it protects the link-evolution path Memory::evolve links , which is generic over the LinkEvolver seam, and it rema… Evidence: `docs/cross-family-guard.md`
- **Decay and importance scoring** (documentation): How a memory's relevance ages 05 §2, M5.T01 . A memory is written with an importance score; that score is the anchor, not the living value. At read time the substrate computes an effective importance — the stored score sunk by elapsed time under a per-tier exponential half-life — and ranks with it. Relevance in recall is three-factor: what the query matches the lexical/dense/graph search signals , how important the memory is now the importance re-rank , and how recently it entered the record the recency re-rank . Evidence: `docs/decay-and-importance.md`
- **Drift detection** (documentation): How the substrate notices the agent moving away from who it said it is 05 §1, M5.T05 . Each core block — persona, commitment, redline — carries an attested baseline : a snapshot of the block's embedding and the namespace's behavior centroid, co-signed through the same second-attester edit gate that protects the block content. A periodic detector measures how much farther current behavior sits from each block's anchor than it did at baseline time, warns through the audit log when a block crosses the threshold, and never blocks a write. The companion control is the cooling window : a new fact landing close to a high-trust core block is admitted but rank-sunk for a bounded window, buying the d… Evidence: `docs/drift.md`
- **Embedding and provider guide** (documentation): Aionforge stores and retrieves embeddings, but it does not run an embedding model itself. A deployment points the host at one provider/model pair and records that model identity on stored vectors so the rest of the substrate can verify dimensions, provenance, and cross-family boundaries. Evidence: `docs/embedding-guide.md`
- **Erasure** (documentation): How the substrate destroys 05 §3, M5.T03 . Erasure is the one destructive path in the system: a hard purge that removes nodes, severs their edges, and clears every index entry, audited and irreversible. Everything else that retires a memory — forgetting, supersession, quarantine, demotion — keeps the record; erasure is what you reach for when the record itself must go. It is off by default behind its own switch, requires a principal, and refuses whole rather than ever purging part of a cascade. Evidence: `docs/erasure.md`
- **Active forgetting** (documentation): How the substrate lets go 05 §2, M5.T02 . Forgetting is a soft expiry : one node-level expired at , set with the status and every edge untouched, audited, and reversible until the retention prune physically removes the record. It is off by default, conservative by construction — every check can only spare a memory, never doom one on its own — and strictly a default-recall notion: a forgotten memory leaves every default read but stays in the record for history and audit. Evidence: `docs/forgetting.md`
- **Graph signals** (documentation): Two of Aionforge Memory's retrieval signals come from the graph rather than from a text or vector index alone. Both turn the associative structure between memories into recall: the entities a query names, the facts about them, and the evidence that supports those facts. They exist for one reason — to recover the memory a single-hop search misses without dragging down the precision a single-hop search is good at. Both run natively in selene-db, so the graph is walked where it lives instead of pulled into Rust and traversed there. Evidence: `docs/graph-signals.md`
- **Note link evolution** (documentation): Link evolution is the deterministic, off-cursor layer that draws and revises relationships between notes — RELATES TO edges like subsumes , contradicts , or elaborates . It runs against already-committed notes and is built so that running it cannot move the reproducible parts of the system. Evidence: `docs/link-evolution.md`
- **MCP client support** (documentation): Aionforge Memory exposes MCP Tools, Resources, and Prompts over stdio and over the MCP Streamable HTTP transport. The HTTP service is intended to be mounted at /mcp and bound to loopback by default. HTTP auth is default-off: keep that local unless built-in HTTP OAuth validation is enabled or an OAuth-aware verifier/equivalent perimeter protects the endpoint. Evidence: `docs/mcp-clients.md`
- **Namespace authorization** (documentation): Every memory lives in a namespace, and every write is checked against who is making it. A capturing agent can only write where it is allowed to, and an attempt to write somewhere it isn't is refused and recorded. This is the boundary that keeps one agent's private memory private and keeps shared spaces from being written behind the host's back. Evidence: `docs/namespace-authorization.md`
- **Observability** (documentation): Aionforge emits spans/events through the tracing https://docs.rs/tracing facade and metrics through the metrics facade. The aionforge binary installs a tracing subscriber see Logging logging below , so events reach stderr out of the box; the metrics facade stays a no-op until a host installs a recorder a deliberate follow-up . Metric labels and span fields are deliberately low-cardinality: no query text, memory content, namespace ids, agent ids, file paths, request ids, or model names are used. Use audit reads and aionforge doctor --json for high-detail inspection. Evidence: `docs/observability.md`
- **Operations and recovery** (documentation): This guide covers the operator-facing binary path: how a host loads config, starts the MCP server, and validates a durable store after a restart or incident. Evidence: `docs/operations-recovery.md`
- **Agent Plugin** (documentation): Aionforge Memory ships a plugin package at plugins/aionforge-memory ../plugins/aionforge-memory . It bundles six Agent Skills plus a Claude Code steward agent, commands, and a SessionStart nudge hook. Evidence: `docs/plugins.md`
- **Procedural memory** (documentation): Procedural memory is where an agent keeps the procedures that worked — skills — so it can reuse them instead of working a solved problem out from scratch every time. A skill is stored as data, never executed by the substrate; the agent that retrieves it decides whether and how to run it. Evidence: `docs/procedural-memory.md`
- **Provenance signing** (documentation): Every captured memory records who wrote it. Signed writes make that record provable: the writer signs each capture with its own key, and the substrate verifies the signature against the key it has on file before any memory is written. A write whose signature doesn't check out, or whose timestamp is too far off, is refused and recorded — it never becomes memory. Evidence: `docs/provenance-signing.md`
- **Red-team suite** (documentation): The red-team suite is the security acceptance gate for the memory substrate. It is ordinary Rust test code, so a failing probe fails CI, and each probe produces a structured report instead of a free-form log line. The report shape lives in aionforge-redteam and records the task, probe name, full denominator, observed attack successes, naive-baseline successes, the binding ceiling, rates, and the pass/fail status for attack-rate probes. Effect-size probes use the same crate and record treatment/baseline denominators, hit rates, rate-difference effect size, the pre-registered threshold, and which side of that threshold is passing. Audit-coverage probes record the full attempt denominator, the… Evidence: `docs/red-team.md`
- **Retrieval** (documentation): Retrieval is how a recall turns a query into a ranked set of memories. It runs BM25 lexical search, a factual lexical anchor, dense vector search, graph-aware search, and quality re-ranks over the same graph engine. The query routes to a profile that decides how hard each signal pulls, then the retriever fuses the ranked lists by rank and hands back a bundle that is the same every time the graph state is. Everything here goes through selene-db. There is no second search engine, no external vector store, and no index the substrate keeps on the side — the BM25 text indexes, the cosine vector indexes, and the maintained candidate-state sets all live in the one engine, and retrieval composes na… Evidence: `docs/retrieval.md`
- **Security model** (documentation): Aionforge Memory treats memory as untrusted, multi-tenant state. The core security posture is fail-closed writes, principal-scoped reads, signed provenance when enabled, and prompt-injection-safe recall rendering. Evidence: `docs/security-model.md`
- **Trust scoring** (documentation): The substrate keeps a running sense of how reliable each agent has been, and lets that sense shape what later recalls surface and what can be promoted. An agent that produces facts which hold up earns trust; one whose facts are contradicted, or whose attestations are later invalidated, loses it. That score is not a number someone sets by hand — it is folded from a record of what actually happened. Evidence: `docs/trust-model.md`
- **aionforge-memory workspace root.** (source_file): aionforge-memory workspace root. Multi-crate, no umbrella facade. The dependency direction is intentional and acyclic L1 domain - L0 store - L2 subsystems - L3 engine - L4 surfaces - bin . Only aionforge-store L0 may name selene-db types; every other crate works through the store's typed surface. See goalslogs/design/01-architecture.md. Evidence: `Cargo.toml`
- **Production-oriented Aionforge Memory config template.** (source_file): Production-oriented Aionforge Memory config template. Replace paths, model ids, endpoints, and environment variable names for your deployment. Do not put secret values in this file. Evidence: `examples/production.toml`
- **JWT validation with constant-time RS256/384/512 via ring already in-tree via rustls .** (source_file): package name = "aionforge-auth" version.workspace = true edition.workspace = true rust-version.workspace = true authors.workspace = true license.workspace = true repository.workspace = true homepage.workspace = true description = "OIDC discovery + RS256-pinned JWT validation with JWKS caching and kid rotation" Evidence: `crates/aionforge-auth/Cargo.toml`
- **Lib** (source_file): mod discovery; mod error; mod fetch; mod jwks; mod validate; mod validator; ⋮---- pub use error::AuthError; pub use validate::VerifiedClaims; pub use validator::JwtValidator; Evidence: `crates/aionforge-auth/src/lib.rs`
- **Cargo** (source_file): package name = "aionforge-capture" version.workspace = true edition.workspace = true rust-version.workspace = true authors.workspace = true license.workspace = true repository.workspace = true homepage.workspace = true description = "Fast ADD-oriented capture path: deduplication, provenance, single-funnel commit." Evidence: `crates/aionforge-capture/Cargo.toml`
- **Capturer** (source_file): use std::future::Future; use std::sync::Arc; ⋮---- use aionforge domain::embedding::Embedding; ⋮---- use aionforge domain::namespace::Namespace; ⋮---- use aionforge store::Store; use tracing::Instrument; ⋮---- use crate::config::CaptureConfig; use crate::error::CaptureError; ⋮---- use crate::request::CaptureRequest; ⋮---- pub struct Capturer { ⋮---- pub fn new ⋮---- pub fn with gate mut self, gate: Arc - Self { self.gate = Some gate ; ⋮---- async fn run &self, request: CaptureRequest - Result { let namespace = enforce namespace &request ; ⋮---- let result = self.run inner request .instrument span.clone .await; record capture span &span, &result ; ⋮---- async fn run inner &self, request: Cap… Evidence: `crates/aionforge-capture/src/capturer.rs`
- **Lib** (source_file): mod capturer; mod config; mod error; mod receipt; mod request; ⋮---- pub use aionforge domain::gate::ProvenanceGate; pub use capturer::Capturer; pub use config::CaptureConfig; pub use error::CaptureError; Evidence: `crates/aionforge-capture/src/lib.rs`
- The remaining 19 evidence entries are in `AI_CONTEXT_PACK.json` or `EVIDENCE_INDEX.json`.

## Rules the Host AI Must Follow

- **Treat this asset as pre-work context, not a runtime environment.**: The AI Context Pack contains only an evidence-backed understanding of the project, not the project's executable state. Evidence: `docs/README.md`, `AGENTS.md`, `README.md`
- **When answering the user, distinguish what can be previewed from what can only be verified after install.**: The consumer value of the pre-install experience comes from reducing bad installs and misjudgments, not from pretending to be a real run. Evidence: `docs/README.md`, `AGENTS.md`, `README.md`

## Questions the User Should Answer First

- Which host AI or local environment do you plan to use it in?
- Do you just want to experience the workflow first, or are you ready to actually install?
- What matters most to you: install cost, output quality, or conflicts with your existing rules?

## Acceptance Checks

- Every capability claim can be traced back to a file path in evidence_refs.
- AI_CONTEXT_PACK.md does not package previews as a real run.
- The user can understand who it fits, what it can do, how to start, and the risk boundaries within 3 minutes.

---

## Doramagic Context Augmentation

The following sections strengthen the repository context for a host AI. Human Manual data is a reading route, and pitfall notes become operating constraints.

## Human Manual Outline

Usage rule: this is only a reading route and salience signal, not factual authority. Concrete claims must still return to repo evidence or Claim Graph.

Host AI hard rules:
- Do not treat page titles, section order, summaries, or importance values as factual project evidence.
- When explaining the Human Manual outline, state that it is only a reading route or salience signal.
- Capability, installation, compatibility, runtime state, and risk claims must cite repo evidence, source paths, or Claim Graph.

- **Project Overview**: importance `high`
  - source_paths: README.md, docs/README.md, docs/honest-scope.md
- **Getting Started**: importance `high`
  - source_paths: README.md, docs/getting-started.md, examples/production.toml, Cargo.toml
- **Crate Workspace & Layering**: importance `medium`
  - source_paths: Cargo.toml, AGENTS.md, crates/aionforge/src/lib.rs, crates/aionforge-domain/src/lib.rs
- **Data Model & Capture Pipeline**: importance `high`
  - source_paths: docs/data-model.md, docs/bi-temporal-model.md, docs/identifiers.md, crates/aionforge-domain/src/blocks.rs, crates/aionforge-domain/src/recall_frame.rs

## Repo Inspection Evidence

- repo_clone_verified: true
- repo_inspection_verified: true
- repo_commit: `f33268cc287d20a1295143fade6b430d76f6a7db`
- inspected_files: `Dockerfile`, `README.md`, `docs/README.md`, `docs/agent-nudges.md`, `docs/apple-container.md`, `docs/attestation-and-promotion.md`, `docs/audit-subgraph.md`, `docs/bi-temporal-model.md`, `docs/capture.md`, `docs/concurrent-merge.md`, `docs/consolidation.md`, `docs/core-memory.md`, `docs/crdt-model.md`, `docs/cross-family-guard.md`, `docs/data-model.md`, `docs/decay-and-importance.md`, `docs/drift.md`, `docs/embedding-guide.md`, `docs/erasure.md`, `docs/forgetting.md`

Host AI hard rules:
- Without repo_clone_verified=true, do not claim that the source code has been read.
- Without repo_inspection_verified=true, do not write README, docs, or package-file conclusions as facts.
- Without quick_start_verified=true, do not claim that the Quick Start path has run successfully.

## Doramagic Pitfall Constraints

These rules come from Doramagic discovery, validation, or compilation findings. The host AI must treat them as operating constraints, not background notes.

### Constraint 1: Capability evidence risk requires verification

- Trigger: README/documentation is current enough for a first validation pass.
- Host AI rule: Reproduce the official install and quickstart path in an isolated environment.
- Why it matters: May increase setup, validation, or first-run risk for the user.
- Evidence: capability.assumptions | https://github.com/jscott3201/aionforge-memory
- Hard boundary: Do not present this pitfall as solved, verified, or ignorable unless later evidence explicitly closes it.

### Constraint 2: Security or permission risk requires verification

- Trigger: no_demo
- Host AI rule: Reproduce the official install and quickstart path in an isolated environment.
- Why it matters: May increase setup, validation, or first-run risk for the user.
- Evidence: downstream_validation.risk_items | https://github.com/jscott3201/aionforge-memory
- Hard boundary: Do not present this pitfall as solved, verified, or ignorable unless later evidence explicitly closes it.

### Constraint 3: Security or permission risk requires verification

- Trigger: no_demo
- Host AI rule: Reproduce the official install and quickstart path in an isolated environment.
- Why it matters: May increase setup, validation, or first-run risk for the user.
- Evidence: risks.scoring_risks | https://github.com/jscott3201/aionforge-memory
- Hard boundary: Do not present this pitfall as solved, verified, or ignorable unless later evidence explicitly closes it.

### Constraint 4: Maintenance risk requires verification

- Trigger: issue_or_pr_quality=unknown。
- Host AI rule: Reproduce the official install and quickstart path in an isolated environment.
- Why it matters: May increase setup, validation, or first-run risk for the user.
- Evidence: evidence.maintainer_signals | https://github.com/jscott3201/aionforge-memory
- Hard boundary: Do not present this pitfall as solved, verified, or ignorable unless later evidence explicitly closes it.

### Constraint 5: Maintenance risk requires verification

- Trigger: release_recency=unknown。
- Host AI rule: Reproduce the official install and quickstart path in an isolated environment.
- Why it matters: May increase setup, validation, or first-run risk for the user.
- Evidence: evidence.maintainer_signals | https://github.com/jscott3201/aionforge-memory
- Hard boundary: Do not present this pitfall as solved, verified, or ignorable unless later evidence explicitly closes it.