# mnemoq - 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 mnemoq. 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_0002` supported 0.86

## What It Can Do

- **Command-Line Startup or Install Flow** (Verify after install): The project documentation contains runnable commands; real use requires running them in a local or host environment. Evidence: `README.md` Claim: `clm_0001` supported 0.86

## How to Start

- `pip install mnemoq` Evidence: `README.md` Claim: `clm_0003` supported 0.86
- `pipx install mnemoq` Evidence: `README.md` Claim: `clm_0004` supported 0.86
- `git clone https://github.com/Mnemoq/MnemoQ.git` Evidence: `README.md` Claim: `clm_0005` supported 0.86
- `pip install -e ".[dev]"` Evidence: `README.md` Claim: `clm_0006` supported 0.86

## Continue-or-Stop Decision Card

- **Current recommendation**: Trial role matching first
- **Why**: This project is more of a role library; the core risk is picking the wrong role or treating role copy as execution capability. Trial role matching with Prompt Preview first, then decide whether to sandbox-import it.

### 30-Second Read

- **What to do now**: Trial role matching first
- **Minimum safe next step**: Trial role matching with Prompt Preview first; import in isolation only once satisfied
- **Do not trust yet**: Role quality and task fit cannot be trusted directly.
- **Continuing will touch**: Role selection bias, Command execution, Host AI configuration

### 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_0002` supported 0.86
- **Capability exists: Command-Line Startup or Install Flow** (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: `README.md` Claim: `clm_0001` supported 0.86
- **There are Quick Start / install-command signals** (supported): You can trust that the docs mention a startup or install entrypoint; do not run it directly in your primary environment because of that. Evidence: `README.md` Claim: `clm_0003` supported 0.86

### What You Cannot Trust Yet

- **Role quality and task fit cannot be trusted directly.** (unverified): A role library proves there are many roles; it does not prove each one fits your specific task or that a role produces high-quality results.
- **Do not treat role copy as real execution capability.** (unverified): Before install you can only judge whether the role description and task profile match; you cannot prove it can complete the task inside the host AI.
- **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.md`
- **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.
- **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

- **Role selection bias**: The user's judgment about which expert role should handle the task. Why: Picking the wrong role makes the AI answer from the wrong expert perspective, wasting time or misleading decisions.
- **Command execution**: Package managers, network downloads, the local plugin directory, project config, or the user's home directory. Why: Running the very first command can already change your environment; decide whether it is worth running first. Evidence: `README.md`
- **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.md`
- **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: `README.md`
- **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 an interactive trial to verify the task profile and role match first; do not import the whole role library up front. (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.
- **Keep a record of the original role selection**: If output goes off-topic, you can return to the task-profiling stage and reselect a role instead of pushing on with the wrong one.
- **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_0007` inferred 0.45
- **Command execution will modify the local environment**: Install commands may write to the user's home directory, the host plugin directory, or project configuration. Mitigation: Run in an isolated environment or a test account first. Evidence: `README.md` Claim: `clm_0008` 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.
- **To confirm**: Do the install commands require network access, permissions, or global writes?. Why: This affects install risk in both enterprise and personal environments.

## 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

- **Command-Line Startup or Install Flow**: 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: `README.md` Claim: `clm_0001` supported 0.86

### Context Scale

- Total files: 216
- Important-file coverage: 40/216
- Evidence index entries: 77
- Role / Skill entries: 68

### 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 mnemoq, 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 mnemoq 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 mnemoq, 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 68 role / Skill / project-doc entries.

- **MnemoQ Documentation** (project_doc): Complete documentation for the MnemoQ agent memory engine. Start here if you're new. Activation hint: Reference this when the user needs to understand the project's structure, install path, or boundaries. Evidence: `docs/README.md`
- **.claude** (project_doc): Personal project profile for Claude Code , alongside the other agent profiles in this repo .devin/ , .opencode/ , .windsurf/ . Activation hint: Reference this when the user needs to understand the project's structure, install path, or boundaries. Evidence: `.claude/README.md`
- **MnemoQ** (project_doc): Local-first memory engine for AI agents — MCP-native, graph-linked, spaced repetition. Activation hint: Reference this when the user needs to understand the project's structure, install path, or boundaries. Evidence: `README.md`
- **Agent Guidelines** (project_doc): Architecture cli.py is a thin dispatcher — all logic lives in src/mnemoq/engine/ modules. Always pass ctx dict and Paths to engine functions; never read module globals directly. Activation hint: Reference this when the user needs to understand the project's structure, install path, or boundaries. Evidence: `AGENTS.md`
- **Architecture Overview** (project_doc): MnemoQ is a local-first memory engine for AI agents. It stores learnings as JSONL, retrieves them via a multi-channel scoring pipeline, and integrates with any MCP-compatible client. This doc gives newcomers a conceptual map and contributors a module-level reference. Activation hint: Reference this when the user needs to understand the project's structure, install path, or boundaries. Evidence: `docs/architecture-overview.md`
- **CLI Reference** (project_doc): Complete reference for all MnemoQ command-line tools. Activation hint: Reference this when the user needs to understand the project's structure, install path, or boundaries. Evidence: `docs/cli-reference.md`
- **Config Tuning Guide** (project_doc): config.json provides project-specific tuning overlaid on engine defaults. Every parameter below has a sensible default in src/agent memory/engine/constants.py ; your memory/config.json overrides only what you need. See templates/config.json for the full template and templates/config-presets/ for ready-made presets. Activation hint: Reference this when the user needs to understand the project's structure, install path, or boundaries. Evidence: `docs/config-tuning.md`
- **Integration Guide — Closing the Learning Loop** (project_doc): Integration Guide — Closing the Learning Loop Activation hint: Reference this when the user needs to understand the project's structure, install path, or boundaries. Evidence: `docs/integration-guide.md`
- **MCP Integration Guide** (project_doc): The Model Context Protocol MCP is the primary integration path for AI agents to access MnemoQ's memory engine. This guide covers installation, client configuration, tool reference, and troubleshooting. Activation hint: Reference this when the user needs to understand the project's structure, install path, or boundaries. Evidence: `docs/mcp-integration.md`
- **Open-Core Architecture** (project_doc): MnemoQ uses an open-core model: the AGPL-3.0-or-later core lives in this public repo, while a proprietary Pro tier runs from a separate private repo. Activation hint: Reference this when the user needs to understand the project's structure, install path, or boundaries. Evidence: `docs/open-core-architecture.md`
- **Python SDK Guide** (project_doc): Programmatic access to the MnemoQ memory engine — log, retrieve, update, resolve, consolidate, and read metrics from Python code. Activation hint: Reference this when the user needs to understand the project's structure, install path, or boundaries. Evidence: `docs/sdk-guide.md`
- **Contributing to MnemoQ** (project_doc): Thank you for your interest in contributing! This document covers everything you need to get started. Activation hint: Reference this when the user needs to understand the project's structure, install path, or boundaries. Evidence: `CONTRIBUTING.md`
- **Roadmap** (project_doc): - x BM25 lexical scoring + Reciprocal Rank Fusion RRF - x Embedding-based retrieval sentence-transformers , hybrid scoring - x Embedding-based semantic dedup cosine ≥ 0.85 → merge - x Optional reranking pass cross-encoder, LLM-local - x Grading harness --eval Activation hint: Reference this when the user needs to understand the project's structure, install path, or boundaries. Evidence: `docs/ROADMAP.md`
- **Data Schema Reference** (project_doc): Canonical reference for the learnings.jsonl entry schema. Each line is a JSON object conforming to the fields below. Activation hint: Reference this when the user needs to understand the project's structure, install path, or boundaries. Evidence: `docs/data-schema.md`
- **Changelog** (project_doc): All notable changes to MnemoQ will be documented in this file. Activation hint: Reference this when the user needs to understand the project's structure, install path, or boundaries. Evidence: `CHANGELOG.md`
- **Contributor License Agreement** (project_doc): Thank you for your interest in contributing to MnemoQ "the Project" . Activation hint: Reference this when the user needs to understand the project's structure, install path, or boundaries. Evidence: `CLA.md`
- **Security Policy** (project_doc): Do not open a public issue for security vulnerabilities. Activation hint: Reference this when the user needs to understand the project's structure, install path, or boundaries. Evidence: `SECURITY.md`
- **System Invariants** (project_doc): Consolidated structural rules. IMMUTABLE during active tasks. Only updated during Sleep Cycle. Activation hint: Reference this when the user needs to understand the project's structure, install path, or boundaries. Evidence: `memory/SYSTEM_INVARIANTS.md`
- **Memory** (project_doc): Session start: memory/HANDOFF.md and memory/SYSTEM INVARIANTS.md are auto-loaded by your IDE/agent platform. Act on HANDOFF's "next action" line if present. Activation hint: Reference this when the user needs to understand the project's structure, install path, or boundaries. Evidence: `templates/agents-memory-section.md`
- **Review Priority Order** (project_doc): Reviews code diffs against project rules. Structured report with severity-ranked findings. Read-only. Activation hint: Reference this when the user needs to understand the project's structure, install path, or boundaries. Evidence: `.claude/agents/code-reviewer.md`
- **Your Mission** (project_doc): Keeps READMEs, API docs, and inline comments in sync with code changes. Only touches .md files. Activation hint: Reference this when the user needs to understand the project's structure, install path, or boundaries. Evidence: `.claude/agents/docs-writer.md`
- **Your Mission** (project_doc): Context gatherer — maps how a feature works across the codebase, returns focused summary. Read-only. Activation hint: Reference this when the user needs to understand the project's structure, install path, or boundaries. Evidence: `.claude/agents/explorer.md`
- **Your Mission** (project_doc): Adversarial tester — writes edge-case tests, runs them, reports failures. Never edits src/. Activation hint: Reference this when the user needs to understand the project's structure, install path, or boundaries. Evidence: `.claude/agents/fuzzer.md`
- **Core Directives** (project_doc): Primary co-developer and orchestrator. Drives tasks to completion, verifies, and commits. Activation hint: Reference this when the user needs to understand the project's structure, install path, or boundaries. Evidence: `.claude/agents/gm.md`
- **Environment** (project_doc): Meta-agent that analyzes failure patterns from recent sessions and evolves subagent prompts to eliminate recurring failures. Activation hint: Reference this when the user needs to understand the project's structure, install path, or boundaries. Evidence: `.claude/agents/meta-agent.md`
- **Plan Deviation Protocol** (project_doc): Surface plan deviations as decision points before implementing them Activation hint: Reference this when the user needs to understand the project's structure, install path, or boundaries. Evidence: `.claude/agents/plan-deviation.md`
- **Readiness Rubric** (project_doc): Audits plan files for readiness. Scores 0-5, identifies gaps, consolidates clarifying questions. Read-only. Activation hint: Reference this when the user needs to understand the project's structure, install path, or boundaries. Evidence: `.claude/agents/plan-reviewer.md`
- **Your Mission** (project_doc): Structural changes extract, rename, split without changing behavior. Runs tests after each step. Activation hint: Reference this when the user needs to understand the project's structure, install path, or boundaries. Evidence: `.claude/agents/refactorer.md`
- **Your Mission** (project_doc): Security auditor — hardcoded secrets, injection, missing auth, unsafe deserialization. Read-only. Activation hint: Reference this when the user needs to understand the project's structure, install path, or boundaries. Evidence: `.claude/agents/security.md`
- **Git Session Lock Snippet** (project_doc): Shared lock-check and lock-release instructions for git-mutating workflows. This is NOT a standalone command — it is referenced by other commands. Activation hint: Reference this when the user needs to understand the project's structure, install path, or boundaries. Evidence: `.claude/commands/_git-lock.md`
- **Steps** (project_doc): Stages changes cleanly and produces a well-structured Conventional Commit message with branch hygiene checks. Activation hint: Reference this when the user needs to understand the project's structure, install path, or boundaries. Evidence: `.claude/commands/commit.md`
- **When to use** (project_doc): Fast ship cycle for small safe edits — same pipeline as /ship but auto-selects sensible defaults and skips local tests. Activation hint: Reference this when the user needs to understand the project's structure, install path, or boundaries. Evidence: `.claude/commands/fast-ship.md`
- **Steps** (project_doc): Create, check, update, and merge pull requests via gh CLI. Activation hint: Reference this when the user needs to understand the project's structure, install path, or boundaries. Evidence: `.claude/commands/pr.md`
- **Steps** (project_doc): Bumps VERSION, commits, tags, and pushes from main to trigger the PyPI publish workflow. Activation hint: Reference this when the user needs to understand the project's structure, install path, or boundaries. Evidence: `.claude/commands/publish.md`
- **Steps** (project_doc): Pre-flight checks, remote sync, clean push, and post-push verification with CI status and PR creation. Activation hint: Reference this when the user needs to understand the project's structure, install path, or boundaries. Evidence: `.claude/commands/push.md`
- **Steps** (project_doc): Rebase feature branch onto main, squash/reorder commits, and resolve conflicts with structured guidance. Activation hint: Reference this when the user needs to understand the project's structure, install path, or boundaries. Evidence: `.claude/commands/rebase.md`
- **Steps** (project_doc): Full ship cycle — commit, push, rebase if needed, create PR, verify CI, and merge. Delegates to individual commands at each step. Activation hint: Reference this when the user needs to understand the project's structure, install path, or boundaries. Evidence: `.claude/commands/ship.md`
- **Pro** (project_doc):  Activation hint: Reference this when the user needs to understand the project's structure, install path, or boundaries. Evidence: `.devin/workflows/pro.md`
- **Your Mission** (project_doc): Adversarial tester — writes edge-case tests, runs them, reports failures. Never edits src/. Activation hint: Reference this when the user needs to understand the project's structure, install path, or boundaries. Evidence: `.opencode/Prompts/Fuzzer.md`
- **Basic Reviewer** (project_doc): You are a QA auditor for technical plans. Score readiness 0-5, identify gaps and missing test criteria. Read-only. Activation hint: Reference this when the user needs to understand the project's structure, install path, or boundaries. Evidence: `.opencode/Prompts/basic-reviewer.md`
- **Review Priority Order** (project_doc): Reviews code diffs against project rules. Structured report with severity-ranked findings. Read-only. Activation hint: Reference this when the user needs to understand the project's structure, install path, or boundaries. Evidence: `.opencode/Prompts/code-reviewer.md`
- **Your Mission** (project_doc): Keeps READMEs, API docs, and inline comments in sync with code changes. Only touches .md files. Activation hint: Reference this when the user needs to understand the project's structure, install path, or boundaries. Evidence: `.opencode/Prompts/docs-writer.md`
- **Your Mission** (project_doc): Context gatherer — maps how a feature works across the codebase, returns focused summary. Read-only. Activation hint: Reference this when the user needs to understand the project's structure, install path, or boundaries. Evidence: `.opencode/Prompts/explorer.md`
- **Core Directives** (project_doc): Primary co-developer and orchestrator. Drives tasks to completion, verifies, and commits. Activation hint: Reference this when the user needs to understand the project's structure, install path, or boundaries. Evidence: `.opencode/Prompts/gm.md`
- **Environment** (project_doc): Meta-agent that analyzes failure patterns from recent sessions and evolves subagent prompts to eliminate recurring failures. Activation hint: Reference this when the user needs to understand the project's structure, install path, or boundaries. Evidence: `.opencode/Prompts/meta-agent.md`
- **Plan Deviation Protocol** (project_doc): Surface plan deviations as decision points before implementing them Activation hint: Reference this when the user needs to understand the project's structure, install path, or boundaries. Evidence: `.opencode/Prompts/plan-deviation.md`
- **Readiness Rubric** (project_doc): Audits plan files for readiness. Scores 0-5, identifies gaps, consolidates clarifying questions. Read-only. Activation hint: Reference this when the user needs to understand the project's structure, install path, or boundaries. Evidence: `.opencode/Prompts/plan-reviewer.md`
- **Input** (project_doc): Interactively triage /plan-reviewer findings — accept, defer, or dismiss each, then batch-apply plan edits. Activation hint: Reference this when the user needs to understand the project's structure, install path, or boundaries. Evidence: `.opencode/Prompts/plan-triage.md`
- **Your Mission** (project_doc): Structural changes extract, rename, split without changing behavior. Runs tests after each step. Activation hint: Reference this when the user needs to understand the project's structure, install path, or boundaries. Evidence: `.opencode/Prompts/refactorer.md`
- **Your Mission** (project_doc): Security auditor — hardcoded secrets, injection, missing auth, unsafe deserialization. Read-only. Activation hint: Reference this when the user needs to understand the project's structure, install path, or boundaries. Evidence: `.opencode/Prompts/security.md`
- **Input** (project_doc): Triage a /code-reviewer report — decide what to fix, defer, or dismiss, then execute fixes. Invoke after /code-reviewer. Activation hint: Reference this when the user needs to understand the project's structure, install path, or boundaries. Evidence: `.opencode/Prompts/triage-review.md`
- **Biomimicry 4-Stage Pipeline** (project_doc): Run the biomimicry 4-agent loop on a software problem. Usage: /bioloop Activation hint: Reference this when the user needs to understand the project's structure, install path, or boundaries. Evidence: `.opencode/commands/bioloop.md`
- **Steps** (project_doc): Stages changes cleanly and produces a well-structured Conventional Commit message with branch hygiene checks. Activation hint: Reference this when the user needs to understand the project's structure, install path, or boundaries. Evidence: `.opencode/commands/commit.md`
- **When to use** (project_doc): Fast ship cycle for small safe edits — same pipeline as /ship but auto-selects sensible defaults and skips local tests. No confirmation prompts between steps. Activation hint: Reference this when the user needs to understand the project's structure, install path, or boundaries. Evidence: `.opencode/commands/fast-ship.md`
- **Steps** (project_doc): Create, check, update, and merge pull requests via gh CLI. Activation hint: Reference this when the user needs to understand the project's structure, install path, or boundaries. Evidence: `.opencode/commands/pr.md`
- **Steps** (project_doc): Bumps VERSION, commits, tags, and pushes from main to trigger the PyPI publish workflow. Activation hint: Reference this when the user needs to understand the project's structure, install path, or boundaries. Evidence: `.opencode/commands/publish.md`
- **Steps** (project_doc): Pre-flight checks, remote sync, clean push, and post-push verification with CI status and PR creation. Activation hint: Reference this when the user needs to understand the project's structure, install path, or boundaries. Evidence: `.opencode/commands/push.md`
- **Steps** (project_doc): Rebase feature branch onto main, squash/reorder commits, and resolve conflicts with structured guidance. Activation hint: Reference this when the user needs to understand the project's structure, install path, or boundaries. Evidence: `.opencode/commands/rebase.md`
- **Steps** (project_doc): Full ship cycle — commit, push, rebase if needed, create PR, verify CI, and merge. Delegates to individual workflows at each step. Activation hint: Reference this when the user needs to understand the project's structure, install path, or boundaries. Evidence: `.opencode/commands/ship.md`
- **Git Session Lock Snippet** (project_doc): Shared lock-check and lock-release instructions for git-mutating workflows. This is NOT a standalone workflow — it is referenced by other workflows. Activation hint: Reference this when the user needs to understand the project's structure, install path, or boundaries. Evidence: `.windsurf/workflows/_git-lock.md`
- **Steps** (project_doc): Manually capture the current conversation as memory via mnemoq --capture-file. Activation hint: Reference this when the user needs to understand the project's structure, install path, or boundaries. Evidence: `.windsurf/workflows/capture.md`
- **Review Priority Order** (project_doc): Reviews code diffs against project rules. Structured report with severity-ranked findings. Read-only. Activation hint: Reference this when the user needs to understand the project's structure, install path, or boundaries. Evidence: `.windsurf/workflows/code-reviewer.md`
- **Steps** (project_doc): Stages changes cleanly and produces a well-structured Conventional Commit message with branch hygiene checks. Activation hint: Reference this when the user needs to understand the project's structure, install path, or boundaries. Evidence: `.windsurf/workflows/commit.md`
- **Your Mission** (project_doc): Keeps READMEs, API docs, and inline comments in sync with code changes. Only touches .md files. Activation hint: Reference this when the user needs to understand the project's structure, install path, or boundaries. Evidence: `.windsurf/workflows/docs-writer.md`
- **Your Mission** (project_doc): Context gatherer — maps how a feature works across the codebase, returns focused summary. Read-only. Activation hint: Reference this when the user needs to understand the project's structure, install path, or boundaries. Evidence: `.windsurf/workflows/explorer.md`
- **When to use** (project_doc): Fast ship cycle for small safe edits — same pipeline as /ship but auto-selects sensible defaults and skips local tests. No confirmation prompts between steps. Activation hint: Reference this when the user needs to understand the project's structure, install path, or boundaries. Evidence: `.windsurf/workflows/fast-ship.md`
- **Your Mission** (project_doc): Adversarial tester — writes edge-case tests, runs them, reports failures. Never edits src/. Activation hint: Reference this when the user needs to understand the project's structure, install path, or boundaries. Evidence: `.windsurf/workflows/fuzzer.md`
- **Core Directives** (project_doc): Primary co-developer and orchestrator. Drives tasks to completion, verifies, and commits. Activation hint: Reference this when the user needs to understand the project's structure, install path, or boundaries. Evidence: `.windsurf/workflows/gm.md`

## Evidence Index

- Indexed 77 evidence entries.

- **MnemoQ Documentation** (documentation): Complete documentation for the MnemoQ agent memory engine. Start here if you're new. Evidence: `docs/README.md`
- **.claude** (documentation): Personal project profile for Claude Code , alongside the other agent profiles in this repo .devin/ , .opencode/ , .windsurf/ . Evidence: `.claude/README.md`
- **MnemoQ** (documentation): Local-first memory engine for AI agents — MCP-native, graph-linked, spaced repetition. Evidence: `README.md`
- **Agent Guidelines** (documentation): Architecture cli.py is a thin dispatcher — all logic lives in src/mnemoq/engine/ modules. Always pass ctx dict and Paths to engine functions; never read module globals directly. Evidence: `AGENTS.md`
- **Architecture Overview** (documentation): MnemoQ is a local-first memory engine for AI agents. It stores learnings as JSONL, retrieves them via a multi-channel scoring pipeline, and integrates with any MCP-compatible client. This doc gives newcomers a conceptual map and contributors a module-level reference. Evidence: `docs/architecture-overview.md`
- **CLI Reference** (documentation): Complete reference for all MnemoQ command-line tools. Evidence: `docs/cli-reference.md`
- **Config Tuning Guide** (documentation): config.json provides project-specific tuning overlaid on engine defaults. Every parameter below has a sensible default in src/agent memory/engine/constants.py ; your memory/config.json overrides only what you need. See templates/config.json for the full template and templates/config-presets/ for ready-made presets. Evidence: `docs/config-tuning.md`
- **Integration Guide — Closing the Learning Loop** (documentation): Integration Guide — Closing the Learning Loop Evidence: `docs/integration-guide.md`
- **MCP Integration Guide** (documentation): The Model Context Protocol MCP is the primary integration path for AI agents to access MnemoQ's memory engine. This guide covers installation, client configuration, tool reference, and troubleshooting. Evidence: `docs/mcp-integration.md`
- **Open-Core Architecture** (documentation): MnemoQ uses an open-core model: the AGPL-3.0-or-later core lives in this public repo, while a proprietary Pro tier runs from a separate private repo. Evidence: `docs/open-core-architecture.md`
- **Python SDK Guide** (documentation): Programmatic access to the MnemoQ memory engine — log, retrieve, update, resolve, consolidate, and read metrics from Python code. Evidence: `docs/sdk-guide.md`
- **Contributing to MnemoQ** (documentation): Thank you for your interest in contributing! This document covers everything you need to get started. Evidence: `CONTRIBUTING.md`
- **License** (source_file): GNU AFFERO GENERAL PUBLIC LICENSE Version 3, 19 November 2007 Evidence: `LICENSE`
- **Roadmap** (documentation): - x BM25 lexical scoring + Reciprocal Rank Fusion RRF - x Embedding-based retrieval sentence-transformers , hybrid scoring - x Embedding-based semantic dedup cosine ≥ 0.85 → merge - x Optional reranking pass cross-encoder, LLM-local - x Grading harness --eval Evidence: `docs/ROADMAP.md`
- **Data Schema Reference** (documentation): Canonical reference for the learnings.jsonl entry schema. Each line is a JSON object conforming to the fields below. Evidence: `docs/data-schema.md`
- **Init** (source_file): version = get engine version ⋮---- def getattr name ⋮---- all = "MemoryClient", "LearningEntry", " version " Evidence: `src/mnemoq/__init__.py`
- **Whitelist of tuning parameters with type and range validation** (source_file): @dataclass frozen=True class Paths ⋮---- memory dir: str repo root: str config path: str learnings path: str quarantine path: str archive dir: str session file: str agents md path: str ⋮---- ENGINE VERSION = get engine version ⋮---- PATHS: Paths None = None ⋮---- def get paths - Paths ⋮---- CTX = {k.lower : v for k, v in CONST DEFAULTS.items } ⋮---- def resolve memory dir memory dir arg: str None - str ⋮---- raw = memory dir arg.strip ⋮---- env dir = os.environ.get "AGENT MEMORY DIR" ⋮---- raw = env dir.strip ⋮---- cwd memory = os.path.join os.getcwd , "memory" ⋮---- def setup paths memory dir arg: str None - Paths ⋮---- memory dir = resolve memory dir memory dir arg repo root = os.path.dir… Evidence: `src/mnemoq/cli.py`
- **Apply staleness boost** (source_file): PATH DOMAIN MAP = { ⋮---- def derive domain file path ⋮---- path lower = file path.lower .replace "\\", "/" ⋮---- def detect under retrieved entries, ctx ⋮---- access thresh = ctx.get "auto learn under retrieved access", 2 reinforcement thresh = ctx.get "auto learn under retrieved reinforcement", 5 results = ⋮---- access count = entry.get "access count", 0 reinforcement count = entry.get "reinforcement count", 0 ⋮---- def detect conflicts entries, ctx ⋮---- unresolved = e for e in entries if not e.get "resolved", False ⋮---- comps i = {c.lower for c in entry i.get "components", } comps j = {c.lower for c in entry j.get "components", } ⋮---- shared components = list comps i & comps j all fil… Evidence: `src/mnemoq/engine/auto_learn.py`
- **Strip markdown code fences** (source_file): EXTRACTION SYSTEM = ⋮---- MAX CONVERSATION CHARS = 8000 ⋮---- def build extraction prompt conversation text: str - str ⋮---- truncated = conversation text : MAX CONVERSATION CHARS ⋮---- def parse llm response response text: str - list dict None ⋮---- """Extract JSON array from LLM response. Handles markdown code fences.""" ⋮---- text = response text.strip Strip markdown code fences ⋮---- lines = text.split "\n" ⋮---- lines = line for line in lines if not line.strip .startswith " " text = "\n".join lines .strip ⋮---- data = json.loads text ⋮---- match = re.search r'\ . \ ', text, re.DOTALL ⋮---- data = json.loads match.group ⋮---- entries = data "entries" ⋮---- ------------------------------… Evidence: `src/mnemoq/engine/capture.py`
- **Consolidation** (source_file): def sprint metrics paths ⋮---- events = read metrics paths ⋮---- retrievals = e for e in events if e.get "event type" == "retrieval" logs = e for e in events if e.get "event type" == "log" ⋮---- lines = ⋮---- hits = sum 1 for e in retrievals avg lat = sum e.get "latency ms", 0 or 0 for e in retrievals / len retrievals ⋮---- dups = sum 1 for e in logs if e.get "outcome" == "DUPLICATE" quars = sum 1 for e in logs if e.get "outcome" == "QUARANTINED" ⋮---- all lat = e.get "latency ms", 0 or 0 for e in events if e.get "latency ms" ⋮---- def score for promotion entry, current step, ctx ⋮---- access count = entry.get "access count", 0 severity = entry.get "severity", "minor" step diff = current st… Evidence: `src/mnemoq/engine/consolidation.py`
- **Homeostasis** (source_file): STATE FILENAME = ".domain state.json" ⋮---- ACCEPT STATUSES = {"added"} ACTUATION REJECT STATUSES = {"duplicate", "semantic duplicate"} DETECTOR REJECT STATUSES = {"conflict", "quarantined"} ⋮---- def state path paths ⋮---- def blank ⋮---- def load state paths ⋮---- path = state path paths ⋮---- data = json.load f ⋮---- def save state paths, state ⋮---- def domain state, domain ⋮---- entry = state.get domain ⋮---- entry = blank ⋮---- def decay all state, decay ⋮---- entry = domain state, domain ⋮---- def effective threshold state, domain, base, ctx ⋮---- floor = ctx.get "adaptive offset floor", 0.1 ceiling = ctx.get "adaptive offset ceiling", 0.2 ⋮---- offset = float entry.get "offset", 0.0… Evidence: `src/mnemoq/engine/homeostasis.py`
- **Hooks** (source_file): POST COMMIT HOOK = """ !/bin/sh ⋮---- PRE COMMIT HOOK = """ !/bin/sh ⋮---- HOOK BODIES = { ⋮---- MNEMOQ MARKERS = "mnemoq", "mnemoq.cli" ⋮---- def is mnemoq hook path: Path - bool ⋮---- text = path.read text encoding="utf-8", errors="replace" ⋮---- def write hook hook path: Path, body: str - bool ⋮---- def resolve default hooks dir - Path None ⋮---- out = subprocess.run ⋮---- hooks dir = Path out.stdout.strip ⋮---- hooks dir = Path.cwd / hooks dir ⋮---- def set core hooks path value: str - bool ⋮---- def install hooks hooks path: str None = None - int Evidence: `src/mnemoq/engine/hooks.py`
- **Triggers** (source_file): def last consolidation event paths ⋮---- path = metrics path paths ⋮---- last = None ⋮---- line = line.strip ⋮---- event = json.loads line ⋮---- last = event ⋮---- def last consolidation ts paths ⋮---- event = last consolidation event paths ⋮---- def effective sleep days base days, ctx, last event ⋮---- adjustment = ctx.get "consolidation interval adjustment", 0.25 ⋮---- activity = si last event.get "promotion candidates" ref = ctx.get "sleep cycle unresolved threshold", 20 or 20 a = min 1.0, activity / ref if ref 0 else 0.0 factor = 1 + adjustment 2 a - 1 eff = base days factor floor = max 0.5, base days 1 - adjustment ceiling = base days 1 + adjustment ⋮---- def check sleep cycle paths, c… Evidence: `src/mnemoq/engine/triggers.py`
- **Init** (source_file): all = Evidence: `src/mnemoq/sdk/__init__.py`
- **Changelog** (documentation): All notable changes to MnemoQ will be documented in this file. Evidence: `CHANGELOG.md`
- **Contributor License Agreement** (documentation): Thank you for your interest in contributing to MnemoQ "the Project" . Evidence: `CLA.md`
- **Security Policy** (documentation): Do not open a public issue for security vulnerabilities. Evidence: `SECURITY.md`
- **System Invariants** (documentation): Consolidated structural rules. IMMUTABLE during active tasks. Only updated during Sleep Cycle. Evidence: `memory/SYSTEM_INVARIANTS.md`
- **Memory** (documentation): Session start: memory/HANDOFF.md and memory/SYSTEM INVARIANTS.md are auto-loaded by your IDE/agent platform. Act on HANDOFF's "next action" line if present. Evidence: `templates/agents-memory-section.md`
- **Review Priority Order** (documentation): You are a senior code reviewer for this project. You review diffs against this project's engineering rules and produce a structured report with severity-ranked findings. Evidence: `.claude/agents/code-reviewer.md`
- **Your Mission** (documentation): You are the Docs Writer for AgentMemoryEngine. Your job is to keep READMEs, API docs, and inline comments in sync with code changes. Evidence: `.claude/agents/docs-writer.md`
- **Your Mission** (documentation): You are the Explorer for AgentMemoryEngine. Your job is to map how a feature works across the codebase and return a focused, structured summary. You are cheap, high-volume reading — the parent agent plans against your summary. Evidence: `.claude/agents/explorer.md`
- **Your Mission** (documentation): You are the Fuzzer. A feature has just been implemented for AgentMemoryEngine. Your job is to try and break it. Evidence: `.claude/agents/fuzzer.md`
- **Core Directives** (documentation): You are GM , the primary co-developer and orchestrator for this project. You are highly autonomous and strictly action-oriented. You exist to build exceptional software alongside the human developer, keeping their session entirely clean of tool noise. Evidence: `.claude/agents/gm.md`
- **Environment** (documentation): You are the Meta-agent. Your sole purpose is to analyze agent performance data and evolve agent prompts to eliminate recurring failures for AgentMemoryEngine. Evidence: `.claude/agents/meta-agent.md`
- **Plan Deviation Protocol** (documentation): When implementing from a plan file, deviations from the stated approach must be surfaced before coding, not mentioned after. Evidence: `.claude/agents/plan-deviation.md`
- **Readiness Rubric** (documentation): You are a precise QA auditor for technical plans. You inspect plans for missing requirements, unstated assumptions, unclear architecture, incomplete acceptance criteria, missing test coverage, and unresolved blockers. Evidence: `.claude/agents/plan-reviewer.md`
- **Your Mission** (documentation): You are the Refactorer for AgentMemoryEngine. Your job is to make structural changes extract functions, rename across files, split modules without changing behavior. Evidence: `.claude/agents/refactorer.md`
- **Your Mission** (documentation): You are the Security Auditor for AgentMemoryEngine. Your job is to perform a focused security pass looking for hardcoded secrets, injection-prone queries, missing authorization, unsafe deserialization, and risky dependencies. Evidence: `.claude/agents/security.md`
- **Git Session Lock Snippet** (documentation): Shared lock-check and lock-release instructions for git-mutating workflows. This is NOT a standalone command — it is referenced by other commands. Evidence: `.claude/commands/_git-lock.md`
- **Steps** (documentation): Acquire the git session lock before proceeding. See git-lock.md for the full lock-check snippet. Evidence: `.claude/commands/commit.md`
- **When to use** (documentation): Small, low-risk edits you are confident about: typo fixes, doc updates, one-line tweaks, config bumps. If the change touches logic, tests, or anything that could break CI use /ship instead. Evidence: `.claude/commands/fast-ship.md`
- **Steps** (documentation): If gh is not installed or not authenticated, stop and tell the user to install it winget install GitHub.cli and authenticate gh auth login . All PR operations require gh . Evidence: `.claude/commands/pr.md`
- **Steps** (documentation): Acquire the git session lock before proceeding. See git-lock.md for the full lock-check snippet. Evidence: `.claude/commands/publish.md`
- **Steps** (documentation): Acquire the git session lock before proceeding. See git-lock.md for the full lock-check snippet. Evidence: `.claude/commands/push.md`
- **Steps** (documentation): Acquire the git session lock before proceeding. See git-lock.md for the full lock-check snippet. Evidence: `.claude/commands/rebase.md`
- **Steps** (documentation): Branch check run before anything else : Evidence: `.claude/commands/ship.md`
- **Your Mission** (documentation): You are the Fuzzer. A feature has just been implemented for AgentMemoryEngine. Your job is to try and break it. Evidence: `.opencode/Prompts/Fuzzer.md`
- **Basic Reviewer** (documentation): You are a QA auditor for technical plans. Score readiness 0-5, identify gaps and missing test criteria. Read-only. Evidence: `.opencode/Prompts/basic-reviewer.md`
- **Review Priority Order** (documentation): You are a senior code reviewer for this project. You review diffs against this project's engineering rules and produce a structured report with severity-ranked findings. Evidence: `.opencode/Prompts/code-reviewer.md`
- **Your Mission** (documentation): You are the Docs Writer for AgentMemoryEngine. Your job is to keep READMEs, API docs, and inline comments in sync with code changes. Evidence: `.opencode/Prompts/docs-writer.md`
- **Your Mission** (documentation): You are the Explorer for AgentMemoryEngine. Your job is to map how a feature works across the codebase and return a focused, structured summary. You are cheap, high-volume reading — the parent agent plans against your summary. Evidence: `.opencode/Prompts/explorer.md`
- **Core Directives** (documentation): You are GM , the primary co-developer and orchestrator for this project. You are highly autonomous and strictly action-oriented. You exist to build exceptional software alongside the human developer, keeping their session entirely clean of tool noise. Evidence: `.opencode/Prompts/gm.md`
- **Environment** (documentation): You are the Meta-agent. Your sole purpose is to analyze agent performance data and evolve agent prompts to eliminate recurring failures for AgentMemoryEngine. Evidence: `.opencode/Prompts/meta-agent.md`
- **Plan Deviation Protocol** (documentation): When implementing from a plan file, deviations from the stated approach must be surfaced before coding, not mentioned after. Evidence: `.opencode/Prompts/plan-deviation.md`
- **Readiness Rubric** (documentation): You are a precise QA auditor for technical plans. You inspect plans for missing requirements, unstated assumptions, unclear architecture, incomplete acceptance criteria, missing test coverage, and unresolved blockers. Evidence: `.opencode/Prompts/plan-reviewer.md`
- **Input** (documentation): You are a plan triage agent. You take a /plan-reviewer report and make accept/defer/dismiss recommendations for each finding, present them to the user for confirmation, then batch-apply accepted changes to the plan file. Evidence: `.opencode/Prompts/plan-triage.md`
- **Your Mission** (documentation): You are the Refactorer for AgentMemoryEngine. Your job is to make structural changes extract functions, rename across files, split modules without changing behavior. Evidence: `.opencode/Prompts/refactorer.md`
- **Your Mission** (documentation): You are the Security Auditor for AgentMemoryEngine. Your job is to perform a focused security pass looking for hardcoded secrets, injection-prone queries, missing authorization, unsafe deserialization, and risky dependencies. Evidence: `.opencode/Prompts/security.md`
- **Input** (documentation): You are a triage agent. You take a /code-reviewer report and make fix/defer/dismiss decisions for each finding, then implement the fixes. Evidence: `.opencode/Prompts/triage-review.md`
- The remaining 17 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`, `.claude/README.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`, `.claude/README.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.

- **Introduction and System Architecture**: importance `high`
  - source_paths: README.md, docs/README.md, docs/architecture-overview.md, docs/open-core-architecture.md, src/mnemoq/__init__.py
- **Data Schema, Retrieval, and Scoring Engine**: importance `high`
  - source_paths: docs/data-schema.md, src/mnemoq/engine/models.py, src/mnemoq/engine/retrieval.py, src/mnemoq/engine/validation.py, src/mnemoq/engine/reranker.py
- **Memory Lifecycle: Logging, Consolidation, Hooks, and Evaluation**: importance `high`
  - source_paths: src/mnemoq/engine/capture.py, src/mnemoq/engine/consolidation.py, src/mnemoq/engine/auto_learn.py, src/mnemoq/engine/hooks.py, src/mnemoq/engine/triggers.py
- **CLI, MCP Server, SDK, Configuration, and Multi-IDE Integration**: importance `high`
  - source_paths: docs/cli-reference.md, docs/config-tuning.md, docs/integration-guide.md, docs/mcp-integration.md, docs/sdk-guide.md

## Repo Inspection Evidence

- repo_clone_verified: true
- repo_inspection_verified: true
- repo_commit: `7caba68e2327651bd5cef21702cd6ac7f301f75c`
- inspected_files: `README.md`, `pyproject.toml`, `docs/README.md`, `docs/ROADMAP.md`, `docs/architecture-overview.md`, `docs/cli-reference.md`, `docs/config-tuning.md`, `docs/data-schema.md`, `docs/integration-guide.md`, `docs/mcp-integration.md`, `docs/open-core-architecture.md`, `docs/sdk-guide.md`, `src/mnemoq/__init__.py`, `src/mnemoq/cli.py`, `src/mnemoq/dashboard/__init__.py`, `src/mnemoq/dashboard/static/js/api.js`, `src/mnemoq/dashboard/static/js/app.js`, `src/mnemoq/dashboard/static/js/consolidation.js`, `src/mnemoq/dashboard/static/js/dashboard.js`, `src/mnemoq/dashboard/static/js/events.js`

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/Mnemoq/MnemoQ
- 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/Mnemoq/MnemoQ
- 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/Mnemoq/MnemoQ
- 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/Mnemoq/MnemoQ
- 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/Mnemoq/MnemoQ
- Hard boundary: Do not present this pitfall as solved, verified, or ignorable unless later evidence explicitly closes it.