agent-memory

Agent Memory Skill

Manage persistent project memory as reviewable markdown in the repository. Any file-reading agent can read and update the same .agent-memory/ files across sessions.

Capabilities

Design Principles

Initial Assessment

Before operating on memory, understand:

1. Current State — Does .agent-memory/ exist? What version/structure? Older formats needing migration?
2. Requested outcome — First-time setup, saving learnings, or maintenance?
3. Project Context — Project type, existing docs, how many people/agents contributing?

Commands

Infer the operation from a clear request; a literal command keyword is not required. For example, “remember why we chose SQLite” routes to Save, and “reconcile these memory files and capture our decision” routes to Sync. Ask one focused question only when the intended operation or a required input remains ambiguous. Preserve read-only requests: onboarding or reviewing existing memory does not authorize rebuilding or saving it.

For a developer handoff, read the index and relevant entries, summarize the current decisions and open questions, and cite their files. Preserve proposals as proposals. A newer timestamp alone does not resolve conflicting decisions; inspect their evidence and review status, then ask when the accepted direction is unknown. Record supersedes only when replacement is established.

For cross-repository work, use accessible references to the owning project's decisions with a revision when relevant. Summarize only the context needed locally; identify unavailable sources rather than inventing their contents. A request concerning one repository does not authorize edits to another.

Operation: Init

Scaffold the .agent-memory/ system from scratch.

Overwrite guard: Before creating or changing AGENTS.md, .agent-memory/index.yaml, .agent-memory/README.md, or any pointer file listed in references/agent-pointers.md, inspect any existing file and preserve its content. If a target file already exists and is not a thin compatible pointer, stage the proposed replacement and ask before overwriting. Report every file kept, created, or changed.

Memory format v2.1 — Entry Points

project/
├── AGENTS.md          # Canonical shared instructions
└── .agent-memory/     # Reviewable project memory

Key: AGENTS.md is the shared source of truth. Add thin pointer files only for agents the project already uses; recipes live in references/agent-pointers.md. Never put shared instructions inside a vendor-only directory. Detect native memory/rule locations read-only and report them; do not migrate or overwrite them implicitly.

Steps

1. Create directories: user/, feedback/, project/, decisions/, context/, conventions/, references/, sessions/ under .agent-memory/.
2. Create files: .agent-memory/README.md (system spec), .agent-memory/index.yaml (empty registry), and AGENTS.md (canonical shared instructions). Create pointer files only for agents already in use, following references/agent-pointers.md.
3. Complete AGENTS.md: replace every placeholder with the project's actual structure and rules. Done when no TODO or placeholder tokens remain.
4. Update index.yaml and report what was created.

Operation: Migrate

Detect and migrate older structures to memory format v2.1.

Steps: Scan for each old structure listed above → preserve existing content → perform only confirmed migrations → move shared instructions into AGENTS.md, then rewrite leftover client files as thin pointers per references/agent-pointers.md → reconcile index.yaml with filesystem → report what changed.

Migration guard: Renames, moves, and pointer rewrites are destructive. Before renaming CURSOR.md, INDEX.yaml, or replacing instruction files, show the planned source and destination paths and ask for confirmation unless the file is empty or already an exact generated pointer. Keep a backup or .migrated file whenever content is moved.

Operation: Build

Scan project and auto-generate initial memory files from existing docs.

1. Scan for docs: *.md, package.json, pyproject.toml, Cargo.toml, CLAUDE.md, AGENTS.md, *.yaml configs, .env.example
2. Distill each source: overview → project/overview.md, architecture → project/architecture.md, decisions → decisions/{topic}.md, conventions → conventions/{topic}.md, user preferences/collaboration style → user/preferences.md only when explicitly confirmed by the user
3. Rules: Summarize don't copy. One topic per file. Reference source docs. Use standard frontmatter.
4. Migrate old formats if found (flat files, old frontmatter fields)
5. Update index.yaml — add entries for each new file, reconcile with filesystem
6. Report with summary table

Operation: Save

Capture learnings from the current conversation into memory.

1. Review conversation for: decisions, feedback, conventions, status changes, important context
2. For each piece: update existing memory file or create new one in appropriate {type}/ directory. Create session log in sessions/ for significant sessions.
3. Source identifier: record the writing runtime as a slug (codex, claude-code, cursor, grok, openclaw, vscode, craft-agent, or other)
4. Write files using standard frontmatter format (see references/templates.md)
5. Update index.yaml and report what was saved/updated

Operation: Sync

Reconcile memory files already present in the current checkout, then save the session. Sync does not fetch, pull, merge, commit, push, or synchronize another repository or a vendor-native memory store. Git operations require their own task authorization and repository workflow.

Phase 1 — Ingest: Scan for unindexed files in .agent-memory/ (add to index) → scan for orphan index entries (remove) → read updated files for awareness.

Phase 2 — Save: Run the full Save operation (review, update/create, session log, index).

Phase 3 — Report: Single combined report (see references/templates.md for format).

Operation: Maintain

Full maintenance: compact, trim stale, fix index, clean old session logs.

1. Health check: Count files by type, check index sync, identify stale/expired entries.
2. Staleness check — frontmatter-driven:
   • Primary signal: expires field. If expires < today → flag as expired, ask update/archive/remove.
   • Fallback (no expires): Use updated date (or created if never updated) + type-based thresholds: context/ >30 days, sessions/ >60 days.
   • Archived entries: status: archived with updated >90 days ago → suggest deletion.
   • supersedes chain: If file A has supersedes: B, and B still exists with status: active, flag B for archival.
3. Compaction: Identify content overlap, suggest merges, promote session log patterns to conventions/ or decisions/.
4. Session cleanup: type: session with updated >60 days → extract valuable info elsewhere if needed, list deletion candidates, and ask for confirmation before deleting.
5. Report with health summary (see references/templates.md for format).

Operation: Status

Quick read-only health check. Count files by type, check index ↔ filesystem sync, report stale/expired entries. If .agent-memory/ doesn't exist, suggest init. If issues found, suggest maintain.

File Format Rules

1. Distill, don't transcribe. Summaries and decisions, not conversation dumps.
2. One idea per file. Split if a memory covers unrelated topics.
3. Update in place. When facts change, edit the file. Don't append forever.
4. Keep index in sync. Every file in index, every index entry points to a file.
5. Use expires on context. Context goes stale. Set a review date.
6. Reference, don't copy. Point to source docs instead of duplicating content.
7. No secrets. No credentials, PII, or sensitive data in memory files.
8. Absolute dates. Resolve relative dates from the date and timezone supplied by the task; otherwise use the current date and timezone. Compute and verify the calendar date, then save it as YYYY-MM-DD. Never copy a date from a template. Ask only when the intended reference date or relative phrase is ambiguous.

For frontmatter schema, memory types, and templates, see references/templates.md.

Reference Files

Assessment Checklist

Use these prompts to choose the operation, then proceed without collecting unnecessary information:

1. Does .agent-memory/ already exist, and what structure/version does it use?
2. Which operation fits the request: init, migrate, build, save, sync, maintain, or status?
3. Which instruction or pointer files already exist, do they point at AGENTS.md, and which vendor-native memory stores must be left untouched? See references/agent-pointers.md.
4. Which project docs can seed memory without copying them verbatim?
5. Is the memory local/private, or intended to be shared through git?

Adjacent Patterns

Behavioral evals

Authors/reviewers only: use the scenario catalog when explicitly evaluating this skill. Skip it during normal task execution. Materialize each case in a fresh temporary directory, withhold assertions from the executing agent, and grade the resulting artifacts and actions. The catalog defines expected behavior; it is not evidence of a passing run. Synthetic browser and service inputs test decisions only, not live integrations.