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Use Tree Ring Memory for local-first AI-agent memory lifecycle work: recall, evidence, audit, forgetting, and consolidation without transcript dumping.
デフォルトでは、最初にソースを確認する Prompt が選択されています。直接コマンドに切り替えるか、ローカルコピーをダウンロードすることもできます。
インストールを決める前に、SKILL.md と SkillsMP に表示されている付属ファイルをお読みください。
Codex または Claude でインストール この Prompt をコピーして Codex、Claude、または他のアシスタントに貼り付けると、Skill ページを確認してインストールできます。
直接コマンドでは確認用 Prompt が省略されます。実行前にソースを確認してください。
npx skills add https://github.com/ChonSong/skill-retriever --skill tree-ring-memoryコマンドは1行のまま表示されます。コピー前に横へスクロールして全体を確認してください。
ローカルで確認しますか？SkillsMP が現在取得できるファイルをダウンロードできます。
AI-powered Draw.io diagram generation with real-time browser preview. Create flowcharts, architecture diagrams, sequence diagrams, and cloud infrastructure diagrams (AWS/GCP/Azure) using natural language. Supports animated connectors, real-time editing, and structured A–H format extraction from text or images.
Multi-agent autonomous startup system for Claude Code. Triggers on "Loki Mode". Orchestrates 100+ specialized agents across engineering, QA, DevOps, security, data/ML, business operations, marketing, HR, and customer success. Takes PRD to fully deployed, revenue-generating product with zero human intervention. Features Task tool for subagent dispatch, parallel code review with 3 specialized reviewers, severity-based issue triage, distributed task queue with dead letter handling, automatic deployment to cloud providers, A/B testing, customer feedback loops, incident response, circuit breakers, and self-healing. Handles rate limits via distributed state checkpoints and auto-resume with exponential backoff. Requires --dangerously-skip-permissions flag.
When the user wants to plan, design, or implement an A/B test or experiment, or build a growth experimentation program. Also use when the user mentions "A/B test," "split test," "experiment," "test this change," "variant copy," "multivariate test," "hypothesis," "should I test this,"...
SOC 職業分類に基づく
SKILL.md を表示中
| name | tree-ring-memory |
| description | Use Tree Ring Memory for local-first AI-agent memory lifecycle work: recall, evidence, audit, forgetting, and consolidation without transcript dumping. |
| category | development |
| risk | safe |
| source | community |
| source_repo | TerminallyLazy/Tree-Ring-Memory |
| source_type | community |
| date_added | 2026-07-08 |
| author | TerminallyLazy |
| tags | ["agent-memory","local-first","recall","privacy","codex","sqlite","cli"] |
| tools | ["claude","codex","cursor","gemini","antigravity","opencode"] |
| license | Apache-2.0 |
| license_source | https://github.com/TerminallyLazy/Tree-Ring-Memory/blob/main/LICENSE |
Tree Ring Memory is a framework-agnostic, local-first memory lifecycle layer for AI agents. Use this skill when an agent should recall, preserve, audit, or forget durable project memory without treating raw conversation transcripts as memory.
The public runtime is a Rust CLI/TUI with local SQLite/FTS storage, scoped recall, evidence records, audit, deterministic consolidation, maintenance, DOX/Revolve source adapters, framework discovery, redaction, and explicit forgetting.
.tree-ring/SKILL.md, .tree-ring/CLI.md, or
other Tree Ring bridge files.Check whether the current project already has Tree Ring guidance:
test -f .tree-ring/SKILL.md && sed -n '1,220p' .tree-ring/SKILL.md
test -f .tree-ring/CLI.md && sed -n '1,220p' .tree-ring/CLI.md
Treat project-local .tree-ring files as more authoritative than generic
examples in this skill. If the CLI is installed, inspect the current command
surface before assuming flags:
tree-ring --help
tree-ring recall --help
tree-ring remember --help
tree-ring evidence --help
tree-ring audit --help
tree-ring forget --help
If Tree Ring is not installed, do not run remote installer commands automatically. Point the user to the project repository or install docs and ask whether they want installation help.
Use narrow, project-scoped recall first:
tree-ring recall "release behavior" --scope project
tree-ring recall "sqlite migration" --scope project
tree-ring recall --scope global
Use recalled memory as context, not authority. Verify it against current source files, tests, docs, issues, pull requests, logs, and runtime state before making changes.
Write concise memory only when it is likely to help future agents:
tree-ring remember "Run project-scoped recall before release changes." --event-type lesson --scope project
Prefer specific event types when supported locally:
decisionlessonwarningcorrectionuser_preferencetool_resultsummaryhypothesisStore the durable lesson, decision, warning, or follow-up. Do not store the full conversation.
Use evidence records for test runs, incidents, reviewed changes, or other evaluated outcomes:
tree-ring evidence \
--outcome observed \
--summary "Installer smoke test passed in an isolated HOME." \
--evidence-ref "ci/install-smoke/2026-07-08"
Outcome guidance:
promoted: durable truth backed by strong evidencerejected: failed or rolled-back approach worth keeping visibledeferred: unresolved idea or future optionobserved: normal evaluated resultDo not promote weak, stale, or unreviewed claims to durable truth.
When a repo has structured source records, run dry runs first:
tree-ring dox sync --source-root . --dry-run
tree-ring revolve sync --source-root revolve --dry-run
tree-ring integrations scan --source-root .
Only write adapter summaries when they are concise, source-linked, useful, and
privacy-safe. Imported memory does not replace the underlying AGENTS.md,
Revolve record, test, pull request, issue, or documentation.
Use the smallest durable ring that fits:
cambium: active or recent task contextouter: recent decisions and task lessonsinner: older compressed project knowledgeheartwood: durable high-confidence truthsscar: failures, regressions, rejected approaches, warningsseed: unresolved ideas, hypotheses, follow-upsPrefer outer or seed unless the user confirms durability or the evidence is
strong.
--help, not as
guaranteed command surfaces..tree-ring
guidance and tree-ring --help over copied command examples.Problem: Recalled memory conflicts with current source. Solution: Treat source files, tests, docs, and runtime evidence as authoritative; supersede or forget stale memory.
Problem: Memory starts becoming transcript storage. Solution: Store only durable decisions, warnings, preferences, outcomes, and follow-ups.
Problem: A lesson is useful but contains sensitive detail. Solution: Store a redacted summary or do not store it.
@agent-memory-systems - Use for broad agent-memory architecture choices.@agent-memory - Use for the listed hybrid memory MCP system.@planning-with-files - Use when simple persistent files are enough.