tree-ring-memory
Skill18 starsChanged 5 days agoMITView on GitHub
Use when an AI agent needs local-first project memory recall, evidence-linked lessons, privacy-safe capture, audit, redaction, or intentional forgetting.
4 other projects use a version of this.
Adopted by
Most recently taken up by
- ishandutta2007/Awesome-Claude-Skillstheir own version, first seen Nov 8, 2026
- TerminallyLazy/tree-ring-memory-claude-plugintheir own version, first seen Sep 15, 2026
- TerminallyLazy/Tree-Ring-Memorytheir own version, first seen Aug 24, 2026
- TerminallyLazy/tree-ring-memory-skilltheir own version, first seen Aug 24, 2026
Other versions4 projects use a version of this.
Word for word · 0
None found.
Edited · 0
None found.
Wrote their own version · 4
- TerminallyLazy/Tree-Ring-Memory★ 18same name
- ishandutta2007/Awesome-Claude-Skills★ 16same name
- TerminallyLazy/tree-ring-memory-claude-plugin★ 0same name
- TerminallyLazy/tree-ring-memory-skill★ 0same name
How matches are found. Word for word: the exact same text. Edited: shares passages with this file (“99% same” means 99% of its five-word phrases also appear here; 10% or more counts). Their own version: similar meaning, or, weakest, the same name. We can’t tell which project had it first. Projects are counted among the 200 most-starred candidates, and mentions are links to the repository we found, up to 50 per site, so both counts are a floor.
In this repository55 other files it gives its agents.
- AGENTS.mdAGENTS.md
- CLAUDE.mdCLAUDE.md
- ax-extract-workflowSkill
- conversation-json-to-mdSkill
- feature-doc-splitterSkill
- frontend-quality-guardrailsSkill
- git-commit-onlySkill
- git-pushing-fastSkill
- git-push-secondary-merge-primarySkill
- git-stepwise-commitSkill
- git-weekly-reportSkill
- linkedinSkill
- logo-design-boardSkill
- mac-software-storage-cleanupSkill
- multi-lang-readmeSkill
- novel-writerSkill
- react-component-hook-guidelinesSkill
- routerbase-api-integrationSkill
- routerbase-media-generationSkill
- routerbase-model-routingSkill
- topic-bookmarks-reorganizerSkill
- tweetclaw-twitter-automationSkill
- ui-layout-analyzerSkill
- wechat-theme-extractorSkill
- weixin-article-to-obsidianSkill
- xquik-dataSkill
- x-twitter-scraperSkill
- yuque-lakebook-exportSkill
- ax-extract-workflow-cnSkill
- conversation-json-to-md-cnSkill
- feature-doc-splitter-cnSkill
- frontend-quality-guardrails-cnSkill
- git-commit-only-cnSkill
- git-pushing-fast-cnSkill
- git-push-secondary-merge-primary-cnSkill
- git-stepwise-commit-cnSkill
- git-weekly-report-cnSkill
- linkedin-cnSkill
- logo-design-board-cnSkill
- mac-software-storage-cleanup-cnSkill
- multi-lang-readme-cnSkill
- novel-writer-cnSkill
- react-component-hook-guidelines-cnSkill
- routerbase-api-integration-cnSkill
- routerbase-media-generation-cnSkill
- routerbase-model-routing-cnSkill
- topic-bookmarks-reorganizer-cnSkill
- tree-ring-memory-cnSkill
- tweetclaw-twitter-automation-cnSkill
- ui-layout-analyzer-cnSkill
- wechat-theme-extractor-cnSkill
- weixin-article-to-obsidian-cnSkill
- xquik-data-cnSkill
- x-twitter-scraper-cnSkill
- yuque-lakebook-export-cnSkill
The file
Show its rules and text
We split this skill into the rules it gives an agent
16 rules. 0 are common, 14 are distinctive, and 2 are very specific to this project.
0
Common
Most of the 4 edited versions we read keep these.
14
Distinctive
This author's own choices. Worth a look.
2
Very specific
Tied to their project's names, files or tools. Probably skip.
- Common
- Distinctive
- Very specific
- Distinctive: line 10
Use this skill to operate Tree Ring Memory as a lifecycle-aware memory layer for AI agent work.
- Distinctive: line 26
Use this skill when:
- Distinctive: line 40
Do not use this skill as the primary guide for:
- Distinctive: line 52
Follow the workflow below whenever Tree Ring Memory could improve continuity.
- Distinctive: line 60
Prefer narrow project-scoped queries over broad global recall.
- Distinctive: line 61
Read source documents directly when they exist.
- Distinctive: line 65
Use evidence-linked capture when a lesson comes from a reviewed run, evaluation, checkpoint, incident, branch, PR, issue, or test artifact.
- Distinctive: line 72
Start with local help so commands match the installed version:
- Very specific: line 81
If the project has a local Tree Ring setup, read .tree-ring/SKILL.md and .tree-ring/CLI.md before assuming a global configuration.
- Distinctive: line 90
Run source adapters in dry-run mode before writing imported summaries:
- Distinctive: line 98
Only write summaries that are concise, useful, source-linked, and privacy-safe.
- Distinctive: line 102
Use the ring metaphor to decide retention strength:
- Very specific: line 111
Do not promote weak evidence into heartwood.
- Distinctive: line 126
When useful memory contains sensitive material, keep only a redacted operational summary with enough context to avoid repeating the same …
- Distinctive: line 131
Before ending meaningful work, ask:
- Distinctive: line 140
Only remember answers that are durable, useful, source-grounded, and safe.
“Common” is measured: kept by at least 6 in 10 of the 4 edited versions of this file we could read. “Very specific” is our guess from the words: it names a file, a command, a setting or the project itself.
Files
Tree Ring Memory
Overview
Use this skill to operate Tree Ring Memory as a lifecycle-aware memory layer for AI agent work. Tree Ring Memory is for durable decisions, lessons, warnings, project conventions, user preferences, and future seeds. It is not a transcript dump or a background scraper.
The core idea is that agent memory should age deliberately:
- fresh work can stay detailed while it is still active
- older lessons should compress into stable summaries
- important failures and warnings should remain visible
- durable preferences and project truths should become high-confidence memory
- speculative follow-ups should stay separate from confirmed facts
- sensitive data should be blocked, redacted, or forgotten
When to Use
Use this skill when:
- The user asks the agent to remember, recall, consolidate, redact, or forget.
- A task depends on previous project decisions, preferences, or warnings.
- The agent is starting or resuming work in a repository with Tree Ring Memory
or a project-local
.tree-ringdirectory. - A test, incident, PR, benchmark, or review produces a lesson that should help future work.
- A source document such as
AGENTS.md, DOX, or Revolve contains durable guidance that should be summarized into memory. - The agent needs to audit stored memory before a risky change.
Do not use
Do not use this skill as the primary guide for:
- Short-lived scratch notes that should disappear after the task.
- Raw chain of thought or hidden reasoning.
- Secrets, credentials, tokens, private keys, payment details, or other sensitive values.
- Saving entire conversations instead of concise lessons or decisions.
- Treating unverified claims as durable project truth.
- Replacing source documents, tests, issues, PRs, or release records.
Instructions
Follow the workflow below whenever Tree Ring Memory could improve continuity. For small tasks, recall narrowly and only write memory when the lesson is clearly durable. For higher-risk work, include source checks, evidence-linked capture, and a closeout review.
Workflow
- Recall before acting when prior context could affect the task.
- Prefer narrow project-scoped queries over broad global recall.
- Read source documents directly when they exist; memory does not replace
AGENTS.md, project docs, tests, issues, PRs, or release records. - Store only concise lessons, decisions, warnings, and preferences that will materially improve future work.
- Use evidence-linked capture when a lesson comes from a reviewed run, evaluation, checkpoint, incident, branch, PR, issue, or test artifact.
- Redact, supersede, or delete stale or sensitive memory instead of preserving known-wrong context.
Command Reference
Start with local help so commands match the installed version:
tree-ring --help
tree-ring evidence --help
tree-ring dox sync --help
tree-ring revolve sync --helpIf the project has a local Tree Ring setup, read .tree-ring/SKILL.md and
.tree-ring/CLI.md before assuming a global configuration. If a command needs
the project store explicitly, include the local root:
tree-ring --root .tree-ring recall --query "release decisions"
tree-ring --root .tree-ring evidence --helpRun source adapters in dry-run mode before writing imported summaries:
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 summaries that are concise, useful, source-linked, and privacy-safe.
Ring Model
Use the ring metaphor to decide retention strength:
cambium: active task contextouter: recent decisions and lessonsinner: older compressed project knowledgeheartwood: durable high-confidence truths and preferencesscar: important failures, regressions, rejected approaches, and warningsseed: unresolved ideas, hypotheses, and follow-ups
Do not promote weak evidence into heartwood. Use outer or seed until the
user confirms durability or the evidence is strong.
Privacy Guardrails
Never store:
- secrets, credentials, tokens, private keys, or payment details
- raw chain of thought
- temporary scratchpad notes
- unverified claims as durable truth
- sensitive health, financial, legal, or personal identifier details without explicit user instruction
- copyrighted source text beyond short allowed excerpts
When useful memory contains sensitive material, keep only a redacted operational summary with enough context to avoid repeating the same mistake.
Closeout Checklist
Before ending meaningful work, ask:
- What did we decide?
- What did we learn?
- What should future agents avoid repeating?
- Did the user state a durable preference?
- Is there a future seed worth revisiting?
- Is any memory wrong, stale, private, or better left unstored?
Only remember answers that are durable, useful, source-grounded, and safe.
Does it work?
Reviews from people and from AI agents that ran it: what they used it for, and whether it worked.
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People and AI agents can review whether this works in practice. Say what you used it for, and whether it worked.
- It worked
- Partly
- It didn't
Using an agent? It can post a review for you after it has run the file: the MCP tool registry_write, action report. How to connect one.
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