Agent skill

Tree Ring Memory

by sickn33 in sickn33/agentic-awesome-skills

Use Tree Ring Memory for local-first AI-agent memory lifecycle work: recall, evidence, audit, forgetting, and consolidation without transcript dumping.

MITAuto-check passedAgent Workflows

Install Tree Ring Memory

skills CLI
$ npx skills add sickn33/agentic-awesome-skills --skill tree-ring-memory -a claude-code

Project install by default; add -g for ~/.claude/skills/.

GitHub CLI
$ gh skill install sickn33/agentic-awesome-skills tree-ring-memory --agent claude-code

Project scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).

Manual copy
$ git clone --depth 1 https://github.com/sickn33/agentic-awesome-skills.git skills-src && mkdir -p .claude/skills && cp -r skills-src/skills/tree-ring-memory .claude/skills/tree-ring-memory && rm -rf skills-src

Use ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.

Claude Code skills documentation · loads skills from .claude/skills/

Facts

Skill name
tree-ring-memory
GitHub stars
47k
Used in
1 other repo
Token cost
~2.2k tokens
SKILL.md length
917 words
Files
1
Skills in repo
1,394
Repo updated
First seen
Licence
MIT

At a glance

Use Tree Ring Memory for local-first AI-agent memory lifecycle work: recall, evidence, audit, forgetting, and consolidation without transcript dumping.

  • Tasks that involve Agent memory
  • SKILL.md covers Overview, When to Use This Skill, How It Works and Step 2: Recall Before Risky Work, plus 10 more sections
  • Calls sh; reaches raw.githubusercontent.com

What it does

Tree Ring Memory is an agent skill from sickn33/agentic-awesome-skills. Use Tree Ring Memory for local-first AI-agent memory lifecycle work: recall, evidence, audit, forgetting, and consolidation without transcript dumping.

Its SKILL.md is about 2.2k tokens, which your agent loads only when the skill is triggered. It is a single SKILL.md file with no bundled scripts.

It sits in Agent Workflows, covering Agent memory. The repository describes itself as: AAS Core is the local, agent-first control plane for complete catalog discovery, agent-owned selection, stack validation, and planning, backed by 2,400+ agentic skills. Includes… The licence is MIT.

When your agent uses it

  • Tasks that involve Agent memory

Example prompts

  • “/tree-ring-memory”

What it can do on your machine

Read from SKILL.md and the folder at commit 1e53ce2. It shows what the files ask for, not the result of running them.

  • Tool permissions

    Pre-approves nothing: there is no allowed-tools line, so your agent's usual permission prompts apply.

    From allowed-tools in the SKILL.md frontmatter.

  • Runs code

    Shell commands in SKILL.md call:

    • sh

    From the folder's file list and the shell code blocks in SKILL.md.

  • Network

    Hosts in commands or code, which the agent is likely to contact:

    • raw.githubusercontent.com

    Also links to:

    • github.com

    From URLs in SKILL.md, links to its own repository left out.

  • Credentials

    Names no API keys, tokens, secrets or passwords.

    From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.

Context cost

Tree Ring Memory loads about 2.2k tokens when it runs. Until then it costs about 42 tokens; SKILL.md has 917 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~42
When it runs · the whole SKILL.md, loaded when a task matches
~2.2k

Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.

Safety

Auto-check passed

The automated check found no risky patterns in SKILL.md.

Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); files beside SKILL.md are not scanned.

SKILL.md

The full file from sickn33/agentic-awesome-skills at commit 1e53ce2, republished under its MIT licence (© sickn33). 917 words, ~2,170 tokens.

Download SKILL.mdSave it as .claude/skills/tree-ring-memory/SKILL.md (or your agent's skills folder).
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
critical
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
MIT

Tree Ring Memory

Overview

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.

When to Use This Skill

  • Use before resuming a project where prior decisions, warnings, preferences, or failed approaches may matter.
  • Use before changing architecture, storage, security, privacy, release, or agent-memory behavior.
  • Use when the user asks to remember, recall, audit, redact, forget, or consolidate agent memory.
  • Use after tests, reviews, incidents, or production behavior validate a lesson future agents should preserve.
  • Use when a project contains .tree-ring/SKILL.md, .tree-ring/CLI.md, or other Tree Ring bridge files.

How It Works

Step 1: Discover Local Guidance

Check whether the current project already has Tree Ring guidance:

bash
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:

bash
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, resolve the actual project root and explain the exact project-local download before obtaining explicit approval to fetch it. Download the official, version-pinned v0.15.0/install.sh to a temporary file, verify its SHA-256 is ef0d5eb8f09cbe2e4c3abe80ee9a98a56759c89ad4ddd103d6c68314cd653ade, inspect it, then run it. The pinned source is https://raw.githubusercontent.com/TerminallyLazy/Tree-Ring-Memory/v0.15.0/install.sh.

bash
cd <project-root>
sh <verified-installer-path> --project --init --release v0.15.0 --no-animation

Do not pipe a network response directly to a shell. After verification and inspection, show the exact installer command and obtain explicit approval again before executing it. For an installed global CLI, initialize from the project root with tree-ring --root .tree-ring init; for a project-local CLI, use .tree-ring/bin/tree-ring --root .tree-ring init.

Check for a newer release without changing files using tree-ring update --check. Run tree-ring update only with user authorization, then rerun init in each project root to refresh managed guidance while preserving custom content.

Step 2: Recall Before Risky Work

Use narrow, project-scoped recall first:

bash
tree-ring recall "release behavior" --project example-service
tree-ring recall "sqlite migration" --project example-service
tree-ring recall "user preference"

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.

Step 3: Write Only Durable Memory

Write concise memory only when it is likely to help future agents:

bash
tree-ring remember "Run project-scoped recall before release changes." --event-type lesson --scope project

Prefer specific event types when supported locally:

  • decision
  • lesson
  • warning
  • correction
  • user_preference
  • tool_result
  • summary
  • hypothesis

Store the durable lesson, decision, warning, or follow-up. Do not store the full conversation.

Step 4: Record Evidence for Evaluated Outcomes

Use evidence records for test runs, incidents, reviewed changes, or other evaluated outcomes:

bash
tree-ring evidence \
  "Installer smoke test passed in an isolated HOME." \
  --outcome observed \
  --evidence-ref "ci/install-smoke/2026-07-08"

Outcome guidance:

  • promoted: durable truth backed by strong evidence
  • rejected: failed or rolled-back approach worth keeping visible
  • deferred: unresolved idea or future option
  • observed: normal evaluated result

Do not promote weak, stale, or unreviewed claims to durable truth.

Step 5: Use Source Adapters Carefully

When a repo has structured source records, run dry runs first:

bash
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.

Ring Selection

Use the smallest durable ring that fits:

  • cambium: active or recent task context
  • outer: recent decisions and task lessons
  • inner: older compressed project knowledge
  • heartwood: durable high-confidence truths
  • scar: failures, regressions, rejected approaches, warnings
  • seed: unresolved ideas, hypotheses, follow-ups

Prefer outer or seed unless the user confirms durability or the evidence is strong.

Show full SKILL.md (358 more words)Show less

Best Practices

  • Recall before risky or repeat work.
  • Keep project memory project-scoped unless it is a durable cross-project user preference.
  • Attach source references such as file paths, issue ids, PR ids, evaluation runs, or docs paths.
  • Re-check current source files and runtime state before acting on recalled memory.
  • Ask at closeout what future agents should remember, avoid, or revisit.
  • Use redaction, deletion, or supersession when memory is wrong, stale, sensitive, or replaced by a newer decision.

Security & Safety Notes

  • Never use Tree Ring Memory as a hidden recorder.
  • Do not store secrets, credentials, tokens, private keys, recovery codes, raw chain-of-thought, or temporary scratchpad content.
  • Do not store sensitive personal data unless the user explicitly asks and the retention boundary is safe.
  • Do not store copyrighted source text beyond short allowed excerpts.
  • Do not run installer, network, destructive, or mutation commands without explicit user approval and a clear target environment.
  • Treat all examples as commands to adapt after checking local --help, not as guaranteed command surfaces.

Limitations

  • Tree Ring Memory is not a replacement for source control, issue trackers, documentation, tests, logs, or live runtime verification.
  • Recalled memory can be stale or wrong. Always verify important claims against the current project before using them to make changes.
  • The CLI surface can change across releases. Prefer local .tree-ring guidance and tree-ring --help over copied command examples.
  • It should not be used for secret storage, comprehensive transcript archives, compliance retention, or unreviewed collection of sensitive personal data.
  • Cross-agent interoperability depends on each tool's ability to call the local CLI or read project-local guidance files.

Common Pitfalls

  • 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.

Additional Resources

© sickn33, MIT. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file

Files

Just SKILL.md in skills/tree-ring-memory of sickn33/agentic-awesome-skills.

Open the folder on GitHubat commit 1e53ce2

Used in 1 other repository

We found 5 copies of this SKILL.md (exact, near-identical or edited) in other folders, from 1 other GitHub owner. This page covers the copy in sickn33/agentic-awesome-skills, which our catalogue first saw on October 7, 2026.

Compare with similar skills

Tree Ring Memory next to the 5 skills that share the most tags, products or categories with it. Stars are the repository's; “used in” counts other GitHub owners with a copy.

Tree Ring Memory compared with similar skills
SkillStarsUsed inTokensAuto-checkLicenceRepo updated
Tree Ring Memory this skillsickn33/agentic-awesome-skills47k1 repos~2.2kAutomated safety check: PassMIT
Project Timeline Reportthedotmack/claude-mem97k1 repos~3.1kAutomated safety check: PassApache-2.0
Neat-Freak Knowledge CloseoutKKKKhazix/khazix-skills21k—~1.9kAutomated safety check: PassMIT
Beads Task Memorygastownhall/beads28k—~1.2kAutomated safety check: PassMIT
MemPalace Memory SearchMemPalace/mempalace59k—~1.4kAutomated safety check: PassMIT
Reflect on Session Learningscursor/plugins10k5 repos~1.2kAutomated safety check: PassNone

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Categories

Questions about Tree Ring Memory

What does Tree Ring Memory do?

Use Tree Ring Memory for local-first AI-agent memory lifecycle work: recall, evidence, audit, forgetting, and consolidation without transcript dumping. Tree Ring Memory is an agent skill from sickn33/agentic-awesome-skills. Use Tree Ring Memory for local-first AI-agent memory lifecycle work: recall, evidence, audit, forgetting, and consolidation without transcript dumping.

When should I use Tree Ring Memory?

Tree Ring Memory fits situations like: tasks that involve Agent memory.

How do I install Tree Ring Memory in Claude Code?

Run `npx skills add sickn33/agentic-awesome-skills --skill tree-ring-memory -a claude-code`. Or copy the skill folder (skills/tree-ring-memory in sickn33/agentic-awesome-skills) into .claude/skills/tree-ring-memory in your project. Claude Code loads it when a task matches its description.

How do I install Tree Ring Memory in Codex?

Run `npx skills add sickn33/agentic-awesome-skills --skill tree-ring-memory -a codex`. Or copy the skill folder (skills/tree-ring-memory in sickn33/agentic-awesome-skills) into .agents/skills/tree-ring-memory in your project. Codex loads it when a task matches its description.

Can I use Tree Ring Memory in Cursor, Gemini CLI or GitHub Copilot?

Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add sickn33/agentic-awesome-skills --skill tree-ring-memory -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/tree-ring-memory, .gemini/skills/tree-ring-memory, .github/skills/tree-ring-memory and .opencode/skills/tree-ring-memory in your project.

What does Tree Ring Memory need to run?

Going by SKILL.md and its folder, Tree Ring Memory needs the command-line tools its instructions call (sh).

Does Tree Ring Memory access the network?

SKILL.md names 2 domains. In commands or code: raw.githubusercontent.com; the agent is likely to contact it when it follows the instructions. As links in the text: github.com. This is read from the text; nothing was executed.

Is Tree Ring Memory safe to install?

Our automated static check of SKILL.md found no risky patterns, such as piping downloads into a shell, reading credential files or hidden Unicode. It is not a guarantee. Review the folder before installing.

What licence does Tree Ring Memory use?

Tree Ring Memory is published under the MIT licence (declared in SKILL.md). It allows redistribution, so the full SKILL.md is shown on this page.

How many tokens does Tree Ring Memory use?

About 2.2k tokens (SKILL.md is roughly 8.7k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full.

What are the alternatives to Tree Ring Memory?

Skills that share tags, products or a category with Tree Ring Memory: Project Timeline Report (thedotmack/claude-mem, 97k stars), Neat-Freak Knowledge Closeout (KKKKhazix/khazix-skills, 21k stars), Beads Task Memory (gastownhall/beads, 28k stars) and MemPalace Memory Search (MemPalace/mempalace, 59k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Tree Ring Memory?

sickn33 (a GitHub user) maintains it in sickn33/agentic-awesome-skills, which has 47,304 GitHub stars. The repository holds 1,394 skills in this directory. The repository was last updated on October 6, 2026.

Source: sickn33/agentic-awesome-skills on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.