Agent skill

Compound Learnings Refresh

by EveryInc in EveryInc/compound-engineering-plugin

Audits a repo's stored learnings against the current codebase, fixes stale, overlapping or superseded docs and reports on every document.

MITAuto-check passedAgent Workflows

Install Compound Learnings Refresh

skills CLI
$ npx skills add EveryInc/compound-engineering-plugin --skill ce-compound-refresh -a claude-code

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

GitHub CLI
$ gh skill install EveryInc/compound-engineering-plugin ce-compound-refresh --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/EveryInc/compound-engineering-plugin.git skills-src && mkdir -p .claude/skills && cp -r skills-src/skills/ce-compound-refresh .claude/skills/ce-compound-refresh && 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
ce-compound-refresh
GitHub stars
25k
Token cost
~2k tokens
SKILL.md length
999 words
Files
16 (incl. scripts, references, assets)
Skills in repo
37
Repo updated
First seen
Licence
MIT

At a glance

Audits a repo's stored learnings against the current codebase, fixes stale, overlapping or superseded docs and reports on every document.

  • Auditing stored learnings for stale, overlapping or superseded entries
  • SKILL.md covers Mode, Worth lens, Artifact Root and Scope, plus 7 more sections
  • Runs Python scripts from its folder; calls git
  • Checking whether documented solutions still match the current codebase

What it does

The skill audits the learnings kept in the solutions folder of the repo's artifact root, checks them against the current code, applies the maintenance actions the evidence supports, and delivers a per-document report along with committed changes. The report and the corrected document set are the deliverables. The agent reads a modes reference first, which sets what each mode may do unattended, how questions are asked and a stale-marking fallback.

The normal refresh judges accuracy: whether each doc is still true and still distinct, and it never deletes an accurate doc just because the repo states the idea elsewhere. A second pass on worth, which can delete accurate docs the codebase already explains, runs only when you ask to clean up or trim the store and then confirm a choice between that and a drift-only fix. Failed writes are recorded as recommendations and the run continues.

Reference files cover classification, investigation, scope, reporting and committing, and two Python scripts validate frontmatter and documentation claims. Subagents receive the resolved solutions path and are spawned without a mode override, so your permission settings apply.

When your agent uses it

  • Auditing stored learnings for stale, overlapping or superseded entries
  • Checking whether documented solutions still match the current codebase
  • Pruning a learnings folder after confirming that deletion is wanted

Example prompts

  • “Refresh our learnings folder against the current code and report what drifted.”
  • “Find solution docs that overlap or were superseded, then merge or mark them.”
  • “Clean up the learnings store and delete docs the codebase already explains, but ask me first.”

Requirements

  • A repository with a compound-engineering learnings folder
  • Python, for the two validation scripts

What it can do on your machine

Read from SKILL.md and the folder at commit cef001f. 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

    Ships 2 files in scripts/ (Python), which the agent can run.

    Shell commands in SKILL.md call:

    • git

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

  • Network

    No URLs in SKILL.md. Its commands use git, which can reach the network depending on how they are called.

    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

Compound Learnings Refresh loads about 2k tokens when it runs, and up to ~20k if it reads all its reference files. Until then it costs about 62 tokens; SKILL.md has 999 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~62
When it runs · the whole SKILL.md, loaded when a task matches
~2k
With references · SKILL.md plus every file in references/, read only if the agent opens them
~20k

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); the scripts in this folder are not scanned.

SKILL.md

The full file from EveryInc/compound-engineering-plugin at commit cef001f, republished under its MIT licence (© EveryInc). 999 words, ~1,970 tokens.

Download SKILL.mdSave it as .claude/skills/ce-compound-refresh/SKILL.md (or your agent's skills folder). This skill also uses 15 other files; get the full folder from GitHub.
name
ce-compound-refresh
description
Refresh the repo's captured learnings against the current codebase. Use when auditing stale, overlapping, superseded, or drifted learnings; avoid general refactor, debugging, or code review unless the learnings store is explicit.
argument-hint
[optional: scope hint — directory, filename, module, or keyword] [mode:non-interactive]

Compound Refresh

Audit the learnings under <root>/solutions/ against the current codebase, apply the maintenance actions the evidence supports, and deliver a complete per-doc report plus committed changes. The report and the corrected document set are the deliverables. The store only compounds value if every doc can be trusted.

Mode

Read references/modes.md now. It reads the mode off the arguments and defines what each mode may apply unattended, the stale-marking fallback, the question tools, and the CONCEPTS.md bootstrap.

Two rules hold in both modes. A failed write is recorded as recommended, and the run continues. And a question is asked through the host's blocking tool, or through the numbered-options fallback that reference defines. It is never silently skipped.

Worth lens

The ordinary refresh judges accuracy: is each doc still true and still distinct. It never deletes an accurate doc for holding knowledge the repo states elsewhere. That second judgment, worth, runs only when the user asked for it and confirmed it. It reads the whole scope against the codebase and can delete accurate docs.

Read the invocation arguments for that intent: the user wants the store cleaned up, culled, pruned, trimmed, upgraded, or brought to the capture bar, in any wording, rather than checked for drift. When the intent is present, state the reading back and confirm before any investigation:

text
You asked to clean up the learnings. Which do you want?
1. Delete or shorten docs the codebase already explains. A doc goes when a test, a code comment, or the instructions file states the same reasoning, and every cut quotes that file. Drift is fixed too. Scope: <scope>.
2. Fix drift only. Stale paths and links, duplicate docs, and guidance the code no longer supports. Nothing accurate is deleted.

On option 1, read references/worth-audit.md before Investigate; it adds the bar, the evidence rule, and the routing. On option 2, or when the intent is absent, do not read that reference and do not apply its test; the accuracy refresh is the whole run. Non-interactive mode cannot confirm, so references/modes.md states what an inferred intent does there.

Artifact Root

Resolve <root> when you first compose a <root>/solutions/ path. Pass the resolved <root>/solutions/ path to any subagent, not the config. Every subagent spawn omits the mode parameter, so the user's permission settings apply.

<!-- ce-docs-root:start -->

Resolve the CE artifact root <root> before composing any artifact path.

  • Read docs_root from <repo-root>/.compound-engineering/config.yaml only (<repo-root> = git rev-parse --show-toplevel). Do not read it from config.local.yaml. Unset -> <root> is docs, exactly as before.
  • Validate a set value: a repo-relative directory whose real, symlink-resolved path stays inside the repo and is neither the repo root nor under .git/. Otherwise stop with an error naming docs_root and the value -- never fall back to docs.
  • Use <root> as the sole artifact location: create it if absent, compose each path as <root>/<subdir> with this skill's own subdirectory, and never also read docs.
<!-- ce-docs-root:end -->

Scope

Candidates are the .md files under <root>/solutions/, excluding README.md and anything under _archived/. A hint that matches nothing never widens the scope. Read references/scope.md for the narrowing strategy, what each mode does on a miss, the empty-store message, triage order, and the README-row cleanup each action carries.

Investigate

Read references/investigate.md for the staleness dimensions, auto-memory rules, subagent roles, and category-shape notes.

Check each learning against the current codebase, then check the set for overlap, supersession, and contradiction. A contradiction misleads actively, so it outranks individual staleness.

A knowledge-track learning sometimes points at a guidance file it names or links, such as a skill's SKILL.md, a runbook, or an instruction file. Compare only guidance the learning names. Never search the guidance layer for one.

Every investigation subagent's prompt carries that reference's three Subagent prompt clauses verbatim. Two are search tools and auto-memory. The third is this:

If the learning is knowledge-track and names or links a guidance file (a skill's SKILL.md, a runbook, a root instruction file), read that file and, when it states a different order or a contradictory rule for the same procedure, return both conflicting quotes plus which side current code follows — or that code witnesses neither. Read only guidance the learning names; do not search for one, and do not edit it.

Show full SKILL.md (374 more words)Show less

Classify

Every doc gets exactly one outcome: Keep, Update, Consolidate, Replace, or Delete. A doc is never archived in place: there is no _archived/, since version history is the archive.

Read references/classify.md before assigning any of them. It defines each outcome's meaning, the Update/Replace boundary, the auto-delete rule and its pre-checks, the relocation and split rules, the retrieval-value test, unverifiable-is-not-false, pattern docs, and what interactive mode asks.

Two boundaries hold whatever the evidence says. This skill never changes product code. A claim about current mechanics follows current code, but independently supported guidance does not become false merely because implementation stopped satisfying it: classify the doc from the guidance evidence and report the implementation conflict as a potential product regression. And when a learning contradicts guidance, the refresh reports that; it must never edit a skill, runbook, or instruction file.

Execute

Read references/per-action-flows.md and follow the section matching each doc's classification, one flow per doc. It defines the criteria, the relocation and split procedures, the replacement subagent contract, and citation cleanup.

Vocabulary Capture

After the per-doc actions, reconcile the domain terms flagged during investigation with CONCEPTS.md. Read references/concepts-vocabulary.md unconditionally. Its qualifying criteria are non-obvious, so a "nothing qualifies" judgment reached without reading it is a shortcut, not a result.

Edits apply silently in every mode. The report's CONCEPTS.md line records what the scan found, including "scanned, no qualifying terms".

Report

Print the full report as markdown. It is the deliverable, not an internal summary, and in non-interactive mode it is the only one. Keep it self-contained and never abbreviated, split into Applied and Recommended. Read references/report.md for the summary block, per-file detail, and what belongs under Recommended.

Commit

Skip if nothing changed. Otherwise stage only the files this refresh modified, and commit in the repo's convention. Read references/commit.md for the per-mode branch decision and the git-failure fallback.

Discoverability Check

After the report, check that the project's instructions would lead an agent to <root>/solutions/ before working in a documented area. Do this every time: the store only compounds value when agents can find it. Read references/discoverability.md for what the reader must learn, the smallest-addition rule and its tone, the CONCEPTS.md variant, consent versus a report line per mode, and folding a late edit into the commit.

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

Files

SKILL.md and 15 other files (scripts, references, assets) in skills/ce-compound-refresh of EveryInc/compound-engineering-plugin.

  • SKILL.md
  • assets/resolution-template.md
  • references/classify.md
  • references/commit.md
  • references/concepts-vocabulary.md
  • references/discoverability.md
  • references/investigate.md
  • references/modes.md
  • references/per-action-flows.md
  • references/report.md
  • references/schema.yaml
  • references/scope.md
  • references/worth-audit.md
  • references/yaml-schema.md
  • scripts/validate-doc-claims.py
  • scripts/validate-frontmatter.py

Open the folder on GitHubat commit cef001f

Compare with similar skills

Compound Learnings Refresh 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.

Compound Learnings Refresh compared with similar skills
SkillStarsUsed inTokensAuto-checkLicenceRepo updated
Compound Learnings Refresh this skillEveryInc/compound-engineering-plugin25k—~2kAutomated safety check: PassMIT
Neat-Freak Knowledge CloseoutKKKKhazix/khazix-skills21k—~1.9kAutomated safety check: PassMIT
Capture Knowledgeadamayoung/TMDb178—~2.3kAutomated safety check: PassApache-2.0
Project Timeline Reportthedotmack/claude-mem97k1 repos~3.1kAutomated safety check: PassApache-2.0
Beads Task Memorygastownhall/beads28k—~1.2kAutomated safety check: PassMIT
Dsh Web Documentationzhu1090093659/dsh-web8.4k—~479Automated safety check: PassApache-2.0

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Questions about Compound Learnings Refresh

What does Compound Learnings Refresh do?

Audits a repo's stored learnings against the current codebase, fixes stale, overlapping or superseded docs and reports on every document. The skill audits the learnings kept in the solutions folder of the repo's artifact root, checks them against the current code, applies the maintenance actions the evidence supports, and delivers a per-document report along with committed changes. The report and the corrected document set are the deliverables.

When should I use Compound Learnings Refresh?

Compound Learnings Refresh fits situations like: auditing stored learnings for stale, overlapping or superseded entries; checking whether documented solutions still match the current codebase; pruning a learnings folder after confirming that deletion is wanted.

How do I install Compound Learnings Refresh in Claude Code?

Run `npx skills add EveryInc/compound-engineering-plugin --skill ce-compound-refresh -a claude-code`. Or copy the skill folder (skills/ce-compound-refresh in EveryInc/compound-engineering-plugin) into .claude/skills/ce-compound-refresh in your project. Claude Code loads it when a task matches its description.

How do I install Compound Learnings Refresh in Codex?

Run `npx skills add EveryInc/compound-engineering-plugin --skill ce-compound-refresh -a codex`. Or copy the skill folder (skills/ce-compound-refresh in EveryInc/compound-engineering-plugin) into .agents/skills/ce-compound-refresh in your project. Codex loads it when a task matches its description.

Can I use Compound Learnings Refresh 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 EveryInc/compound-engineering-plugin --skill ce-compound-refresh -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/ce-compound-refresh, .gemini/skills/ce-compound-refresh, .github/skills/ce-compound-refresh and .opencode/skills/ce-compound-refresh in your project.

What does Compound Learnings Refresh need to run?

Going by SKILL.md and its folder, Compound Learnings Refresh needs Python for the scripts in its folder and the command-line tools its instructions call (git). Our summary lists: A repository with a compound-engineering learnings folder; Python, for the two validation scripts.

Does Compound Learnings Refresh access the network?

SKILL.md contains no URLs. Its commands use git, which can reach the network depending on how they are called. This is read from the text; nothing was executed.

Is Compound Learnings Refresh 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. The check reads SKILL.md only: the scripts in the folder are not scanned, so read them before running anything.

What licence does Compound Learnings Refresh use?

Compound Learnings Refresh is published under the MIT licence (the repository's licence). It allows redistribution, so the full SKILL.md is shown on this page.

How many tokens does Compound Learnings Refresh use?

About 2k tokens (SKILL.md is roughly 7.9k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full. Its references folder adds about 18k tokens, read only when the agent opens those files.

What are the alternatives to Compound Learnings Refresh?

Skills that share tags, products or a category with Compound Learnings Refresh: Neat-Freak Knowledge Closeout (KKKKhazix/khazix-skills, 21k stars), Capture Knowledge (adamayoung/TMDb, 178 stars), Project Timeline Report (thedotmack/claude-mem, 97k stars) and Beads Task Memory (gastownhall/beads, 28k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Compound Learnings Refresh?

EveryInc (a GitHub organization) maintains it in EveryInc/compound-engineering-plugin, which has 25,412 GitHub stars. The repository holds 37 skills in this directory. The repository was last updated on October 7, 2026.

Source: EveryInc/compound-engineering-plugin on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.