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LevNasLevNas/ccmemo/skills/review-knowledge/SKILL.md

review-knowledge

Skill4 starsChanged 5 months agoMITView on GitHub

Review and maintain the knowledge base — find stale entries, orphan entries without connections, missing links between related entries, and generate topic summaries. Supports the "internalization" phase of knowledge management by surfacing knowledge for periodic review and reflection.

2 other projects use a version of this.

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  • Other versions2 projects use a version of this.

    Word for word · 0

    None found.

    Edited · 0

    None found.

    Wrote their own version · 2

    1. shioki/Cursor-Knowledge-Management-System★ 1same name
    2. TOMOSIA-VIETNAM/agent-stack★ 1same 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 repository3 other files it gives its agents.

The file

We split this skill into the rules it gives an agent

2 rules. About 0 are common, 1 is distinctive, and 1 is very specific to this project.

  • ≈0

    Common · estimate

    Many files like this have a rule of this kind.

  • ≈1

    Distinctive · estimate

    This author's own choices. Worth a look.

  • 1

    Very specific

    Tied to their project's names, files or tools. Probably skip.

  • Common
  • Distinctive
  • Very specific
  1. Distinctive:

    When the user wants to understand the current state of knowledge on a topic

    line 19
  2. Very specific:

    No argument or "health" → health

    line 27

≈ “Common” is an estimate: at least 1 in 5 of the 350,495 skill files we read have a rule of the same kind, not the same words. “Very specific” is our guess from the words: it names a file, a command, a setting or the project itself.

Keep what fits and drop the rest. Your version, ready for your agents.
Files
SKILL.md

Review Knowledge

Goal

Maintain knowledge base health and surface entries for review, helping the user internalize accumulated knowledge through periodic reflection.

When to Use

  • User explicitly requests a knowledge review (e.g., "review knowledge", "check knowledge base")
  • At the end of a significant work phase or project milestone
  • When the user wants to understand the current state of knowledge on a topic
  • Periodically (e.g., weekly/monthly) to keep the knowledge base healthy

Execution

Delegate the review work to a Sonnet subagent to minimize main context consumption.

  1. Determine the review mode from user input:
    • No argument or "health" → health
    • topic:<keyword> → topic with the specified keyword
    • fix → fix
  2. Determine the knowledge base path (default: .claude/knowledge/entries/)
  3. Precompute deterministic graph facts from the MAIN agent's Bash (subagents run in a sandbox that blocks code execution, so these must run here):
python3 "{plugin_root}/scripts/kb_graph.py" --root .claude/knowledge/entries stats
python3 "{plugin_root}/scripts/kb_graph.py" --root .claude/knowledge/entries lint --json

Notes: pure stdlib, ~1s, no index needed. lint exiting 1 just means it found findings — capture stdout either way. If python3 is unavailable or the commands fail, set both outputs to (unavailable) and continue; the subagent then derives everything by reading files as before. 4. Spawn a subagent with the following configuration:

Agent(
  subagent_type: "general-purpose",
  model: "sonnet",
  description: "review knowledge base",
  prompt: |
    You are a knowledge base review agent. Read the procedure file and follow it precisely.

    ## Input
    ### mode
    {mode}

    ### topic_keyword (only for topic mode)
    {topic_keyword}

    ### current_date
    {current_date}

    ### graph_stats (deterministic, precomputed by kb_graph.py)
    {graph_stats}

    ### graph_lint (deterministic, precomputed by kb_graph.py)
    {graph_lint}

    ## Instructions
    1. Read the procedure file at: {plugin_root}/skills/review-knowledge/procedure.md
    2. Follow the procedure step by step for the specified mode
    3. The knowledge base is at: {project_root}/.claude/knowledge/
    4. Return the full review report in the output format specified in the procedure
)

Replace the placeholders:

  • {mode} — review mode: health, topic, or fix
  • {topic_keyword} — keyword or tag for topic mode (empty for other modes)
  • {current_date} — today's date in YYYY-MM-DD format (needed for stale entry detection)
  • {graph_stats} / {graph_lint} — stdout captured in step 3 ((unavailable) on failure)
  • {plugin_root} — the plugin's installation path (shown in the skill loading message as "Base directory for this skill")
  • {project_root} — the project working directory
  1. Report the subagent's result to the user

IMPORTANT: The procedure file path uses the plugin's base directory, NOT the project directory. Read the "Base directory for this skill" line from the skill loading message to determine the correct path.

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