Review knowledge
npx -y skills add LevNas/ccmemo --skill review-knowledgeAssembled from the repository path, not quoted from the project. Check it against their README if it does not work.
One thing to look at
- 3 stars3 stars. Stars are a popularity signal and not a quality one, but at this level it is likely that nobody has read this closely except its author, and you would be relying on your own review.
What its author says it does
Copied from the file, not written here
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.
The file declares its own license as MIT. That is the author’s claim about this one file, and it is not the same thing as the license GitHub reports for the repository, which is listed with the other numbers below.
SKILL.md
3.5 KB, as published. Nobody here has run it
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.
- Determine the review mode from user input:
- No argument or "health" →
health topic:<keyword>→topicwith the specified keywordfix→fix
- No argument or "health" →
- Determine the knowledge base path (default:
.claude/knowledge/entries/) - 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, orfix{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
- 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.