Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx skills add LevNas/ccmemo --skill review-knowledgegit clone --depth 1 https://github.com/LevNas/ccmemoWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/skills/levnas/ccmemo/review-knowledge)<a href="https://agentmods.dev/skills/levnas/ccmemo/review-knowledge"><img src="https://agentmods.dev/badge/skills/levnas/ccmemo/review-knowledge/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/levnas/ccmemo/review-knowledge"><img src="https://agentmods.dev/badge/skills/levnas/ccmemo/review-knowledge.svg" alt="Reviewed on agentmods" width="80" height="20"></a>What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00051 | $0.00821 |
| Opus 5.5 | $0.00020 | $0.00328 |
| Sonnet 5.5 | $0.00010 | $0.00164 |
| Haiku 4.5 | $0.00005 | $0.00082 |
Grade A, and why
review-knowledge scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 1mo ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
How it starts
The opening of the file, as written. The whole thing — 88 lines — stays where its author put it; the contents beside it link to each section on GitHub.
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
)
What ships with it
1 file beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 1mo ago First seen · 88 lines · 51 tokens per session scan A 661e4ea3e266
review-knowledge is a skill published in the GitHub repository LevNas/ccmemo (4 stars, last pushed 11d ago), licensed MIT. It adds 51 tokens to every session and 821 once invoked, about $0.0002 per session on Opus 5.5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-31.
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