Getting it into your agent
This one installs as part of its plugin. Adding the marketplace and installing the plugin brings it with everything else the plugin ships.
/plugin marketplace add tessaryai/plugins/plugin install crewWrote 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/tessaryai/plugins/manage-knowledge)<a href="https://agentmods.dev/skills/tessaryai/plugins/manage-knowledge"><img src="https://agentmods.dev/badge/skills/tessaryai/plugins/manage-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/tessaryai/plugins/manage-knowledge"><img src="https://agentmods.dev/badge/skills/tessaryai/plugins/manage-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 | $0.00065 | $0.00848 |
| Opus 5.5 | $0.00026 | $0.00339 |
| Sonnet 5.5 | $0.00013 | $0.00170 |
| Haiku 4.5 | $0.00006 | $0.00085 |
Grade A, and why
manage-knowledge scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 1mo ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
How it starts
The opening of the file, as written. The whole thing — 79 lines — stays where its author put it; the contents beside it link to each section on GitHub.
manage-knowledge
Internal crew primitive — dispatched by
/crew:run. You are running because the orchestrator selected this as one step of a larger workflow; carry out the work below. This skill is not meant to be invoked on its own — user requests go to/crew:run.
You curate an evergreen knowledge base of durable decisions and gotchas — the "why"
behind the code that source and user docs don't capture. This complements update-docs
(which keeps user/developer docs accurate); here you distill decisions and lessons.
Argument is optional: a PR number captures from that PR; with no argument, do a sweep over recent merged PRs that aren't yet represented.
0. Load config and mode
python3 "${CLAUDE_PLUGIN_ROOT}/lib/load_config.py"
Use knowledge.dir (default docs/knowledge), labels.agent_pr, and ledger.dir.
Then read ${CLAUDE_PLUGIN_ROOT}/reference/work-model.md and resolve the mode before any
gh call.
1. Gather source material
- GitHub — PR mode:
gh pr view <N> --comments+gh pr diff <N>— read the description, the review thread, and the change itself. - GitHub — sweep mode:
gh pr list --state merged --limit 20 --json number,title,mergedAtand pick recent ones not yet referenced inknowledge.dir. - Local mode: read the task's
decision.mdandreview.mdfrom the ledger plus the branch's history (git log/git diff <base>...<branch>in the worktree).
2. Extract durable knowledge
Pull out only durable, reusable items — things a future engineer would want to know:
- Decisions — "we chose X over Y because Z" (with the trade-off and constraints).
- Patterns / conventions — a new approach the team adopted and why.
- Gotchas — non-obvious pitfalls, footguns, or constraints discovered the hard way.
Skip the ephemeral (one-off bug fixes with no lasting lesson, routine changes). If a PR yields nothing durable, record nothing for it.
3. Dedupe and write
- Read existing entries under
knowledge.dir. If an item is already covered, update that entry rather than adding a duplicate; only add genuinely new knowledge. - Append/update a dated entry in
knowledge.dir/decisions.md(create the file and a briefknowledge.dir/README.mdtopic index if absent), linking the source PR:
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 · 79 lines · 65 tokens per session scan A 263f358281b0
manage-knowledge is a skill published in the GitHub repository tessaryai/plugins (3 stars, last pushed 1mo ago), licensed MIT. It adds 65 tokens to every session and 848 once invoked, about $0.0003 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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