Borrowing it
Nothing to install: this file belongs to gcake119/joplin-llm-wiki. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.
curl -O https://raw.githubusercontent.com/gcake119/joplin-llm-wiki/main/.agents/skills/knowledge-capture-policy/SKILL.mdgit clone --depth 1 https://github.com/gcake119/joplin-llm-wikiWrote 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/gcake119/joplin-llm-wiki/knowledge-capture-policy)<a href="https://agentmods.dev/skills/gcake119/joplin-llm-wiki/knowledge-capture-policy"><img src="https://agentmods.dev/badge/skills/gcake119/joplin-llm-wiki/knowledge-capture-policy/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/gcake119/joplin-llm-wiki/knowledge-capture-policy"><img src="https://agentmods.dev/badge/skills/gcake119/joplin-llm-wiki/knowledge-capture-policy.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 | $0.00038 | $0.00888 |
| Opus 5 | $0.00019 | $0.00444 |
| Sonnet 5 | $0.00008 | $0.00178 |
| Haiku 4.5 | $0.00004 | $0.00089 |
Grade A, and why
knowledge-capture-policy 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 12d 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 — 110 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Knowledge Capture Policy
Use this policy from other skills when a conversation, workflow, debug session, archive, or architecture explanation has produced reusable knowledge. The goal is to create useful pending capture drafts, not to write formal notes automatically.
Tool Boundary
- Use
joplin_brainstormwhen the output is an exploratory note, decision record, debugging lesson, archive summary, or architecture mental model. - Use
joplin_querywhen the output is grounded in an explicit knowledge-base question and should preserve query sources. - Use
joplin_show_captureonly to inspect an existing pending capture. - Use
joplin_confirm_captureonly after the user explicitly confirms that the pending capture should become a formal note. - Do not call joplin_confirm_capture automatically.
- Do not write files directly under
brainstorming/,artifacts/,raw/, orwiki/as a substitute for MCP tools. - If MCP tools are not available, tell the user the MCP server is not loaded and ask them to restart or reload Codex or Cursor after checking MCP config.
Signal Levels
Strong Signal
Create a pending capture draft when the work has reached one of these outcomes:
- A Spectra archive completed and produced durable decisions, spec changes, or verification evidence.
- A debugging session verified a root cause and fix.
- An architecture explanation produced a reusable mental model.
- Brainstorming converged on a decision, rejected alternatives, or next steps.
- A handoff prompt or workflow rule can be reused in future sessions.
Medium Signal
Ask the user whether to create a pending capture when:
- The discussion is valuable but still unresolved.
- The classification between
brainstormingandartifactsis unclear. - The content may contain sensitive context that the user should review first.
- A Spectra proposal or design already exists, but extra rationale may be worth saving separately.
Low Signal
Do not prompt or create a capture for:
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.
- 12d ago First seen · 110 lines · 38 tokens per session scan A 3161cb30ed33
knowledge-capture-policy is a skill published in the GitHub repository gcake119/joplin-llm-wiki (2 stars, last pushed 3mo ago), licensed MIT. It adds 38 tokens to every session and 888 once invoked, about $0.0002 per session on Opus 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.
Other skills, from other repositories
karpathy-llm-wiki
Use when building or maintaining a personal LLM-powered knowledge base. Triggers: ingesting sources into a wiki, querying wiki knowledge, linting wiki quality, 'add to wiki', 'what do I know about', or any mention of 'LLM wiki' or 'Karpathy wiki'.
setup
Set up memex with provisioned Postgres (RDS + pgvector), AGENTS.md injection, first import.
cold-start
Day-one data bootstrapping for a new brain. Sequences the highest-leverage data sources to go from empty brain to useful brain in one session. Uses the agent host's managed connectors for safe credential handling — the agent never holds raw API keys. Covers Gmail import, calendar sync, contacts seeding, X/Twitter…
eiirp
Everything In Its Right Place. The universal post-work organizer. After any significant work session, EIIRP runs a 7-phase audit: (1) inventory every output, (2) walk the filing taxonomy to decide where each lands, (3) check ontology consistency against the brain's actual shape, (4) file enriched brain pages, (5)…
maintain
Brain health checks: back-link enforcement, citation audit, filing validation, stale info detection, orphan pages, and benchmarks. Use when asked to check brain health, run maintenance, or audit quality.
ingest
Route content to specialized ingestion skills. Detects input type and delegates.