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/joplin-knowledge-flow/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/joplin-knowledge-flow)<a href="https://agentmods.dev/skills/gcake119/joplin-llm-wiki/joplin-knowledge-flow"><img src="https://agentmods.dev/badge/skills/gcake119/joplin-llm-wiki/joplin-knowledge-flow/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/joplin-knowledge-flow"><img src="https://agentmods.dev/badge/skills/gcake119/joplin-llm-wiki/joplin-knowledge-flow.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 | $0.00102 | $0.01216 |
| Opus 5 | $0.00051 | $0.00608 |
| Sonnet 5 | $0.00020 | $0.00243 |
| Haiku 4.5 | $0.00010 | $0.00122 |
Grade A, and why
joplin-knowledge-flow 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 11d 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 — 108 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Joplin Knowledge Flow
Use the joplin-llm-wiki MCP tools as the primary interface for knowledge-flow
operations in Codex or Cursor conversations.
Tool Preference
- Use
joplin_queryfor questions over the localwiki/andraw/corpus. - Use
joplin_brainstormfor exploratory thinking that should become a brainstorming pending capture. - Use
joplin_show_captureto inspect a pending capture without changing files. - Use
joplin_confirm_captureto turn a pending capture into a formal note underbrainstorming/chat/orartifacts/<project>/. - Use
joplin_suggest_archive_projectbefore project artifact archival. - Use
joplin_archive_projectonly after the user confirms the project name. - Use
joplin_sync_sourcesfor existingsqlite-syncmodes. - Use
joplin_sync_workflow_noteswhen the user edited@llm-wiki/brainstormingor@llm-wiki/artifactsin Joplin and wants those workflow notes pulled back into workspacebrainstorming/orartifacts/. - Use
joplin_compile_wikifor existingwiki-compileoragent-compileflows.
Capture Policy Integration
When another skill has produced reusable knowledge, apply the
knowledge-capture-policy rules before deciding whether to call these MCP
tools. Strong signal reusable work should normally create a pending capture draft
with joplin_brainstorm. Use joplin_query only when the user asks an explicit
knowledge-base question that should preserve query sources. Medium signal work
should ask the user whether they want a pending capture. Low signal work should
not interrupt the conversation.
If MCP tools are not available in the current session, tell the user the MCP server is not loaded and ask them to reload/restart Codex or Cursor after checking the MCP configuration. Do not silently replace this workflow with ad hoc file writes.
Query And Capture
Queries should preserve the pending capture workflow:
- Answer with
joplin_queryorjoplin_brainstorm. - If the result includes
capture_draft_id, show the id and ask whether to confirm it when the user wants a formal note. - Confirm only through
joplin_confirm_capture.
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.
- 11d ago First seen · 108 lines · 102 tokens per session scan A 7ef356254d38
joplin-knowledge-flow is a skill published in the GitHub repository gcake119/joplin-llm-wiki (2 stars, last pushed 3mo ago), licensed MIT. It adds 102 tokens to every session and 1,216 once invoked, about $0.0005 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'.
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…
setup
Set up memex with provisioned Postgres (RDS + pgvector), AGENTS.md injection, first import.
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.