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 jessepinkman9900/claude-second-brain --skill brain-ingestgit clone --depth 1 https://github.com/jessepinkman9900/claude-second-brainWrote 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/jessepinkman9900/claude-second-brain/brain-ingest)<a href="https://agentmods.dev/skills/jessepinkman9900/claude-second-brain/brain-ingest"><img src="https://agentmods.dev/badge/skills/jessepinkman9900/claude-second-brain/brain-ingest/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/jessepinkman9900/claude-second-brain/brain-ingest"><img src="https://agentmods.dev/badge/skills/jessepinkman9900/claude-second-brain/brain-ingest.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 | $0.00074 | $0.00944 |
| Opus 5.5 | $0.00030 | $0.00378 |
| Sonnet 5.5 | $0.00015 | $0.00189 |
| Haiku 4.5 | $0.00007 | $0.00094 |
Grade A, and why
brain-ingest scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 1mo ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
How it starts
The opening of the file, as written. The whole thing — 86 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Brain Ingest
Runs the full 9-step ingest workflow defined in CLAUDE.md. Do not skip steps.
Brain Discovery
All commands target the default brain registered in ~/.claude-second-brain/config.toml.
Resolve paths at call time via the claude-second-brain CLI — do not bake paths into this file:
BRAIN_PATH=$(npx -y claude-second-brain path) # absolute path to the default brain's directory
qmd commands go through the CLI proxy, which sets INDEX_PATH for you:
npx -y claude-second-brain qmd -- query -c wiki "<terms>"
Pass --brain <name> before the -- to target a non-default brain.
Inputs
- File path — a file in
raw-sources/articles/,raw-sources/pdfs/, orraw-sources/personal/ - URL — fetch and read the full content directly
- Pasted text — treat whatever the user has shared as the source
Workflow
Step 1 — Read the source
- File: use the Read tool on the provided path
- URL: fetch and read the full content
- Pasted text: treat as the source directly
Step 2 — Discuss with the user
- Summarize the source in 3–5 bullets
- Ask: what aspects matter most? Anything to emphasize or skip?
- Let the user's response shape which topics get deep treatment before proceeding
Step 3 — Create source summary page
- File:
$BRAIN_PATH/wiki/sources/[slug].md(slug = kebab-case from title) - Sections: title, author/date, one-paragraph abstract, key claims (bulleted), notable quotes (max 3), synthesis note, links to wiki pages this source touches
- Frontmatter:
type: source-summary,tags,updated: YYYY-MM-DD
Step 4 — Update wiki/index.md
- Add the new source to the Sources Ingested section: one-line description +
[[wiki/sources/slug]]link
Step 5 — Identify affected wiki pages
- Run:
npx -y claude-second-brain qmd -- query -c wiki "<source topic and key claims>" - Also Glob
$BRAIN_PATH/wiki/*.mdand$BRAIN_PATH/wiki/sources/*.mdto catch anything qmd missed - List all pages to create or update before proceeding
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 · 86 lines · 74 tokens per session scan A 90e413df05d9
brain-ingest is a skill published in the GitHub repository jessepinkman9900/claude-second-brain (46 stars, last pushed 6mo ago), licensed MIT. It adds 74 tokens to every session and 944 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 2026-08-30.
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'.
waku-computer-use
Control local macOS, Windows, and Linux apps through Waku Computer Use. Prefer purpose-built connectors, APIs, or CLIs when available.
knowit
Persistent, structured project memory for AI coding agents via the Knowit MCP server. Use before planning or editing code to load relevant rules, architecture, decisions, patterns, and conventions; use after finishing work to save durable learnings. Triggers on "remember this", "what are our conventions", "project…
debrief
Use at the end of a session (or midway through a long one) to deliberately capture what was learned — lessons, decisions, workflows, state changes, and facts — into the knowledge base. The nightly harvest is a safety net for lessons; unless the host opted into KBHARVESTFACTS, /debrief is the only thing that records…
kb-workflow
Use before starting any non-trivial task to search the knowledge base for context, and after completing work to capture findings. Teaches the token-efficient retrieval pattern and self-learning loop.
kmd-ingest
The write protocol for a markdown knowledge base (Obsidian-compatible, the LLM-wiki pattern) — personal or shared. Use for EVERY write into the KB — distilling a new or scraped source, promoting a finished artifact/report/lesson into the KB, filing a durable learning, insight, or query answer, or correcting/updating…