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 nicholasglazer/gnosis-mcp --skill ingestgit clone --depth 1 https://github.com/nicholasglazer/gnosis-mcpWrote 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/nicholasglazer/gnosis-mcp/ingest)<a href="https://agentmods.dev/skills/nicholasglazer/gnosis-mcp/ingest"><img src="https://agentmods.dev/badge/skills/nicholasglazer/gnosis-mcp/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/nicholasglazer/gnosis-mcp/ingest"><img src="https://agentmods.dev/badge/skills/nicholasglazer/gnosis-mcp/ingest.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector pass
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 | $0.00054 | $0.01878 |
| Opus 5 | $0.00027 | $0.00939 |
| Sonnet 5 | $0.00011 | $0.00376 |
| Haiku 4.5 | $0.00005 | $0.00188 |
Grade A, and why
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 10d 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 — 235 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Ingest
One skill that covers every way to get content into gnosis-mcp. Routes
based on $ARGUMENTS:
- Path to a directory / file → local file ingest
git <repo>→ git-history ingestcrawl <url>→ web-crawl ingestreingest→ full reset + re-ingest from the default pathprune <path>→ delete DB chunks whose source is gone
Action: $ARGUMENTS
ingest <path> — local files
Default entry point. Handles .md, .txt, .ipynb, .toml, .csv,
.json (+ .rst / .pdf if those extras are installed).
First-time ingest
gnosis-mcp ingest ./docs --embed
--embedruns the bundled ONNX embedder (requires[embeddings]extra). Without it you get keyword-only search — usually enough for dev-doc corpora (see bench-experiments), but--embedcosts nothing on a first ingest and enables hybrid later if you want it.- Incremental: every file's content hash is stored, so re-running only
processes changed files. Use
--forceto re-ingest regardless.
Chunk size
Default is 2000 characters (~600 tokens) — peak of the Feb 2026 sweep on a real dev-docs corpus. Override per-ingest or globally:
# This invocation only
GNOSIS_MCP_CHUNK_SIZE=1500 gnosis-mcp ingest ./docs --embed
# Persistent (put in shell profile)
export GNOSIS_MCP_CHUNK_SIZE=3000 # long-form blogs / ADRs
If you're unsure, run /gnosis:tune to sweep sizes against your own
golden queries.
Reorganized your knowledge folder
Files moved, deleted, renamed. Pick one:
# Safest: re-ingest + drop chunks for files that no longer exist
gnosis-mcp ingest ./docs --embed --prune
# Nuclear: drop everything first, then re-ingest
gnosis-mcp ingest ./docs --embed --wipe
# Preview what prune would delete
gnosis-mcp prune ./docs --dry-run
By default --prune leaves crawled URLs alone (since those don't
correspond to local files). Add --include-crawled if you want those
gone too.
ingest git <repo> — git commit history
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.
- 10d ago First seen · 235 lines · 54 tokens per session scan A c857a6e7bd37
ingest is a skill published in the GitHub repository nicholasglazer/gnosis-mcp (29 stars, last pushed 21d ago), licensed MIT. It adds 54 tokens to every session and 1,878 once invoked, about $0.0003 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 2026-08-30.
Other skills, from other repositories
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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'.
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Guide for using the NeuroLink SDK and CLI. Invoke when users ask how to use neurolink, integrate AI providers, add MCP tools, configure RAG, set up memory, deploy servers, or work with multimodal content. Covers SDK, CLI, providers, tools, and enterprise features.
memobase
A Russian-language skill for searching a local knowledge base built from documents and other sources such as web pages, YouTube, audio, and Obsidian notes.
wiki-query
A knowledge-base search skill that retrieves existing information from a local collection of documents and combines it into an answer. It can use exact matches, broader search, and links between related pages.
vault
Generate an Obsidian LLM wiki vault from a project's source code and any static documents in raw/.