Getting it into your agent
It runs from inside its repository, so the clone comes first — what it calls does not travel with the file alone.
git clone --depth 1 https://github.com/nicholasglazer/gnosis-mcpnpx agentmods add skills/nicholasglazer/gnosis-mcp/evalWrote 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/eval)<a href="https://agentmods.dev/skills/nicholasglazer/gnosis-mcp/eval"><img src="https://agentmods.dev/badge/skills/nicholasglazer/gnosis-mcp/eval/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/eval"><img src="https://agentmods.dev/badge/skills/nicholasglazer/gnosis-mcp/eval.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector warn
SkillSpector: 1 finding, up to medium
These are SkillSpector’s own severities. On a checked sample its high-severity flags on skills were ~96% false positives — a documented command, a public API, a “never do X” rule — so we show them as a caution to read, not a verdict. Why →
- medium Rogue Agent · line 96 Skill establishes unauthorized persistence across sessions via cron jobs, startup scripts, or state files. Session persistence allows an attacker to maintain access beyond the current interaction.Fix: Remove any persistence mechanisms (cron jobs, startup scripts, state files). Skills should not maintain state across sessions without explicit user consent.
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 | $0.00071 | $0.02295 |
| Opus 5.5 | $0.00028 | $0.00918 |
| Sonnet 5.5 | $0.00014 | $0.00459 |
| Haiku 4.5 | $0.00007 | $0.00230 |
Grade A, and why
eval 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 — 183 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Eval
gnosis-mcp eval in ~10 lines of wrapper logic. Reports retrieval
quality, compares to last known numbers, and points at /gnosis:tune if
anything looks regressed.
Know what you are measuring. gnosis-mcp eval does not score your
corpus. It loads nine hardcoded sample documents (SAMPLE_DOCS +
SAMPLE_GIT_HISTORY_DOCS from the repository's tests/eval/ fixtures)
into a temporary database and ignores GNOSIS_MCP_DATABASE_URL, so it
prints identical numbers no matter what you have indexed. It is a harness
smoke test, not a measurement of your docs. To score your own corpus, run
the real-corpus benchmark (Step 1b) — that path is corpus-specific and
reports nDCG@10, which gnosis-mcp eval never emits.
Different from /gnosis:tune: tune sweeps configurations looking
for the best chunk size / embedder / rerank combo. Eval just reports
current numbers. Run eval often (after each ingest, whenever the
corpus changes). Run tune occasionally (after corpus shape change,
new embedder, weekend of experimentation).
Usage
/gnosis:eval # full run — print numbers + interpret + compare
/gnosis:eval quick # numbers only, no interpretation
/gnosis:eval save # save current result as new baseline
/gnosis:eval diff # compare current to last saved baseline
Mode: $ARGUMENTS
Step 1 — run the harness
gnosis-mcp eval --json
Parses to:
{
"cases": 10,
"hit_rate_at_k": 1.0,
"mrr": 1.0,
"mean_precision_at_k": 0.75,
"k": 5
}
Those five keys are the whole contract — there is no ndcg_at_10 in this
command's output, and no queries / hit_at_5 / mean_precision_at_5
(the real names carry _at_k plus the separate k field).
If the command errors, the cause is almost always a missing repository
checkout: eval imports its fixtures from tests/eval/, so a plain
pip install (no tests/ directory) exits 1 with an install-from-source
hint. It does not need the [embeddings] extra, a golden file, or a
populated database — it builds its own fixture in a temp DB. Don't
proceed with empty numbers — fail loudly.
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 Changed · +52 lines · +7 tokens per session a81849bbd356
- 2mo ago First seen · 131 lines · 64 tokens per session scan A f4cf26298589
eval is a skill published in the GitHub repository nicholasglazer/gnosis-mcp (31 stars, last pushed 22d ago), licensed MIT. It adds 71 tokens to every session and 2,295 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.
eval compared with skills from other repositories
| Mod | Type | Stars | Last push | Licence | Scan | Tokens | Works with |
|---|---|---|---|---|---|---|---|
| evalnicholasglazer/gnosis-mcp | Skill | 31 | 22d ago | MIT | A | 71 | Claude Code |
| accreta-setupfrancescofioredev/accreta | Skill | 1 | 9d ago | MIT | A | 100 | Claude Code, Codex |
| vaultburakolgun/vault-anything | Skill | 5 | 4mo ago | MIT | A | 23 | Claude Code |
| vault-updateburakolgun/vault-anything | Skill | 5 | 4mo ago | MIT | A | 33 | Claude Code |
| llmwikiatomicstrata/llm-wiki-compiler | Skill | 2.2k | 7d ago | MIT | A | 66 | Claude Code, Codex |
| paper-readerpoco-ai/Agentero | Skill | 1.1k | today | MIT | A | 43 | Claude Code, Codex |
| idea-evaluatorpoco-ai/Agentero | Skill | 1.1k | today | MIT | A | 123 | Claude Code, Codex |