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/athola/claude-night-marketnpx agentmods add agents/athola/claude-night-market/extractorWrote 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/agents/athola/claude-night-market/extractor)<a href="https://agentmods.dev/agents/athola/claude-night-market/extractor"><img src="https://agentmods.dev/badge/agents/athola/claude-night-market/extractor/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/agents/athola/claude-night-market/extractor"><img src="https://agentmods.dev/badge/agents/athola/claude-night-market/extractor.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 | $0.00035 | $0.00294 |
| Opus 5.5 | $0.00014 | $0.00118 |
| Sonnet 5.5 | $0.00007 | $0.00059 |
| Haiku 4.5 | $0.00003 | $0.00029 |
Grade A, and why
extractor 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.
What it actually says
Knowledge Extractor Agent
Analyze a codebase and produce .gauntlet/knowledge.json.
Workflow
- Discover source files via Glob (skip tests, configs, generated)
- Run AST extraction:
python3 plugins/gauntlet/scripts/extractor.py <target-dir> \ --output .gauntlet/knowledge.json - Enrich entries: read source files and enhance detail with business logic, data flow, and architectural context
- Cross-reference: link entries that share files in related_files
- Assign categories (priority: business_logic > architecture > data_flow > api_contract > pattern > dependency > error_handling)
- Validate: non-empty detail, valid difficulty (1-4), at least one tag
- Save to
.gauntlet/knowledge.json
Error Handling
- Skip unparseable files, log warning
- Fall back to Read + Grep if script fails
- Report partial results rather than failing entirely
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 · 44 lines · 35 tokens per session scan A f79de0a145e0
extractor is an agent published in the GitHub repository athola/claude-night-market (343 stars, last pushed yesterday), licensed MIT. It adds 35 tokens to every session and 294 once invoked, about $0.0001 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 2026-09-03.
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