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 yogsoth-ai/de-anthropocentric-research-engine --skill benchmark-archaeologygit clone --depth 1 https://github.com/yogsoth-ai/de-anthropocentric-research-engineWrote 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/yogsoth-ai/de-anthropocentric-research-engine/benchmark-archaeology)<a href="https://agentmods.dev/skills/yogsoth-ai/de-anthropocentric-research-engine/benchmark-archaeology"><img src="https://agentmods.dev/badge/skills/yogsoth-ai/de-anthropocentric-research-engine/benchmark-archaeology/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/yogsoth-ai/de-anthropocentric-research-engine/benchmark-archaeology"><img src="https://agentmods.dev/badge/skills/yogsoth-ai/de-anthropocentric-research-engine/benchmark-archaeology.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector warn
SkillSpector: 1 finding, up to high
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 →
- high Prompt Injection · line 104 Hidden instructions were detected in comments or invisible text. These could contain malicious directives. Manual review is recommended.Fix: Audit all comments and invisible characters. Remove any instructions that direct the agent to perform unauthorized actions. Use plain, reviewable content.
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 | $0.00048 | $0.01228 |
| Opus 5.5 | $0.00019 | $0.00491 |
| Sonnet 5.5 | $0.00010 | $0.00246 |
| Haiku 4.5 | $0.00005 | $0.00123 |
Grade A, and why
benchmark-archaeology 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 — 128 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Benchmark Archaeology
Systematic excavation and critical analysis of AI/ML evaluation methodology. Treats benchmarks as historical artifacts requiring forensic examination — uncovering hidden assumptions, methodological drift, validity decay, and coverage gaps that accumulate over time.
Strategy Routing
| Signal | Route To |
|---|---|
| "audit this benchmark", "benchmark quality", "BetterBench" | benchmark-audit |
| "saturation", "ceiling", "score plateau", "when will X be solved" | saturation-analysis |
| "does it actually measure", "construct validity", "what does score mean" | validity-probing |
| "what's not tested", "coverage gaps", "missing capabilities" | coverage-mapping |
| "different papers get different scores", "protocol differences" | protocol-forensics |
Manifest
Strategies (5)
| Strategy | Purpose |
|---|---|
| benchmark-audit | Systematic quality assessment using BetterBench 46-criterion framework |
| saturation-analysis | Track score trajectories, detect saturation and failure points |
| validity-probing | Challenge construct validity — does benchmark measure claimed capability? |
| coverage-mapping | Map evaluation coverage, identify untested capability dimensions |
| protocol-forensics | Analyze evaluation protocol differences across papers for same benchmark |
Tactics (3)
| Tactic | Purpose |
|---|---|
| score-trajectory-analysis | Collect historical scores, fit saturation curves, detect inflection points |
| artifact-detection | Detect annotation artifacts and shortcuts in benchmarks |
| evaluation-protocol-comparison | Compare implementation differences of same benchmark across papers |
Subagent SOPs (9 + 1 shared)
| SOP | Purpose |
|---|---|
| benchmark-inventory | Identify and catalog all relevant benchmarks in target domain |
| metric-decomposition | Decompose composite metrics into constituent signals |
| contamination-audit | Detect train-test data leakage and memorization artifacts |
| construct-validity-assessment | Evaluate whether benchmark measures its claimed capability |
| documentation-audit | Assess documentation completeness against BetterBench/Datasheets standards |
| capability-taxonomy-mapping | Build capability taxonomy, map existing benchmark coverage |
| leaderboard-dynamics-analysis | Analyze leaderboard score distributions, compression, selective reporting |
| protocol-element-extraction | Extract evaluation protocol parameters from papers |
| benchmark-synthesis | Produce final structured audit report |
| saturation-detection (shared) | Detect saturation signals in score trajectories (from literature-survey) |
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 · 128 lines · 48 tokens per session scan A 6e9f5d1fed03
benchmark-archaeology is a skill published in the GitHub repository yogsoth-ai/de-anthropocentric-research-engine (505 stars, last pushed 4d ago), licensed Apache-2.0. It adds 48 tokens to every session and 1,228 once invoked, about $0.0002 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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