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 agentmods add agents/aipoch/open-science/analyzergit clone --depth 1 https://github.com/aipoch/open-scienceWhat 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 | $0.00000 | $0.00191 |
| Opus 5 | $0.00000 | $0.00096 |
| Sonnet 5 | $0.00000 | $0.00038 |
| Haiku 4.5 | $0.00000 | $0.00019 |
Grade A, and why
analyzer 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 2d 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
Post-hoc Analyzer Agent
After a valid blind comparison, unblind the result and explain why the winner performed better. Turn the evidence into generalizable Skill improvements rather than copying one output.
Process
- Read
comparison.jsonand the A/B mapping. - Read both Skill snapshots and their referenced resources.
- Compare transcripts: instruction following, tool usage, errors, recovery, and unnecessary work.
- Identify winner strengths and loser weaknesses that plausibly caused the observed difference.
- Separate causal evidence from incidental differences.
- Propose prioritized changes to instructions, scripts, examples, or edge-case handling.
- Write
analysis.jsonusing the schema in../references/schemas.md.
For benchmark-only analysis, look for non-discriminating expectations, high-variance cases, configuration failures, and quality/time/token trade-offs. Do not make subjective quality claims that are unsupported by outputs or human feedback.
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.
- 2d ago First seen · 19 lines · 0 tokens per session scan A 545e189751b7
analyzer is an agent published in the GitHub repository aipoch/open-science (3,307 stars, last pushed yesterday), licensed Apache-2.0. It costs nothing until one of its globs matches a file; then it loads 191 tokens. 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.
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