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 CHENyiru3/AI-Skills-Collections --skill computational-biology-retrospectivegit clone --depth 1 https://github.com/CHENyiru3/AI-Skills-CollectionsWrote 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/chenyiru3/ai-skills-collections/computational-biology-retrospective)<a href="https://agentmods.dev/skills/chenyiru3/ai-skills-collections/computational-biology-retrospective"><img src="https://agentmods.dev/badge/skills/chenyiru3/ai-skills-collections/computational-biology-retrospective/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/chenyiru3/ai-skills-collections/computational-biology-retrospective"><img src="https://agentmods.dev/badge/skills/chenyiru3/ai-skills-collections/computational-biology-retrospective.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 | $0.00080 | $0.02167 |
| Opus 5.5 | $0.00032 | $0.00867 |
| Sonnet 5.5 | $0.00016 | $0.00433 |
| Haiku 4.5 | $0.00008 | $0.00217 |
Grade A, and why
computational-biology-retrospective 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 6d 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 — 119 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Computational Biology Retrospective
Turn a mixed research folder into a concise, traceable account of what was attempted, what worked, what failed, and what remains uncertain. Preserve lessons that another agent can retrieve and apply without the original conversation.
Treat algorithm behavior, implementation correctness, statistical evidence, and biological interpretation as distinct questions. A completed run or improved benchmark does not by itself establish biological validity. An unsuccessful experiment does not by itself refute the biological hypothesis.
Scope and output
- Use the user's folder, question, and requested output path. Otherwise use the active project root, follow its existing reporting convention, and fall back to
EXPERIENCE.mdin that root. Use the user's requested language or the established project language; default to English if neither is clear. - Review existing evidence. Reading artifacts and computing small, transparent summaries is part of this work; running project pipelines, retraining models, or changing analyses requires a request that includes that work. List proposed experiments separately from completed ones.
- Write the Markdown report without asking for routine confirmation. Preserve original scripts, datasets, logs, and reports. Add an index link only if requested or required by the project's documented convention.
- If the folder is unavailable or the working directory contains unrelated projects with no identifiable target, request the project location. Otherwise make useful progress before asking about an ambiguity; explicitly state the review scope when no narrow question was supplied.
1. Find the project record before exploring the experiments
Read applicable AGENTS.md instructions and make a bounded inventory of the root and likely documentation directories. Prefer rg --files for discovery and rg -n for targeted text searches. Do not dump large data directories or entire notebooks into context.
Look first for an index or recording document: INDEX.md, README.md, experiment registries, research logs, lab notebooks, HANDOFF.md, progress notes, and any existing experience report. Names are hints; identify which document actually maps the work. Follow Obsidian links or other local link conventions if present.
What ships with it
3 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
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.
- 6d ago First seen · 119 lines · 80 tokens per session scan A 9f88db673e8d
computational-biology-retrospective is a skill published in the GitHub repository CHENyiru3/AI-Skills-Collections (1 stars, last pushed 7d ago), licensed MIT. It adds 80 tokens to every session and 2,167 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 2026-10-02.
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