Scientific Agent Skills is a collection of reusable procedures that give AI agents capabilities for scientific research across areas such as biology, chemistry, medicine, and drug discovery. It is used by researchers and by people building AI scientist workflows with compatible coding agents. The catalogue contains many of the project's skills and supporting instructions.
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 K-Dense-AI/scientific-agent-skills --skill analytical-method-validationgit clone --depth 1 https://github.com/K-Dense-AI/scientific-agent-skillsWrote 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/k-dense-ai/scientific-agent-skills/analytical-method-validation)<a href="https://agentmods.dev/skills/k-dense-ai/scientific-agent-skills/analytical-method-validation"><img src="https://agentmods.dev/badge/skills/k-dense-ai/scientific-agent-skills/analytical-method-validation/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/k-dense-ai/scientific-agent-skills/analytical-method-validation"><img src="https://agentmods.dev/badge/skills/k-dense-ai/scientific-agent-skills/analytical-method-validation.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- Socket pass
- Snyk pass
- 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 Excessive Agency · line 283 Skill enables autonomous high-impact decisions without human-in-the-loop verification. Critical operations (destructive commands, financial transactions, data deletion) should require explicit user confirmation.Fix: Add human-in-the-loop confirmation for destructive, irreversible, or high-impact operations. Never auto-execute commands that modify files, send data, or alter system state.
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 | $0.00281 | $0.04879 |
| Opus 5.5 | $0.00112 | $0.01952 |
| Sonnet 5.5 | $0.00056 | $0.00976 |
| Haiku 4.5 | $0.00028 | $0.00488 |
Grade A, and why
analytical-method-validation 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 14d 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.
Copies of this mod
3 near-identical copies found in the catalogue:
- analytical-method-validation — 100% identical, 93 lines differ
- analytical-method-validation — 92% identical, 83 lines differ
- analytical-method-validation — 91% identical, 76 lines differ
How it starts
The opening of the file, as written. The whole thing — 343 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Analytical Method Validation
When to use
Any time the question is whether an analytical procedure is fit for its intended purpose: designing a validation study, evaluating validation data, verifying a compendial procedure, transferring a procedure to another laboratory or instrument, or defending any of these in a report.
The two rules
1. Establish which framework governs before designing anything. The same assay validates differently under ICH Q2(R2), USP <1225>, ICH M10, CLSI EP, and ISO/IEC 17025. They differ in which characteristics are required, how the studies are laid out, and whether numeric acceptance criteria are supplied at all. Blending them produces a protocol that satisfies none of them.
2. State acceptance criteria before collecting data. Criteria chosen after seeing results are not acceptance criteria, and deciding them post hoc is a standing audit finding. ICH Q2(R2) deliberately supplies almost no numeric criteria — they have to come from the specification, the analytical target profile (ICH Q14 section 3), or development data. ICH M10 is the exception: it supplies explicit numbers, and they differ between chromatographic assays and ligand binding assays.
Scope
This skill plans studies, computes the statistics correctly, and structures the documentation. It
does not decide that a procedure is validated, release a batch, accept or reject a run, close
an investigation, or substitute for the analyst, the technical reviewer, the quality unit, or the
regulator. Every script reports computations and supported findings; only the responsible reviewers can
make the fitness-for-purpose decision. JSON uses null for unavailable statistics.
Copyright boundary
ICH guidelines are published openly and licensed for reuse with acknowledgement, so their requirements are encoded directly in this skill. USP general chapters, CLSI EP documents, and ISO standards are copyrighted and paywalled. For those, this skill supplies the designation, scope, and where to obtain an authorised copy — never the text, never invented thresholds. Do not ask an agent to retrieve, transcribe, or reconstruct their content. If a number matters and it lives in a paywalled document, read it from the authorised copy.
What ships with it
16 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.
- assets/validation-protocol-template.md 4.1 KB
- assets/validation-report-template.md 3.9 KB
- references/compendial-and-clsi.md 7.6 KB
- references/framework-selection.md 5.3 KB
- references/ich-m10-bioanalytical.md 8.8 KB
- references/ich-q2r2.md 13 KB
- references/source-ledger.md 7.5 KB
- references/statistics.md 13 KB
- scripts/_catalog.py 23 KB runs code
- scripts/_common.py 34 KB runs code
- scripts/check_accuracy_precision.py 16 KB runs code
- scripts/check_bioanalytical_run.py 14 KB runs code
- scripts/check_detection_limits.py 14 KB runs code
- scripts/check_response.py 10 KB runs code
- scripts/compare_methods.py 9.1 KB runs code
- scripts/plan_validation.py 15 KB runs code
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.
- 14d ago Changed · +22 lines 7c2cd278bd39
- 15d ago Changed · +4 lines 4c810b0b37b7
- 1mo ago Changed · +17 lines 9f6db7bd7785
- 1mo ago First seen · 300 lines · 281 tokens per session scan A 78e81a7713ef
analytical-method-validation is a skill published in the GitHub repository K-Dense-AI/scientific-agent-skills (50,453 stars, last pushed today), licensed MIT. It adds 281 tokens to every session and 4,879 once invoked, about $0.0011 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.
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