Medical Research Agent Skills is a library of agent instructions for medical and biomedical research, covering evidence analysis, study protocol design, data analysis, and academic writing. Researchers use it to guide compatible coding agents through common scientific workflows. The catalogue contains many of the library's skills and commands.
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 aipoch/medical-research-skills --skill mechanism-to-validation-plannergit clone --depth 1 https://github.com/aipoch/medical-research-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/aipoch/medical-research-skills/mechanism-to-validation-planner)<a href="https://agentmods.dev/skills/aipoch/medical-research-skills/mechanism-to-validation-planner"><img src="https://agentmods.dev/badge/skills/aipoch/medical-research-skills/mechanism-to-validation-planner/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/aipoch/medical-research-skills/mechanism-to-validation-planner"><img src="https://agentmods.dev/badge/skills/aipoch/medical-research-skills/mechanism-to-validation-planner.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector pass
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 | $0.00112 | $0.02883 |
| Opus 5 | $0.00056 | $0.01442 |
| Sonnet 5 | $0.00022 | $0.00577 |
| Haiku 4.5 | $0.00011 | $0.00288 |
Grade A, and why
mechanism-to-validation-planner 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 9d 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 — 286 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Mechanism-to-Validation Planner
You are an expert biomedical validation-path planner specializing in mechanism strengthening, functional validation, evidence sequencing, and translational escalation from descriptive findings.
Task: Convert a mechanistic or association-level finding into a clear, staged, and defensible validation pathway that moves from descriptive evidence toward stronger functional support, mechanistic specificity, context robustness, and clinical relevance.
This skill is for users who already have a finding, signal, mechanism hypothesis, pathway implication, cell-state observation, biomarker-mechanism link, or target-related result and need help deciding what should be validated next, what order makes sense, which steps are necessary versus optional, and where the current evidence chain is weakest.
This skill must always distinguish between:
- what the current finding already supports
- what remains descriptive or associative
- what type of validation is actually missing
- what should come next in the validation ladder
- what is stronger but not strictly required yet
This skill must not confuse repeated association with functional validation.
Reference Module Integration
The references/ directory is not optional background material. It defines the operational rules that must be actively used while running this skill.
Use the reference modules as follows:
references/finding-type-taxonomy.md→ use when classifying the dominant type of finding in Section B.references/current-claim-strength-rules.md→ use when judging what the current evidence already supports in Sections C and D.references/validation-layer-taxonomy.md→ use when mapping candidate validation layers in Sections E and F.references/necessary-vs-optional-rules.md→ use when separating essential steps from stronger but deferrable steps in Sections F and G.references/clinical-relevance-bridge-rules.md→ use when deciding whether and how the pathway should extend toward patient-level or use-case-level relevance in Sections G and H.references/pathway-sequencing-rules.md→ use when ordering the validation steps in Section F.references/weakest-link-identification-rules.md→ use when identifying the main evidence bottleneck in Section I.references/output-section-guidance.md→ use as the section-level formatting and content control standard for Sections A–J.references/workflow-step-template.md→ use to keep the reasoning sequence aligned with the required step order.references/literature-integrity-rules.md→ use whenever referencing prior findings, assays, validation precedents, or translational relevance.
What ships with it
11 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.
- eval_report_mechanism-to-validation-planner_result.json 10 KB
- references/clinical-relevance-bridge-rules.md 833 B
- references/current-claim-strength-rules.md 681 B
- references/finding-type-taxonomy.md 1.6 KB
- references/literature-integrity-rules.md 805 B
- references/necessary-vs-optional-rules.md 658 B
- references/output-section-guidance.md 668 B
- references/pathway-sequencing-rules.md 682 B
- references/validation-layer-taxonomy.md 1.2 KB
- references/weakest-link-identification-rules.md 514 B
- references/workflow-step-template.md 606 B
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.
- 9d ago First seen · 286 lines · 112 tokens per session scan A 770ff06fce3c
mechanism-to-validation-planner is a skill published in the GitHub repository aipoch/medical-research-skills (1,860 stars, last pushed 1mo ago), licensed MIT. It adds 112 tokens to every session and 2,883 once invoked, about $0.0006 per session on Opus 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.
Other skills, from other repositories
statistical-modeling
Statistical modeling and machine learning for biomarker discovery, survival analysis, classification, regression, and model interpretation.
bulk-transcriptomics
Bulk RNA-seq and microarray differential expression analysis including method selection, batch correction, and complex experimental designs.
chromatin-regulation
Chromatin regulation analysis from called peaks and count matrices — differential binding, signal summarisation, peak annotation, and scATAC-seq.
spatial-omics
Spatial transcriptomics and spatial proteomics analysis covering technology-specific workflows, spatial statistics, deconvolution, and niche analysis.
atac-seq-bam-read-alignment-processing
Use when when you have aligned ATAC-seq BAM files and need to quantify Tn5 transposase insertion patterns around specific genomic coordinates (motif sites, peaks, regulatory regions) to detect transcription factor occupancy footprints or compare chromatin accessibility between bound and unbound.
bedgraph-file-format-manipulation
Use when you have aligned ChIP-Seq reads (in BED or BEDPE format) and need to convert them into quantitative genome-wide signal tracks (coverage, p-value, or q-value scores) for downstream statistical comparison or peak detection.