How do I install the Bioresearch Agent Router skill?

Run npx skillmds@latest add alim430/bioresearch-agent-router in your terminal (requires Node.js), paste this page's agent-chat prompt into Claude, Cursor, or any MCP-connected agent, or download the SKILL.md file and copy it into your agent's skills directory.

Is Bioresearch Agent Router safe to use?

This skill has not completed SkillMD's automated safety review yet. SkillMD never runs a skill's scripts for you; review the SKILL.md before installing.

Which AI agents work with Bioresearch Agent Router?

This skill is tagged as working with Claude Code, Claude.ai, OpenAI Codex. SKILL.md is an open format, so most agents that read a skills directory can load it too.

Is Bioresearch Agent Router free to use?

Yes. Installing skills from SkillMD is free, and the skill stays under its author's original license.

Who published Bioresearch Agent Router?

Alim430 (@alim430) published this skill. Their other Agent Skills are listed on their SkillMD profile.

Bioresearch Agent Router by alim430

Name: Bioresearch Agent Router
Author: Alim430

Bioresearch Agent Router

Classify a free-text research intent into the right BioResearch Agent workflow (literature / biomarker / causal / case-study / doctor) using a deterministic, rule-based router. Use when an AI client receives an open-ended biomedical research request and must pick which workflow or skill to invoke — NOT to generate or evaluate hypotheses. No LLM, no network.

Alim430 1ada23a 2.3 KB Updated Sep 17, 2026

File contents

BioResearch Agent — Agent Router Skill

Capability

A rule-based intent classifier that translates a free-text research request into one of the framework's workflows/skills:

Route	Workflow / skill
`literature`	Literature review + co-occurrence graph (`bioresearch-literature-analysis`)
`biomarker`	Biomarker discovery — DEG + enrichment (`bioresearch-biomarker-discovery`)
`causal`	Mendelian randomization (`bioresearch-causal-inference`)
`case-study`	Disease case study / validation run (`bioresearch-disease-case-study`)
`doctor`	Environment & reproducibility check (`bioresearch-environment-check`)

It is intent translation, not reasoning: it maps a request to an existing workflow and emits the matching CLI command. It does not generate, rank, or evaluate hypotheses, and uses no model and no network — the same input always yields the same route (deterministic).

Run

bioresearch route "find biomarkers for Parkinson's disease using GSE7621"
bioresearch route "test the causal effect of BMI on type 2 diabetes with Mendelian randomization"

Output is JSON: {route, confidence, matched_keywords, scores, rationale, suggestion} plus a suggested CLI command. confidence is the share of all matched keywords belonging to the winning route; an unmatched intent returns route: "unknown" with a suggestion list of available routes.

When to invoke

An agent should call this router first when it gets an ambiguous or free-form biomedical request, to decide which specialized skill/workflow to dispatch to. It is the entry funnel of the skill system — not a replacement for the analysis skills themselves.

Note

Honest scope: keyword-substring matching only. It will not understand paraphrases that contain none of the known keywords (it then returns unknown rather than guessing). Extend bioresearch/router.py:ROUTE_KEYWORDS to cover new phrasing.

---name: bioresearch-agent-routerdescription: Classify a free-text research intent into the right BioResearch Agent workflow (literature / biomarker / causal / case-study / doctor) using a deterministic, rule-based router. Use when an AI client receives an open-ended biomedical research request and must pick which workflow or skill to invoke — NOT to generate or evaluate hypotheses. No LLM, no network.---# BioResearch Agent — Agent Router Skill## CapabilityA **rule-based intent classifier** that translates a free-text research request into one of theframework's workflows/skills:| Route | Workflow / skill ||:---|:---|| `literature` | Literature review + co-occurrence graph (`bioresearch-literature-analysis`) || `biomarker` | Biomarker discovery — DEG + enrichment (`bioresearch-biomarker-discovery`) || `causal` | Mendelian randomization (`bioresearch-causal-inference`) || `case-study` | Disease case study / validation run (`bioresearch-disease-case-study`) || `doctor` | Environment & reproducibility check (`bioresearch-environment-check`) |It is **intent translation, not reasoning**: it maps a request to an *existing* workflow and emitsthe matching CLI command. It does **not** generate, rank, or evaluate hypotheses, and uses **nomodel and no network** — the same input always yields the same route (deterministic).## Run```bashbioresearch route "find biomarkers for Parkinson's disease using GSE7621"bioresearch route "test the causal effect of BMI on type 2 diabetes with Mendelian randomization"```Output is JSON: `{route, confidence, matched_keywords, scores, rationale, suggestion}` plus asuggested CLI command. `confidence` is the share of all matched keywords belonging to the winningroute; an unmatched intent returns `route: "unknown"` with a suggestion list of available routes.## When to invokeAn agent should call this router *first* when it gets an ambiguous or free-form biomedical request,to decide which specialized skill/workflow to dispatch to. It is the entry funnel of the skillsystem — not a replacement for the analysis skills themselves.## NoteHonest scope: keyword-substring matching only. It will not understand paraphrases that containnone of the known keywords (it then returns `unknown` rather than guessing). Extend`bioresearch/router.py:ROUTE_KEYWORDS` to cover new phrasing.

Frequently asked questions