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Find Drug Repurposing Candidates

find_drug_repurposing_candidates
Read-onlyIdempotent

Discover drug repurposing opportunities by ranking approved and trial-stage drugs based on disease-target genetic evidence and clinical phase.

Instructions

Rank existing clinical-stage drugs as repurposing candidates for a disease.

Surfaces approved or trial-stage drugs whose target carries genetic/association evidence for the disease — i.e. drug-repurposing hypotheses. For the full approved-plus-pipeline drug picture of a disease (not only repurposing candidates), use map_disease_drug_landscape instead.

How it works: take the top target_limit Open Targets evidence-scored targets for the disease; for each, fetch its ChEMBL drugs at or above min_phase; drop duplicate molecules; rank by composite_repurposing_score = OT evidence score × (max ChEMBL phase / 4). Ranking uses clinical and association evidence only — no protein structure.

Returns a JSON record whose candidates list holds up to 20 drugs (each with ChEMBL ID, name, max phase, target gene/UniProt, OT evidence score, composite score, and mechanism), plus the candidate count and the methodology string. Returns an empty candidates list with a message when the disease has no Open Targets associations. The composite score is a prioritisation aid, not an efficacy prediction — validate mechanistically before acting on it.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
paramsYes

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Behavior5/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

The description goes well beyond the annotations (readOnlyHint, openWorldHint, idempotentHint) by detailing the ranking algorithm, scoring formula, candidate list size, empty result behavior, and caveats about the composite score. This provides comprehensive behavioral insight.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is well-structured and front-loaded with the core purpose. While it is relatively long, every sentence adds value given the tool's complexity. There is no redundancy, so it earns a 4.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness5/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the tool's complexity and the presence of an output schema, the description is remarkably complete. It covers purpose, usage, algorithm, return structure, edge cases, and caveats, ensuring the agent has all necessary context.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The input schema already provides clear descriptions for all three parameters with defaults and constraints. The tool description does not add new parameter-level semantics; it only references parameters in the algorithm. With schema coverage at 0% (description adds no param info), the baseline of 3 is appropriate.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states it ranks clinical-stage drugs as repurposing candidates for a disease, and explicitly distinguishes from the sibling tool map_disease_drug_landscape. This meets the criteria for a specific verb+resource+scope with sibling differentiation.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines5/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description provides explicit guidance: use this tool for repurposing candidates; for the full drug picture use map_disease_drug_landscape instead. This qualifies as explicit when/when-not/alternatives.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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