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tc2fh
by tc2fh

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Find pathways, reactions, and molecules in Reactome using free-text search on names, synonyms, identifiers, and cross-references. Refine results by species or type.

Instructions

Free-text search across the Reactome knowledgebase (Solr-backed).

Matches pathways, reactions, physical entities, and reference molecules by
name, synonym, identifier, and cross-reference.

Args:
    query: Search text (e.g. "TP53", "glycolysis", "apoptosis").
    species: Optional species filter, e.g. "Homo sapiens".
    types: Optional comma-separated type filter, e.g. "Pathway,Reaction"
        or "Protein".
    rows: Max entries to return per type group (1-100).
    start: Zero-based offset into the result set for pagination.
    cluster: Group hits by type (recommended; keeps the response compact).

Returns:
    Dict with `entries` (flattened `{stId, name, type, exactType, species,
    referenceIdentifier, compartmentNames, databaseName, ...}` with HTML
    highlight markup stripped), `entriesCount` (total matches), and
    `resultTypes` (per-type match counts).

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
rowsNo
queryYes
startNo
typesNo
clusterNo
speciesNo
Behavior4/5

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

With no annotations, the description carries the full burden and does well: it reveals the Solr backend, return structure (entries, entriesCount, resultTypes), that HTML markup is stripped, and that 'cluster' groups hits by type. It does not mention errors, rate limits, or default sorting, but the core behavior is well disclosed.

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

Conciseness5/5

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

The description is front-loaded with a one-sentence summary, followed by a tightly structured Args list and a Returns explanation. Every sentence is informative and necessary; no filler or repetition. The length is appropriate for the tool's complexity.

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 that there is no output schema and no annotations, the description covers the tool's purpose, all parameters, return structure, and behavioral nuances. It is sufficiently complete for an agent to select and invoke the tool correctly, including pagination and response compaction.

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

Parameters5/5

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

The schema has zero descriptions for parameters, and the description fully compensates by explaining each parameter (query, species, types, rows, start, cluster) with examples and formatting expectations. It adds meaning beyond the bare schema, clarifying value ranges, defaults, and effects such as clustering.

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 explicitly states a specific action ('Free-text search') applied to a defined resource ('the Reactome knowledgebase'), and further specifies what is matched (pathways, reactions, physical entities, reference molecules) and by which criteria (name, synonym, identifier, cross-reference). This clearly distinguishes it from sibling tools that handle specific lookups or listings.

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

Usage Guidelines4/5

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

The description gives clear context for when to use the tool (general free-text searching across multiple entity types) with illustrative query examples. It does not explicitly mention alternatives or state when not to use it, but the scope is evident from the text. This matches 'clear context, no exclusions'.

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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