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search_interactions

Read-only

Find regulatory interactions by regulator or target name/ID, with filters for species, dataset, confidence, score, and entity type.

Instructions

精确查询起点或终点;至少给出一端名称/已解析 ID。完整性仅针对当前名称候选查询,别名不保证穷尽。

Input Schema

NameRequiredDescriptionDefault
limitNo
offsetNo
datasetYes
refreshNo
speciesYes
min_scoreNo
confidenceNoall
target_typeNoall
target_symbolNo
regulator_typeNoall
regulator_symbolNo
target_entity_idNo
regulator_entity_idNo

Output Schema

NameRequiredDescriptionDefault
dataYes
errorNo
statusYes
coverageYes
warningsNo
provenanceYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

C2.9/5.0
Behavior3/5

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

Annotations already declare readOnlyHint=true and openWorldHint=true, so the safety profile is covered externally. The description adds a genuinely useful caveat that alias coverage is not exhaustive and completeness is bounded to the current name candidates, but says nothing about pagination (limit/offset), the effect of refresh, or what dataset=complete costs.

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?

Two dense clauses with no filler, and the anchoring requirement is front-loaded ahead of the completeness caveat. Brevity is close to over-terse given the parameter surface, but there is no wasted sentence.

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

Completeness2/5

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

An output schema and annotations exist, so return shape and safety need not be restated, but for a 13-parameter search tool with zero schema descriptions the definition is far too thin — an agent cannot tell what confidence, min_score, dataset, or the type filters do.

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

Parameters2/5

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

Schema description coverage is 0% across 13 parameters, so the description carries the full burden and largely fails: it only gestures at the symbol/entity_id pair while dataset, confidence, min_score, target_type, regulator_type, refresh, limit, and offset remain unexplained anywhere.

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

Purpose3/5

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

The description states that it performs a precise query anchored on a start or end point (i.e., regulator or target), and that at least one end must be supplied by name or resolved ID. However, it uses generic '起点/终点' phrasing rather than the schema's regulator/target vocabulary, and it does not differentiate itself from siblings like get_interaction_evidence or get_neighbors.

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

Usage Guidelines3/5

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

It gives a clear precondition (at least one of the two ends must be specified by symbol or resolved ID), which implies usage context. It offers no explicit when-not guidance and never names an alternative tool for the cases this one does not cover.

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