metabo-idmapper

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exact_match

Matches metabolite names to standard database identifiers using exact name lookup, auto-accepting confident matches for immediate assignment.

Instructions

MetaboAnalyst batch name->ID. Exact DB-name matches are a lookup, not a judgement: with auto_accept_exact they are committed at confidence M1 (KEGG/HMDB/structure by what resolves); everything non-exact stays pending for the LLM.

Tool call template

Replace each placeholder with a value matching the input schema. Only required parameters are included; add optional parameters as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {
      "workdir": "<workdir>"
    },
    "name": "exact_match"
  }
}

Input Schema

Name	Required	Description	Default
`workdir`	Yes
`feature_ids`	No
`auto_accept_exact`	No

Schema Changelog

Changes observed during successful MCP inspections.

First observedv0.0.1Jul 28, 2026

TDQS

B3.3/5.0

Behavior4/5

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

With no annotations, the description discloses key behaviors: exact matches are committed at confidence M1, non-exact items remain pending, and auto_accept_exact controls automatic acceptance. This adds good context beyond a basic purpose statement.

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 sentences front-load purpose and then detail behavior. No wasted words, though the structure could be enhanced with a brief note on parameters.

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?

Lacking output schema, the description does not mention what the tool returns. It also fails to explain two of three parameters. For a batch lookup tool with moderate complexity, more detail is needed to be fully self-contained.

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 coverage is 0%, so description must compensate. It explains the auto_accept_exact parameter's effect but does not explain workdir (required) or feature_ids (optional). Only one of three parameters gains clarity.

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

Purpose4/5

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

Description clearly states it performs exact name-to-ID matching in MetaboAnalyst, distinguishing it from a 'judgement'. However, it does not explicitly differentiate from sibling tools like search_synonym or verify_candidate, though the exact-match focus is implied.

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?

Implies usage for exact DB-name matches only, and that non-exact items stay pending for the LLM. Provides some guidance on the auto_accept_exact flag but does not explicitly state when not to use the tool or name alternatives.

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