Skip to main content
Glama

mass_match_candidates

Computes neutral monoisotopic mass windows from given m/z and adduct for metabolite candidate matching via subsequent database searches.

Instructions

m/z + adduct -> neutral monoisotopic mass windows (weak evidence). Hand the window to search_synonym / a DB search; never accept a mass-only hit as primary.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
mzYes
adductsNo
tol_ppmNo
Behavior3/5

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

No annotations are provided, so the description should convey behavioral traits. It mentions 'weak evidence' indicating the tentative nature of the output, but does not disclose other behaviors such as whether it is read-only, requires authentication, or has rate limits. The description is minimal but not misleading.

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?

Two concise sentences clearly state the transformation and usage guidance with no superfluous words. The key information is front-loaded.

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

Completeness4/5

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

For a tool with 3 parameters and no output schema, the description covers the core purpose and usage. However, it omits details about the output (e.g., return format, windows) and how tolerance influences the result, which a user might need for proper invocation. Still, it is complete enough for its simple role.

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?

The description explains the roles of m/z and adduct (to compute mass windows) but does not explain the 'tol_ppm' parameter or the format of 'adducts' (e.g., strings). Schema coverage is 0%, so more detail is needed to compensate, but the description only partially covers the parameters.

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 the transformation (m/z + adduct -> neutral monoisotopic mass windows) and labels it as weak evidence. It distinguishes from siblings by specifying that the result should be handed to search_synonym or a DB search, making the tool's role unambiguous.

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?

Explicitly states when to use this tool (to generate mass windows) and when not to rely on it ('never accept a mass-only hit as primary'), also directing to siblings (search_synonym, DB search). This provides clear usage guidelines.

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

Install Server

Other Tools

Latest Blog Posts

MCP directory API

We provide all the information about MCP servers via our MCP API.

curl -X GET 'https://glama.ai/api/mcp/v1/servers/Wooyoung-kim91/metabo-idmapper'

If you have feedback or need assistance with the MCP directory API, please join our Discord server