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mxmGrss

HAL MCP Publisher

by mxmGrss

search_structures

Read-only

Find research labs and structures in HAL by name or acronym. Returns matching results to locate the right structure for deposits.

Instructions

Recherche un laboratoire ou une structure de recherche dans HAL.

Args: query: nom ou acronyme de la structure (ex. 'LIP6', 'physique quantique'). rows: nombre de résultats (max 50).

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
rowsNo
queryYes

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.2.0

TDQS

A4.6/5.0
Behavior4/5

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

The readOnlyHint annotation already indicates a safe read operation daten The description adds useful behavioral context: the search targets HAL structures and rows is capped at 50 results. No mutation, auth, or unexpected side effects are implied.

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 short, front-loaded with the purpose, and uses a structured Args section for parameter details. Every sentence adds value with no redundant phrasing.

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?

For a simple read-only search tool with two parameters and an output schema, the description covers the search scope, parameter semantics, valid examples, and result limit. Nothing essential is left unexplained for an agent to invoke the tool correctly.

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?

Input schema description coverage is 0%, so the description fully compensates. It explains that query accepts names or acronyms with examples like 'LIP6' and 'physique quantique', and rows means number of results with a max of 50. This goes well beyond the bare schema definitions.

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 a specific action and resource: search for a laboratory or research structure in HAL. It distinguishes itself from sibling tools like search_publications and search_references by naming the target entity type.

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 makes clear that this tool is for finding structures/laboratories, which gives an agent context for when to choose it over publication or reference search tools. It does not explicitly list exclusions or alternative tool names, but the context is unambiguous.

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