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Resolve a title to a Leginova document

leginova_suggest
Read-onlyIdempotent

Autocomplete legal document titles from partial French names to return IDs and slugs, helping you find known documents without a full search.

Instructions

Autocomplete over titles: turns a partial name ("code du travail", "loi du pays 2021-2", "télétravail") into documents with their ids and slugs. Cheaper than a search when the target is known by name.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
queryYesPartial title in French
scopeNoall

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
suggestionsYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv1.0.0

TDQS

A4/5.0
Behavior3/5

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

Annotations already declare readOnly, idempotent, openWorld and non-destructive, so the safety profile is covered structurally. The description adds a cost/latency trait relative to search, which is genuinely useful, but says nothing about result caps, ranking, or pagination behavior for an autocomplete endpoint.

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 sentences, zero filler, with the core behavior and output shape front-loaded and the cost comparison as a trailing qualifier. Nothing could be cut without losing information.

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?

An output schema exists, so return values need not be explained, and the description still hints at the id/slug payload. Combined with annotation coverage, the definition is nearly sufficient; only the undocumented scope parameter leaves a small gap.

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

Parameters3/5

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

Schema coverage is 50%: 'query' is documented and the description's sample strings ('code du travail', 'loi du pays 2021-2', 'télétravail') usefully indicate expected phrasing, including accented French. However, the six-value 'scope' enum carries no explanation in either schema or description, so the description does not fully compensate for the coverage gap.

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 names a specific operation ('Autocomplete over titles') and states exactly what it returns (documents with their ids and slugs), which is enough to distinguish it from leginova_search without opening either schema. The examples of partial inputs make the resource concrete.

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?

It gives an explicit selection rule against a named sibling: use this 'cheaper than a search when the target is known by name'. That is clear routing guidance, but it stops short of stating when-not-to-use cases (e.g. broad or fuzzy discovery, where search should win).

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