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Data SL Consulting

Rechercher sur data-slconsulting.com

search_site
Read-onlyIdempotent

Recherche plein texte dans les pages et articles publiés de data-slconsulting.com (guides Pennylane, Power BI, MCP, IA et comptabilité, cas clients, fiches techniques). Renvoie titre, adresse et extrait ; lire ensuite une page avec fetch_page.

Input Schema

NameRequiredDescriptionDefault
typeNopage (offres, guides), post (articles) ou any.any
limitNoNombre maximal de résultats (1 à 20).
queryYesTermes recherchés, par exemple « API Pennylane » ou « FEC ».

Output Schema

NameRequiredDescriptionDefault
resultsYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A3.6/5.0
Behavior3/5

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

Annotations already declare read-only, idempotent, safe behavior, lowering the bar. The description adds the return shape (title, address, excerpt) and the fetch_page follow-up, but since an output schema already exists, the return details are partially redundant.

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-loaded with the core action and scope, then the workflow hint. The parenthetical content-type list is slightly verbose but still earns its place by clarifying scope.

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?

With rich annotations, full schema coverage and an output schema, the description is almost complete. It covers what, scope and next step; only sibling differentiation from get_offers is missing.

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 description coverage is 100%, so the schema fully documents query, type and limit including the enum and limits. The description adds no parameter-level meaning beyond that baseline, which is appropriate.

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?

States a specific verb (full-text search) and resource (published pages and articles of data-slconsulting.com), enumerating content types for scope. It names the natural follow-up sibling fetch_page, though it does not distinguish itself from get_offers.

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?

Clearly implies the search-then-read workflow by directing the agent to fetch_page next. It gives clear operational context but no explicit exclusions about when not to use it versus get_offers.

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

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