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

Annotations already mark it as read-only, and the description adds valuable behavioral details such as matching fields (name, description, category, tags), relevance sorting, and cursor-based pagination. No contradiction with annotations.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

Three short sentences, each conveying essential information: purpose, usage context, and pagination. No redundant wording; information density is high.

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

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

For a simple search tool with two well-documented parameters and good annotations, the description covers what it does, when to use it, and pagination. It doesn't describe the result item structure, but in the absence of an output schema and given sibling tools, this is an acceptable gap.

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

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

Schema coverage is 100%, so the baseline is 3. The description goes beyond the schema by explaining the cursor's role in pagination ('Résultat paginé par curseur') and clarifying that query accepts natural language terms, adding practical meaning.

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

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

The description clearly states a specific action: 'Recherche les composants pertinents' with a defined search mechanism over name, description, category, and tags, sorted by relevance. It strongly distinguishes itself from sibling tools like list_components (likely a full listing) and get_component (likely by ID) by focusing on free-text search.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

Provides explicit usage direction: 'À UTILISER quand on cherche un composant par fonction ou mot-clé' with concrete examples. It doesn't explicitly mention when NOT to use it or name alternatives, but the context is clear and practical.

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