lu_dp_search_guidelines

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

No annotations are provided, so the description carries full burden. It doesn't disclose return format, pagination behavior, or whether results are ranked by relevance. It does clarify the query must be in French (a useful operational constraint) and lists topic coverage areas, but doesn't describe what happens for empty/no-match searches. With no annotations, this is adequate but not rich.

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?

Single sentence, front-loaded with the primary verb and resource, followed by concrete topic examples. Zero waste. Could arguably earn a 5, but the sentence is slightly dense on examples which could be trimmed.

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 search tool with well-documented params and no output schema, the description covers the main axes: what it searches, the language requirement, and the topic scope. However, it doesn't clarify the relationship to lu_dp_get_guideline (does search return full docs or IDs for subsequent retrieval?) and lacks any notes about return structure or limits given no output schema exists.

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 description coverage is 100%, so all four parameters (query, type, limit, topic) are already documented in the schema. The description adds marginal value by explaining query should be in French and giving example values, and implicitly links the topic parameter to the listed domains. Baseline 3 is appropriate since the schema already does the heavy lifting.

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 uses a specific verb ('Search') with a clear resource ('CNPD guidance documents') and lists concrete example topics (vidéosurveillance, cookies, sous-traitance). It distinguishes from sibling tools by positioning this as the search entry point vs. lu_dp_get_guideline (retrieval) or lu_dp_list_topics (topic enumeration), though it doesn't explicitly name the sibling to differentiate.

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?

The description implies this is for searching guidance documents vs. lu_dp_search_decisions which presumably searches decisions, and mentions French queries explicitly. However, it doesn't state when to use this vs lu_dp_list_topics or lu_dp_get_guideline, nor any exclusions/alternatives. Usage context is inferred rather than explicit.

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