get_keywords_similar

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

No annotations are provided, so the description must fully disclose behavioral traits. It fails to do so—it doesn't mention that this is likely a read-only operation (implied by 'get'), what data source it queries, potential rate limits, authentication needs, or the format of returned results. The description is too minimal to guide safe and effective use.

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?

The description is a single, concise sentence in French, which is front-loaded but under-specified. While it avoids verbosity, it's too brief to be helpful—every word should earn its place, but this provides minimal value. It's structured but lacks substance, making it inefficient for comprehension.

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?

Given the high complexity (27 parameters, low schema coverage, no annotations, no output schema), the description is severely incomplete. It doesn't explain the tool's behavior, output format, or key use cases. For a tool with extensive filtering capabilities, this minimal description fails to provide the necessary context for an agent to invoke it correctly.

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?

The input schema has 27 parameters with only 15% description coverage (only 'keyword', 'lineCount', 'order', and 'order_by' have descriptions). The tool description adds no parameter semantics—it doesn't explain what metrics like 'similarity', 'volume', or 'competition' mean, how filtering works, or the purpose of the many min/max parameters. This leaves most parameters undocumented, failing to compensate for the low schema coverage.

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 'Obtenir la correspondance des mots-clés' (Get the correspondence of keywords) is vague and tautological—it essentially restates the tool name 'get_keywords_similar' in French without specifying what 'correspondance' means (e.g., finding similar keywords based on metrics like similarity, volume, competition). It doesn't clearly distinguish this from sibling tools like 'get_keywords_related' or 'get_keywords_match', leaving the purpose ambiguous.

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 provides no guidance on when to use this tool versus alternatives. With many sibling tools for keyword analysis (e.g., 'get_keywords_related', 'get_keywords_match', 'get_keywords_find'), there's no indication of context, prerequisites, or exclusions. This lack of differentiation makes it hard for an agent to choose appropriately.

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