get_keyword_full_top

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

With no annotations provided, the description carries full burden for behavioral disclosure. It states the tool returns data (implying read-only) and specifies the scope (top-100 results), but doesn't mention rate limits, authentication needs, pagination behavior, data freshness, or error conditions. For a tool with 4 parameters and complex sorting options, this leaves significant behavioral gaps.

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 efficiently structured in two sentences: the first states the core function, and the second details the return metrics. It's front-loaded with the main purpose and avoids unnecessary words, though it could be slightly more concise by integrating the two sentences.

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 tool's complexity (4 parameters with nested sorting, no output schema, no annotations), the description is minimally adequate. It covers the purpose and return metrics but lacks behavioral context, usage guidelines, and output format details. The high schema coverage helps, but for a data retrieval tool with sibling alternatives, more contextual guidance would be beneficial.

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 the schema already documents all parameters thoroughly. The description adds minimal value beyond the schema by implying the 'keyword' parameter is for analysis and mentioning metrics that correlate with sortable fields, but doesn't explain parameter interactions or provide usage examples. Baseline 3 is appropriate when schema 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 clearly states the tool 'shows Google's top-100 search results for the analyzed keyword' and specifies it returns detailed domain metrics like visibility, organic/PPC keywords count, SDR score, and backlink metrics. It uses specific verbs ('shows', 'returns') and identifies the resource (search results/domains), but doesn't explicitly differentiate from sibling tools like 'get_keyword_top' or 'get_keyword_top_urls'.

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?

No guidance is provided on when to use this tool versus alternatives. The description doesn't mention prerequisites, exclusions, or compare it to sibling tools like 'get_keyword_top' (which might return less detailed data) or 'get_keyword_top_urls' (which might focus on URLs rather than domains). Usage is implied only by the tool's name and description.

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