image_search_quick_wins

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

The description discloses key behavioral traits like the CTR baseline calibration and the constraint to avoid speculation about causes. Since no annotations are provided, the description carries full burden, and it covers the analysis posture well. However, it does not mention whether the tool mutates data, requires authentication, or has rate limits, leaving some 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 well-structured with a clear purpose statement followed by behavioral instructions and presentation guidelines. It is front-loaded with the core function. However, the presentation instructions are somewhat lengthy and could be shortened by referencing a standard output format, but they add significant value for agent usage.

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 moderate complexity (3 parameters, no output schema), the description provides sufficient context for an agent to use it correctly. It covers what the tool does, how to interpret results, and how to present them. The lack of output schema is partially compensated by the detailed presentation guidance. However, it could mention if the data is aggregated by query or by page for completeness.

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 baseline is 3. The description does not add additional semantic meaning beyond what the schema provides for the three parameters (days, max_position, min_impressions), as it focuses on the tool's overall purpose and output usage rather than parameter details.

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 finds image-search queries ranking at positions 4-15 with high impressions, sorted by estimated traffic gain. It specifies the verb 'find' and the resource 'image-search queries', with explicit ranking and sorting criteria that distinguish it from siblings like 'compare_web_vs_image' or 'image_impressions_no_clicks'.

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 clear context on when to use this tool, including the use of an image-search CTR baseline and instructions to base analysis only on returned data. However, it does not explicitly say when not to use it or name alternatives, leaving some room for ambiguity among the many image-related sibling tools.

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