quick_wins

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

With no annotations, the description carries the full burden. It discloses the return behavior (queries at positions 4-15, high impressions, sorted by traffic opportunity) and adds explicit guardrails for analysis: 'Base your analysis ONLY on the data returned... Do not speculate about causes... If the data does not contain enough information... say so clearly.' This goes beyond a simple statement and helps the agent interpret results responsibly.

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 main purpose is front-loaded and clear. The additional IMPORTANT and PRESENTATION sections are structured with clear labels and add valuable guidance for an AI agent (avoid speculation, create dashboard-like visualizations). While somewhat long, every section serves a distinct purpose, so the length is justified.

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?

The tool has no output schema, so the description must convey what it returns. It provides a high-level return description (queries with positions and impressions) and gives enough context for selection and invocation. The analysis and presentation instructions further complete the picture, though the exact output structure is not specified.

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% for all three parameters (days, max_position, min_impressions), so the schema already provides sufficient semantics. The description mentions 'positions 4-15' which aligns with max_position but adds no new meaning beyond the schema, so a baseline 3 is appropriate.

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 what the tool does: 'Find keywords you're almost ranking for that could be pushed to page one. Returns queries at positions 4-15 with high impressions, sorted by traffic opportunity.' This provides a specific verb (find/returns), resource (keywords/queries), and scope (positions 4-15, high impressions), distinguishing it from siblings like ctr_opportunities or content_gaps.

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 purpose implies a use case (finding quick ranking wins), but the description does not explicitly state when to use this tool versus alternatives, nor does it mention exclusions. There is no reference to sibling tools or when not to use it.

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