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

Annotations already declare readOnlyHint=true, idempotentHint=true, destructiveHint=false, and openWorldHint=false, so the 'Read-only' sentence is largely redundant confirmation. The one addition is that the tool hands back an actionable payload (an add_keywords call or a negative to review), which tells the agent the output is a proposed action rather than raw data — useful but thin for a multi-signal analysis tool.

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 core sentence is front-loaded and information-dense, but the 'Find money left on the table' framing is marketing flavor, and the trailing 'Tools revision: d80f65c0.' is pure metadata noise that dilutes a short description.

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?

An output schema exists, so the return shape need not be re-explained, and the description covers the analytical purpose well. However, for a tool with five undocumented parameters — including a lookback window and a result cap that change the answer — omitting any parameter guidance leaves a real gap.

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 0% across five parameters, so the description needed to carry the burden and does not. It never explains the time window (days, default 30), the meaning of detail=summary vs full, the render modes, or what max_findings=25 does to result truncation — all of which materially affect the call.

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?

States a specific verb and resource plus three concrete finding categories (non-keyword converting search terms, converting keywords losing impression share, blocking negatives), which lets an agent understand what the tool produces. It never names a sibling such as analyze_search_terms, analyze_waste, or get_keyword_ideas, so differentiation is only inferable from the finding types.

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?

Usage is implied by the framing ('find money left on the table') and by the note that it returns the add_keywords call or the negative to review, suggesting a pre-optimization workflow. There is no explicit statement of when to prefer this over analyze_search_terms or analyze_waste, and no prerequisites or exclusions are given.

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