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

With no annotations supplied, the description carries the full burden and does well: it discloses the plan entitlement gate, the credit cost model, the cached-versus-live tradeoff, and that results are normally blurred but come unblurred here. It omits what happens when the caller is not on Pro/Agency (error vs. empty) and whether custom_prompts affects cost, but the core behavior is unusually well covered.

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?

Two dense sentences: entitlement and return payload first, cost/behavioral tradeoff second. No filler, no restatement of the title, and the most decision-relevant facts (plan gate, credits) are front-loaded.

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?

There is no output schema, so the description must explain the return shape; it names the content (competitor citation URLs, per-engine sub-queries) but not the structure or how the 'citation gap' analysis is represented, so an agent cannot anticipate the response. For a paid, 3-parameter analytical tool this leaves a meaningful hole.

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%, so the baseline is 3; the description earns an extra point by tying live_refresh=true to a concrete cost delta and clarifying that the cheaper path is served cached. It adds nothing about custom_prompts (what a 'buyer prompt' scan yields or how it interacts with the cached path), leaving one parameter purely schema-documented.

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 concrete return payload: unblurred third-party competitor citation URLs plus observed AI-engine sub-queries, naming the specific engine fields (Gemini webSearchQueries, ChatGPT web_search_call, Perplexity citations). It is clearly a retrieval tool, distinct from the sibling mutation/scan tools, though it never explains the 'gaps' half of its own name, so an agent must infer that dimension.

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?

Gives real decision context: it is gated to Pro/Agency plans and costs 1 credit cached versus 10 credits with live_refresh=true, which implies when to choose the cheap versus fresh path. It offers no explicit routing guidance to or away from the sibling tools (scan_domain_ai_readiness, check_brand_hallucinations), so usage is only implied.

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