get_engine_answers

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

The description provides several useful behavioral details: answer text is capped at ~4000 chars per engine with a truncated flag, a not-found prompt returns availablePrompts, and there's an account/auth requirement (works on Starter and up, free trial has no MCP access). With no annotations provided, the description carries the full transparency burden and does disclose observable behaviors well. However, it doesn't describe the return structure or cite-position format beyond what's stated, leaving some 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 a single dense paragraph that front-loads the core purpose ('THE RECEIPTS behind the tracking grid') and packs in engine-scoping, output contents, truncation, prompt-sourcing, and access constraints. It's information-dense but coherent; every sentence earns its place. A lighter structural breakdown would improve readability, but nothing is wasted.

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?

For a 3-param tool with 100% schema coverage and no output schema, the description is thorough: it explains what's returned (answer text, brands cited, source URLs, citation position), the truncation cap, the prompt-matching fallback, and access-tier requirements. It maps cleanly onto siblings (get_visibility) and the input schema. The main gap is the absence of a sample output shape, which the description compensates for reasonably.

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% — brand, engine, and prompt each have descriptive help text in the schema, including engine key aliases and the prompt-sourcing hint. The description adds context by naming get_visibility's prompts[].prompt as the copy source and explaining the availablePrompts fallback. Both layers reinforce rather than repeat, keeping this dimension at baseline-plus.

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?

Purpose is stated with a specific verb and resource: it returns the stored answers/evidence ('REceipts') for a brand and one tracked prompt on the most recent day, including citation position. It clearly differentiates from get_visibility (tracking grid) by positioning itself as the underlying receipts/evidence layer. The scope (per prompt, optional per engine, most recent day) is explicit.

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 tells you when to use it (to get receipts behind the tracking grid, pulling actual answer text per engine) and how to prepare input (copy exact prompt text from get_visibility's prompts[].prompt). It also names the sibling tool the data comes from and clarifies access constraints (Starter+ required, free trial excluded). While it doesn't explicitly enumerate when NOT to use it, the alternative source (get_visibility) is referenced and the use-case context is clear.

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