pipeline_validate

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

With no annotations provided, the description carries full responsibility for behavioral transparency. It does not disclose whether the tool is read-only, what it returns (e.g., a score, pass/fail, or report), any side effects, or prerequisites. 'Validate' implies analysis but provides no detail on the operation's behavior.

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 concise and well-structured: a clear one-line purpose, a parameter example, and a usage directive. No unnecessary words or repetition.

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 is simple (one parameter, no output schema), but the description omits the return value or output format, which is essential for a validation tool. It covers input and usage context adequately but leaves the outcome ambiguous, making it minimally complete.

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?

The description adds meaningful format guidance for the single parameter with a concrete JSON array example ('["B0XXX","B0YYY",...]'). This goes beyond the schema's bare string type, helping the agent construct valid input.

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's function with a specific verb ('Validate') and object ('pipeline recall') against a list of known-good ASINs. This distinguishes it from sibling tools like cache_query or asin_score, which serve different purposes.

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 an explicit 'USE THIS TOOL WHEN' clause indicating the intended use case: measuring how well the cache and pipeline cover existing products. It gives clear context for when to use it, though it does not explicitly mention alternatives or exclusions.

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