gatefare.sample_response

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

Beyond the annotations (readOnlyHint, idempotentHint), the description discloses a 4 KiB UTF-8 size cap and the null-return behavior for older listings. These are operational constraints an agent needs to know and are not present in the annotations.

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?

Three sentences with zero fluff: purpose, usage/comparison, and constraints are each front-loaded. Every sentence earns its place and no redundant information is present.

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 simple read-only tool with 3 schema-covered parameters and no output schema, the description covers the essential behavioral details (size cap, null case) and gives a clear comparison workflow. Nothing an agent needs to invoke it correctly is missing.

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% and each parameter (slug, handle, urlName) already has a clear description. The tool description adds no extra parameter semantics, which is acceptable given the high schema coverage; the baseline of 3 applies.

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 uses a specific verb+resource ('Fetch the publisher-pasted representative response for an API') and immediately differentiates it from the sibling gatefare.get_api by contrasting the publisher-pasted sample with the captured example from probing. This makes the tool's unique role unmistakable.

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?

It explicitly instructs when to use this tool: compare the sample against gatefare.get_api's captured example to spot inconsistencies BEFORE paying. It also implicitly advises on fallback behavior by noting it returns null when no sample exists, giving the agent clear decision guidance.

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