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

The annotations already declare readOnly and idempotent, and the description confirms no network call occurs. It adds context about the stub vs. live server behavior, which is useful, but doesn't mention error handling or rate limits. Still, it's a read-only discovery tool, so the transparency is sufficient.

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 somewhat repetitive, with the same example snippets appearing in both the description and the schema, and the bullet-point format repeats the same information in slightly different wording. It could be tightened without losing clarity, but it's not excessively long.

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?

Given the tool's simplicity (one parameter, no output schema), the description covers the essential aspects: purpose, usage, and parameter behavior. The return type is mentioned in the schema description, and the description adds the distinction between stub and live server. It feels complete for the intended scope.

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 schema already describes the 'code' parameter and gives an example, achieving 100% coverage. The description adds multiple concrete examples (filter by category, search summary, find by path) that go beyond the schema's single example, providing practical guidance on how to construct the function. This elevates it above the baseline.

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 searches the API catalog for endpoint discovery, with a specific verb and resource. It also distinguishes itself from the sibling tool 'xquik' by noting that 'explore' is for discovery while 'xquik' fetches live data.

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?

Explicitly states when to use (before 'xquik', when user asks about API capabilities) and when not to use (for live data, if endpoint parameters are already known). This gives clear routing guidance.

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

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

Beyond the annotations (destructiveHint=true, openWorldHint=true), the description adds rich behavioral context that the annotations cannot convey: the bounded sandbox, no local file or arbitrary host access, approval-required durable writes, 402/429/404 error semantics, pagination via has_more/next_cursor, and the server-side authentication model. No contradiction with annotations — the write/approval framing aligns with destructiveHint=true and the sandbox stays consistent with openWorldHint=true.

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 long but excellently structured with clear headers, scannable bullets, and a front-loaded purpose statement. Every section (when to use, behavior, error handling, format, examples) earns its place given the tool's complexity — a proxy over 120 routes. It is slightly more verbose than strictly necessary but the organization compensates.

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 complex proxy tool with no output schema, the description covers everything an agent needs: when to call, approval requirements, behavioral constraints, error handling per status code, pagination semantics, input format, and realistic examples. The only minor gap — the absence of an output schema — is offset by explanation of return behaviors like has_more/next_cursor and durable actions.

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 schema alone documents the single 'code' parameter with an example. The description adds genuine value beyond that with the 'Input format' section (bounded function signature for xquik.request with method/body/query) and three concrete examples covering search, user lookup, and POST-after-approval. This exceeds the baseline 3 for high-coverage cases.

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 opens with a specific, differentiated statement: "sends approved requests across 120 catalog routes" and immediately distinguishes the package stub ("returns setup guidance only") from the live tool. It names the sibling 'explore' as what it is not, so an agent can tell them apart without opening schemas.

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 contains explicit 'When to use' and 'When not to use' sections. It states to call it after 'explore' identifies the endpoint, when not to (if endpoint unknown), and covers approval gates for private reads, metered operations, and writes. It also names the alternative tool and directs the agent away from it appropriately.

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