make_siteverify_requestReturn a server-side fetch example for redeeming a captcha.cc proof token exactly once.
| Name | Required | Description | Default |
|---|---|---|---|
| secret_env_var | No | CAPTCHA_CC_SECRET_KEY | |
| proof_token_expression | No | req.body.proofToken |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint=true and idempotentHint=true. The description adds valuable context by clarifying it 'returns an example' rather than performing an actual request, and emphasizes 'exactly once' redemption. This goes beyond the structured annotations and helps the agent understand the tool's output nature.
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 sentence that is front-loaded with the action ('Return a server-side fetch example') and includes only essential detail ('redeeming a captcha.cc proof token exactly once'). Every word earns its place, with no redundancy.
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 and the description clearly conveys its purpose and output nature. However, the lack of parameter documentation is a notable gap. The presence of an output schema is not required, but without it, the description could still explain what the returned example looks like or provide parameter context, making it only 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?
Schema description coverage is 0% and the description does not explain the parameters (secret_env_var, proof_token_expression) or their roles. While the parameter names offer some hints, the description fails to compensate for the missing schema descriptions, leaving the agent without clear guidance on how to use the two parameters.
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 ('Return') and identifies a clear resource (server-side fetch example for redeeming a captcha.cc proof token exactly once). It distinguishes itself from sibling tools (create_challenge, make_widget_snippet) by focusing on server-side verification code generation.
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?
No guidance is provided on when to use this tool versus alternatives. It doesn't mention scenarios like server-side verification needs or exclude client-side options, and sibling tools are not referenced. The usage context is implied from the purpose but not explicitly stated.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Add one secure layer between your agents and this server.
Each tool targets a clearly distinct stage of captcha integration: creating a challenge, generating a client-side widget snippet, and providing a server-side verification example. No two tools overlap in purpose, so an agent can reliably select the right one.
Tool names follow a verb_noun pattern with clear verbs ('create', 'make'), but two tools use 'make' while one uses 'create', which is a minor inconsistency. However, the pattern is still predictable and readable.
Three tools is well-scoped for a captcha integration helper server, covering the essential client, server, and challenge creation aspects without unnecessary bloat.
The tool set covers the core workflow: create a challenge, get a widget snippet, and verify a proof token. Minor gaps like challenge status or debugging tools are absent, but the essential lifecycle is complete for typical integration tests.