solve_captcha

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

With no annotations provided, the description carries the full burden of behavioral disclosure. It states the internal flow ('CapSolver will create a task on its server, solve the captcha challenge, and return the solution token') and details the return payload structure for both success and failure. It does not mention costs, rate limits, or authentication, but the core behavior and error reporting are transparent enough for an agent to call it safely.

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 well-structured and front-loaded: it leads with purpose, then presents an organized Args section with one line per parameter, followed by a Returns section. Despite covering 14 parameters, it avoids fluff and each line adds information. The format is scannable and efficient for an agent to parse.

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 complexity (14 parameters, 3 required, multiple captcha types), the description covers everything an agent needs: what it does, when to use it, how each parameter behaves, and the exact return format. It also notes that an output schema exists (implied by 'Returns:'), though the schema itself is not provided here. For a token-based captcha solver, this is complete and self-sufficient.

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 input schema has zero description coverage, so the description must compensate for every parameter. It does so comprehensively: all 14 parameters are individually explained in the Args list, including formats for proxy and user_agent, defaults for timeout and polling_interval, and notes on auto-detection for version. This fully compensates for the schema's lack of descriptions.

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 clear, specific statement: 'Solve a captcha in token mode — no browser required.' It names the exact action, resource, and distinguishes from a browser-based flow, implying a contrast with the sibling tool solve_on_page without naming it. The purpose is unambiguous and the verb+resource pairing is precise.

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 gives an explicit condition: 'Use this when you only need the token to submit to a target website (e.g. via form POST or API call).' This clearly frames the intended context. However, it does not explicitly exclude alternatives like solve_on_page or detect_captchas, nor does it mention when not to use it, so it stops short of a full when/when-not comparison.

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