page_hcaptcha

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

No annotations are provided, so the description carries the full behavioral burden. It does this well by disclosing the vision model (Cloudflare Workers AI GLM), the clicking mechanism ('humanized mouse'), the multi-round loop until a token appears, and credential sourcing from env vars or params. It does not describe failure or timeout behavior, but the core behavioral profile is unusually explicit.

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 dense but efficient: the purpose is front-loaded, and each clause adds useful detail about model, variants, clicking behavior, loop termination, credentials, and return shape. It is long, but not bloated, and the JSON return shape is cleanly included.

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 has no output schema and no annotations, the description compensates well by stating the return JSON, auth mechanism, loop cap, and challenge scope. The main gaps are the missing semantics of the required page_id/session_id parameters and lack of error-condition details, but the description is otherwise sufficient for correct invocation.

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 67%, with page_id and session_id completely undocumented, and the description does not clarify those two required parameters. It mostly repeats what the schema already says about cf_api_key, cf_account_id, and max_rounds (env defaults and default 4), adding little new meaning for parameter selection.

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 'HCAPTCHA SOLVER' and states a specific verb and resource: 'solve hCaptcha image challenges from the live page.' It goes beyond a generic captcha label by naming the host vision model and the specific challenge variants it handles, clearly distinguishing it from sibling tools like captcha_solve, page_captcha_ocr, and page_captcha_rotate.

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 implies usage through phrases like 'from the live page' and 'Handles ALL challenge variants,' which tells an agent this is the hCaptcha-specific solver. However, it never explicitly states when to prefer this tool over sibling captcha tools or when not to use it, leaving the routing decision to inference.

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