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

Annotations already declare readOnlyHint, idempotentHint, and destructiveHint=false. The description adds value beyond them by disclosing that the call is free (no spend incurred), that the returned spend figure is session-scoped, and that it is compared against an environment-configured cap — behavioral context the annotations do not carry.

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?

Two sentences, both earning their place: the first front-loads what is returned, the second states when to call it. No filler, no repetition of the title.

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?

Zero parameters, an output schema that already documents the return shape, and annotations covering the safety profile — the description supplies the remaining needed context (cost-free, session-scoped spend, the limit it is measured against, and trigger conditions). Nothing an agent needs to invoke it correctly is absent.

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 tool takes zero parameters, so the baseline is 4 and there is no parameter semantics the description could add or omit. Nothing here is misleading or missing.

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?

States a specific verb (return) and resource (CaptchaNo account balance in USD), plus a second scope detail — session spend against the optional CAPTCHANO_MAX_SPEND_USD limit. It is unmistakably distinct from the siblings solve_captcha, get_task, and list_captcha_types, none of which report account state.

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?

Gives two concrete, actionable triggers: before a large batch of solves, and after an insufficient_balance error. That is clear contextual guidance, though it never names an alternative tool or states when not to call it, keeping it short of a full 5.

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?

Annotations already declare readOnlyHint, idempotentHint, destructiveHint=false, and openWorldHint, so the safety profile is covered; the description correctly reinforces 'read-only' rather than contradicting it. It adds genuinely new behavioral context beyond the annotations – a 10-minute result retention window and a ~5-second polling cadence – plus that the call is free. It stops short of describing failure states, such as what happens when the id has expired.

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 short sentences: what it does, when to call it (with polling guidance), then retention and cost traits. The action and the trigger are front-loaded and every sentence carries distinct information.

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 single-parameter polling tool with a full output schema, the description supplies everything an agent needs to decide to call it: the trigger, the poll interval, the retention window, and the cost. Return-value details are correctly left to the output schema.

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 100% and the single parameter is documented as 'Task id returned by solve_captcha.' The description reinforces the same provenance ('a task created by solve_captcha') but adds no format, length, or validity semantics beyond the schema, so 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 states a specific verb and resource: 'Fetch the current status and solution of a task created by solve_captcha.' It explicitly ties the tool to the sibling that creates the task, so an agent can distinguish get_task from solve_captcha without opening any schema.

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 gives explicit trigger conditions: call when solve_captcha returned status "solving" and poll roughly every 5 seconds, or use it to re-read an already received solution. It also names the sibling tool that produces the id, leaving nothing to inference.

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?

Annotations already establish readOnly, idempotent, non-destructive, and closed-world. The description adds genuinely new behavioral context beyond them: it is static, free, and makes no network call, which tells an agent it can call this speculatively without cost or latency. Missing only details like output size, which the output schema likely covers.

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?

Two sentences, no filler. The value proposition is front-loaded in sentence one and the usage trigger in sentence two, with the cost/no-network note compressed into a short trailing clause.

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 zero-arg, read-only discovery tool with an output schema and full annotation coverage, this description supplies everything an agent needs: what it enumerates, when to reach for it, and that calling it is cheap and side-effect free.

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 tool takes zero parameters, so per the rubric the baseline is 4. The description correctly introduces no parameter guidance, which is appropriate here, and instead points at where inputs live in the return value rather than in the call.

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 names a specific verb+resource ('List every captcha type solve_captcha supports') and immediately scopes what the listing contains (required/optional fields, solution field, sitekey discovery). This clearly separates it from solve_captcha, get_task, and get_balance, which are action/state tools rather than a discovery lookup.

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 states the trigger condition explicitly: 'Use when you are unsure which type a page uses or which arguments to pass.' That covers when to use it well. It stops short of an explicit when-not (e.g. skip if you already know the type), though the zero-arg, no-network framing makes the exclusion self-evident.

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?

Goes well beyond the annotations (readOnly=false, idempotent=false, openWorld=true) by disclosing wait behaviour ('up to ~50 s by default, polling automatically'), the graceful-degradation path (returns the task id), cost/billing semantics (billed to CaptchaNo, failed solves free), and token lifetime/one-use constraint ('valid for one submission and expires in about 2 minutes'). These are exactly the operational traits annotations cannot express, and they are consistent with the declared non-idempotent, non-readOnly profile.

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?

Front-loads purpose, then usage, then prerequisites, then per-type requirements, then timing/billing/pitfalls. Despite being a long description for a 12-parameter tool, every sentence carries distinct actionable content (a required-field rule, a timing limit, a billing rule, or a misuse warning) with no filler.

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?

With 12 parameters, an output schema present, and non-idempotent semantics, the description covers the gaps that matter: per-type required inputs, wait/timeout behaviour, the fallback to get_task, billing, and token reuse limits. Return values are deferred to the output schema, so nothing an agent needs to invoke this 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 description coverage is 100%, which sets a baseline of 3, but the description adds genuine cross-field conditional logic the schema cannot express per-property: which fields are required per type (recaptcha_*/turnstile → url + sitekey; datadome → url + challengeUrl + proxy; image → body). It also points to list_captcha_types for sitekey discovery, which the schema does not.

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?

States a specific verb and resource (solve a captcha) plus the deliverable ('return the token / cookie / text needed to pass it'), and enumerates the covered captcha families (reCAPTCHA v2/v3/Enterprise, Turnstile, DataDome, image). An agent can distinguish this from get_task, get_balance and list_captcha_types without opening a schema.

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?

Gives an explicit trigger condition ('Use when an authorised browser or HTTP automation is blocked by...'), names the alternative when the call outlives its window ('call get_task with it instead of solving again'), and adds an exclusion ('Do not call repeatedly for the same captcha'). Nothing about when to use or avoid this tool is left to inference.

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