Check AI-search readiness (ChatGPT, Perplexity, Google AI Overviews)

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

Annotations already cover read-only/destructive/open-world, and the description adds genuinely new operational context: execution happens on the caller's own Apify account via APIFY_TOKEN, billing is pay-per-event through Apify, and the server itself charges nothing. It also discloses the async escape hatch (status 'running' plus a runId) rather than failing, which an agent must plan for.

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 dense with information: the first front-loads scope, the second front-loads the cost/ownership model and the async fallback. No restatement of the title and 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?

An output schema exists so return values needn't be spelled out, yet the description still summarizes them (readiness score plus prioritised fixes). Combined with billing, auth source, timeout behavior, and the follow-up tool reference, nothing essential for a correct first call 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%, so all four parameters — including the maxCostUsd spend cap and waitSecs timeout behavior — are already documented in the schema. The description adds billing framing but no parameter-level semantics beyond what the schema provides, so the baseline 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?

States a specific verb ('Checks whether AI assistants and AI search engines can find, read and cite') plus the exact artifacts inspected (robots.txt for GPTBot/ClaudeBot/PerplexityBot/Google-Extended, llms.txt, schema.org, sitemap). This is clearly distinguishable from siblings like audit_accessibility_wcag or scan_speed_and_revenue 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?

The listed checks establish the use case clearly and the description routes the agent to get_audit_results when the wait window expires ('the scan keeps going; use get_audit_results'). It does not, however, say when to prefer this over overlapping siblings such as full_website_audit, so there is no explicit when-not guidance.

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