ActableSite AI Crawler Monitor

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

Annotations already indicate safety (readOnlyHint, idempotentHint, not destructive). The description adds value by stating the scan is free and does not guarantee AI outcomes, and that private/local URLs are rejected. This provides helpful behavioral context beyond annotations.

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 two sentences: the first clearly states the action and output, the second provides a critical disclaimer. Every word serves a purpose, no wasted text.

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 one parameter, no output schema, and ample annotations, the description is nearly complete. It explains inputs, outputs, and limitations. A minor improvement would be to clarify the format of the returned evidence.

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 schema fully covers the single parameter (url) with a detailed description. The tool description adds no additional parameter information beyond what the schema provides, so baseline score of 3 is appropriate.

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 clearly states it runs a readiness scan for a public website and returns three specific signals. It distinguishes itself from sibling tools (e.g., check_ai_crawler_policy) by focusing on readiness scanning.

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 explains when to use (to run a scan) and includes a disclaimer about what it does not guarantee, providing contextual guidance. However, it does not explicitly state when not to use it or compare directly to siblings.

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 indicate readOnly, openWorld, idempotent, and non-destructive. The description adds critical context beyond annotations by stating that the result does not prove network access, authentic bot identity, crawling, indexing, citation, or ranking.

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 that are both necessary and informative. The first sentence defines the action and scope, the second sets expectations about limitations. No fluff.

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 simple tool with one parameter, no output schema, and strong annotations, the description covers the essential: which crawlers are checked, what the result represents, and key limitations. No gaps.

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 only parameter (url) is fully described in the input schema with the same wording found in the description (public HTTP/HTTPS, rejects private/local). Schema coverage is 100%, so baseline 3 is appropriate; the description adds no additional parameter meaning.

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 clearly states it checks the homepage robots.txt rule for eight named AI crawler tokens (OpenAI, Anthropic, Perplexity, Google AI). It also explicitly states what it does not prove, distinguishing it from sibling tools like audit_public_website.

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 provides clear context by mentioning the free result is complete and includes a bounded optional handoff to exact monitoring terms. However, it does not explicitly compare to alternative tools or state when not to use it.

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 include readOnlyHint, openWorldHint, idempotentHint, destructiveHint false. The description adds behavioral context: it is informational, returns specific offer data, and mandates user confirmation. No contradictions with annotations.

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: first lists all offer specifics, second gives usage directive. No unnecessary words, front-loaded with details, highly efficient.

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-param, no-output-schema tool, the description fully covers the offer content, behavioral intent, and required user action. Sibling tools are unrelated, so no further context needed.

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?

Input schema has zero parameters with 100% coverage. The description adds meaning by listing the output fields (price, scope, cadence, etc.), which is valuable since there is no output schema. Baseline 4 for zero-param tool.

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 explicitly states the tool returns the exact offer details (price, scope, cadence, etc.) and distinguishes it as informational. It is a specific verb-resource pair, clearly differentiated from sibling tools like get_full_report_offer.

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 provides clear guidance: present the offer and require explicit user confirmation before any purchase action. It implies when to use (informational) but does not explicitly exclude alternatives or compare to siblings.

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 indicate read-only, idempotent, non-destructive. Description adds crucial behavioral context: requiring user confirmation before proceeding, and discloses the exact content returned (price, deliverables, etc.). No contradictions.

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, concise and front-loaded: first sentence defines output, second sentence provides usage instruction. No wasted words.

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?

Completely describes what the tool returns and the required user interaction. No output schema, but description covers return values and context sufficiently.

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?

Zero parameters; schema already covers this. Description adds value by detailing the returned data, which is especially important given no output schema.

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?

Clearly states the tool returns the full report offer for ActableSite's paid 15-check repair report, specifying verb and resource. Differentiates from sibling tools which focus on auditing, crawling policy, and other offers.

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?

Explicitly instructs to present information to the user and require explicit confirmation before purchase, but does not explicitly state when to use versus alternative tools.

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, and destructiveHint, so the description adds value by explaining it is informational, cannot initiate checkout, and mentions material NPI limitations. No contradictions.

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 concise, using two sentences. The first sentence lists what the tool returns efficiently, and the second provides crucial usage instructions. Every sentence serves a purpose.

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 zero parameters, no output schema, and rich annotations, the description fully covers the tool's purpose, usage, and behavioral traits. It is complete for an informational tool.

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 has zero parameters, so baseline is 4. No parameter information is needed, and the description does not need to add anything beyond that.

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 clearly states the tool returns the current Practice Radar weekly-edition receipt, pricing options, included fields, delivery and cancellation paths, and limitations. It distinguishes from sibling tools like audit_public_website or get_crawler_watch_offer, which serve different purposes.

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 explicitly says this tool is informational, cannot open checkout or purchase, and requires explicit user confirmation before any separate purchase action. This provides clear when-to-use and when-not-to-use guidance.

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