Check AI crawler robots.txt policy and monitor public-site policy, sitemap, and llms.txt changes.
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Average 4.5/5 across 5 of 5 tools scored.
The first two tools (audit_public_website, check_ai_crawler_policy) are clearly distinct active scanning tools. The three 'get_*_offer' tools all return pricing information but for different products (crawler watch, full report, practice radar), making them distinguishable by product name.
All tools follow a consistent verb_noun pattern using snake_case: 'audit_public_website', 'check_ai_crawler_policy', and three 'get_*_offer' tools. The verbs 'audit', 'check', and 'get' clearly indicate the action, and the nouns precisely describe the target.
With 5 tools, the server is well-scoped for its purpose: two core monitoring actions (audit and policy check) and three informational offer tools for different products. This covers the essential functionality without unnecessary bloat.
The server covers scanning and policy checking but lacks tools to actually purchase or activate monitoring services after showing offers. Users must leave the MCP to complete transactions, creating a dead-end for the offer flows.
audit_public_websiteAudit public website readinessARun ActableSite's free three-signal readiness scan for a public website. Returns observable evidence for business identity, semantic reading path, and explicit action path. This does not guarantee AI crawling, indexing, citation, ranking, recommendation, traffic, or revenue.
| Name | Required | Description | Default |
|---|---|---|---|
| url | Yes | Public HTTP or HTTPS website URL. Private, local-network, authenticated, and restricted targets are rejected. |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint, idempotentHint, and openWorldHint, so the description adds value by detailing the observable evidence and explicitly stating what the tool does NOT guarantee (AI crawling, ranking, etc.), which is good behavioral context.
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 short sentences that immediately convey the tool's function and limitations. No redundant words, perfectly front-loaded.
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 simple tool (1 param, no output schema) and rich annotations, the description covers the key aspects: what the scan does, what it returns, and its limitations. Could have included more detail on the return format, but sufficient for the tool's complexity.
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 has 100% coverage for the single parameter 'url', with a clear description including allowed and rejected targets. The description does not add extra meaning, so baseline 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?
Clearly states it runs a three-signal readiness scan for a public website, specifying the three signals (business identity, semantic reading path, explicit action path). Distinguishes from siblings like check_ai_crawler_policy and get_crawler_watch_offer which have 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?
States when to use: for a free readiness scan of a public website. Implicitly differentiates from siblings through description content, but lacks explicit when-not-to-use or alternative tool references.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
check_ai_crawler_policyCheck AI crawler robots.txt policyACheck the homepage robots.txt rule for eight named OpenAI, Anthropic, Perplexity, and Google AI crawler tokens. The free result stays complete and includes a bounded optional handoff to exact monitoring terms. Results describe robots policy only and do not prove network access, authentic bot identity, crawling, indexing, citation, or ranking.
| Name | Required | Description | Default |
|---|---|---|---|
| url | Yes | Public HTTP or HTTPS website URL. Private and local-network targets are rejected. |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already indicate readOnly, idempotent, and non-destructive. The description adds significant context by clarifying limitations (does not prove crawling, indexing, etc.) and the handoff capability, exceeding what annotations provide.
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 concise sentences with no fluff. First sentence states the action, second sets expectations. Every sentence is valuable.
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 simple input (one parameter) and rich annotations (readOnly, idempotent), the description is complete, covering purpose, limitations, and optional handoff. No output schema 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?
The single parameter is described in the schema with clear constraints (public URLs only, private rejected). The description adds minimal extra meaning beyond implying the URL should be the homepage, but schema coverage is high.
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 checks homepage robots.txt rules for eight named AI crawler tokens. It distinguishes from siblings like audit_public_website by focusing specifically on robots.txt policies for AI crawlers.
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 sets expectations by stating what the tool does not prove (network access, authentic bot identity, etc.) and mentions a bounded optional handoff to monitoring terms. However, it does not explicitly name alternative tools for specific use cases.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
get_crawler_watch_offerGet the Crawler Watch monitoring offerAReturn the exact $9 monthly price, one-site scope, 15-minute check cadence, two-check confirmation, delivery and cancellation paths, and synthetic-check limitations. This tool is informational: present the offer and require explicit user confirmation before any separate checkout or purchase action.
| Name | Required | Description | Default |
|---|---|---|---|
No parameters | |||
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Beyond annotations (readOnly, idempotent, etc.), description adds that it returns specific offer components and requires user confirmation, enriching behavioral context.
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 concise sentences cover purpose and guidelines without waste, front-loading key return details.
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?
Despite no output schema, description fully enumerates returned fields (price, scope, cadence, etc.) and usage context, making it 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?
No parameters exist; schema coverage is 100% so baseline is 4. No additional parameter info needed.
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?
Description clearly states it returns specific offer details (price, scope, cadence) and distinguishes from sibling tools like get_full_report_offer or get_practice_radar_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?
Explicitly states the tool is informational and requires user confirmation before any purchase action, guiding the agent on when and how to use it.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
get_full_report_offerGet the full repair report offerAReturn the exact one-time price, deliverables, delivery path, checkout URL, support contact, and limitations for ActableSite's paid 15-check repair report. Present this information to the user and require explicit user confirmation before opening checkout or attempting any purchase.
| Name | Required | Description | Default |
|---|---|---|---|
No parameters | |||
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations indicate read-only, idempotent, non-destructive. Description adds that user confirmation is required before proceeding to checkout, a behavioral trait 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?
Two concise sentences covering what the tool returns and the mandatory user confirmation step. No unnecessary 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?
Description lists the types of information returned (price, deliverables, etc.), compensating for lack of output schema. Sibling tools are unrelated, so tool stands alone. Slightly lower because return format is unspecified.
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?
No parameters exist; schema coverage is 100%. Baseline for zero parameters is 4, and description adds no parameter info, which 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?
Description clearly states the tool returns specific offer details (price, deliverables, etc.) for ActableSite's paid repair report, and distinguishes from sibling tools like audit_public_website 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?
Description implies use when presenting the repair report offer to the user and requiring confirmation before purchase. It does not explicitly list when not to use, but context with sibling tools makes it clear.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
get_practice_radar_offerGet the Practice Radar data offerAReturn the current Practice Radar weekly-edition receipt, public sample, exact $19 one-time and $39 monthly options, included fields, delivery and cancellation paths, and material NPI limitations. This tool is informational: it cannot open checkout or purchase. Present the offer and require explicit user confirmation before any separate checkout or purchase action.
| Name | Required | Description | Default |
|---|---|---|---|
No parameters | |||
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint, openWorldHint, idempotentHint, and destructiveHint. The description adds valuable context by specifying what data is returned and that it cannot trigger purchases, which aligns with and supplements the annotations without contradiction.
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, first listing the returned content and second giving usage guidance. Every word earns its place, with no redundancy or 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?
For a simple tool with no parameters and no output schema, the description covers purpose, usage guidelines, behavioral constraints, and even material NPI limitations, making it fully sufficient for an agent to understand and use the tool correctly.
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?
With zero parameters, the baseline is 4. The description adequately explains that the tool returns a static offer, and since there are no parameters, no further meaning is needed.
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 returns the current Practice Radar weekly-edition receipt, public sample, pricing options, included fields, delivery/cancellation paths, and NPI limitations. It distinguishes itself from sibling tools like 'get_crawler_watch_offer' by specifying the unique resource (Practice Radar).
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 states it is informational and cannot open checkout or purchase, advising to require user confirmation before separate checkout. However, it does not name specific alternative tools for checkout, so there is slight room for improvement in directing agents to the correct follow-up tool.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
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