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Agent Harbor pay-per-call tools

AI-crawler access report

ai_crawler_access
Read-onlyIdempotent

Given a website domain, reports which AI crawlers may fetch its home page under its robots.txt (RFC 9309): GPTBot, OAI-SearchBot, ChatGPT-User, ClaudeBot, Claude-SearchBot, PerplexityBot, Google-Extended, Applebot-Extended, CCBot and more, each allowed or blocked, plus Googlebot, listed sitemaps, whether /llms.txt is published and page-level noindex/nosnippet, with fixes. Static check, no browser. Not charged if robots.txt cannot be read (no response, or a bot block). Costs $0.01 USDC per successful call (x402, eip155:8453); failures are not charged.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
domainYesBare domain, no scheme or path, e.g. mailchimp.com

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A4.4/5.0
Behavior5/5

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

Annotations cover the safety profile (readOnly, idempotent, non-destructive, openWorld), and the description goes well beyond them: it discloses the static/no-browser nature, the exact cost ($0.01 USDC via x402 on eip155:8453), and the non-charge conditions (unreadable robots.txt, no response, bot block, failures). That billing/edge-case behavior is exactly the kind of context annotations cannot express.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

A single dense sentence, front-loaded with what is reported before the pricing clause. Every clause carries information, though the run-on structure makes it slightly harder to scan than a two-sentence split would.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness5/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

With no output schema, the description carries the return-value burden and does so explicitly, listing each reported artifact plus the 'with fixes' note. Pricing and failure semantics are also covered, so an agent has everything needed to call it correctly.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema coverage is 100% and the schema already specifies the bare-domain format with an example, so the description adds no syntax or constraint detail beyond 'Given a website domain'. Baseline 3 is appropriate when the schema does the heavy lifting.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

States a specific verb and resource ('reports which AI crawlers may fetch its home page under its robots.txt'), enumerates the concrete outputs (crawler list, sitemaps, llms.txt, noindex/nosnippet, fixes), and cites the RFC. It is clearly distinguishable from siblings like site_audit or domain_verify.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines4/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

Gives clear context for when the tool applies ('Given a website domain', 'Static check, no browser') and implicitly scopes it to robots.txt/AI-crawler compliance checks. It does not, however, name a sibling alternative or state when not to use it versus site_audit.

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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