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llms.txt Compliance Checker

llms-txt-auditor
Read-only

Give it a domain. It checks whether the site publishes a valid llms.txt / llms-full.txt (the emerging AI-crawler-friendly-docs convention) and whether robots.txt blocks GPTBot, ClaudeBot, Google-Extended, PerplexityBot and 5 other AI crawlers. llms.txt-first, no browser, no LLM, no API key. — $0.01/call, x402 (USDC on base).

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
itemsYesList of domains to audit for llms.txt presence and AI-crawler robots.txt policy.
maxConcurrencyNoHow many domains to audit in parallel.

TDQS

A4.1/5.0
Behavior4/5

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

Annotations already declare readOnlyHint=true and destructiveHint=false, so safety is covered. The description adds useful behavioral context beyond annotations: it is 'llms.txt-first', uses no browser, no LLM, no API key, and costs $0.01/call via x402. This helps the agent understand operational constraints without contradicting annotations.

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?

The description is four sentences, each contributing value: usage instruction, core functionality, operational constraints, and pricing. It is front-loaded with 'Give it a domain' and not overly verbose, though the payment detail could be considered extraneous for tool selection.

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

Completeness4/5

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

Given the tool's low complexity (2 params, no output schema), the description adequately covers purpose, constraints, and cost. However, it does not describe the return format (e.g., per-domain results), which would be helpful since there is no output schema. This is a minor gap for an otherwise complete description.

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 description coverage is 100%, with clear descriptions for both 'items' (domains to audit) and 'maxConcurrency' (parallel audits). The description does not add significant meaning beyond the schema; the phrase 'Give it a domain' even slightly misrepresents the array-based 'items' parameter. Baseline 3 is appropriate.

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?

The description states a clear action ('checks whether the site publishes a valid llms.txt / llms-full.txt... and whether robots.txt blocks...') and identifies the specific resources (llms.txt, robots.txt, named AI crawlers). It distinguishes from sibling 'ai-crawler-access-checker' by combining both llms.txt and robots.txt checks, making the scope explicit.

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?

The description provides clear context for when to use the tool: give it a domain, no browser/LLM/API key needed, and costs $0.01/call. It implies a lightweight audit, but it does not explicitly state when NOT to use it or name alternatives such as 'ai-crawler-access-checker' for robots.txt-only checks.

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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TDQS

A4/5.0
Disambiguation2/5

Several tools have overlapping purposes: ai-crawler-access-checker and llms-txt-auditor both check robots.txt for AI crawler access, while ai-answer-change-alert, ai-overview-tracker, and llm-brand-visibility all track AI-generated citations/visibility. An agent may struggle to pick the right one without reading full descriptions.

Naming Consistency4/5

Most tools use lowercase hyphenated noun phrases (e.g., ai-answer-change-alert, social-preview-checker), but pricing_info uses an underscore, breaking the otherwise consistent pattern. Minor deviation but still readable.

Tool Count5/5

Seven tools is well-scoped for a specialized SEO/AI-visibility server. Each tool addresses a distinct aspect (crawler access, llms.txt, AI citations, brand visibility, social previews) without being excessive, and the pricing_info helper is a sensible addition.

Completeness4/5

The set covers the core AI-era SEO workflow: audit AI crawler access, validate llms.txt, track AI overview citations, monitor answer changes, and check brand visibility. Missing obvious features like generating llms.txt or deeper competitor analysis, but no critical dead ends.

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