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Check one area of a website

check_category
Read-onlyIdempotent

Inspect a single area and return its verdict, the checks that failed, why each matters and how to fix it. Categories: seo, ai (whether AI crawlers and answer engines can read and cite the site), security (headers, exposure, secrets in source), privacy, tls (certificate and protocol), dns (records, SPF, DMARC, CAA), a11y (accessibility), content, slop (AI-generated-filler signals), design, infra, tech, credibility, correlation (does the page deliver what its title promises), faq, discoverability, local, contact. Use this rather than audit_website when the question is narrow — "is my site secure", "why is my SEO bad", "can ChatGPT see my site".

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
urlYesThe website to inspect. A bare domain works — "example.com" is treated as https://example.com.
categoryYesWhich area to inspect.
failing_onlyNoReturn only problems, omitting checks that passed.

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
urlYes
nameNoHuman-readable category name.
scoreYes
countsNoChecks by status. The last five are undetermined states and are never scored as passes.
categoryYesThe category id that was inspected.
problemsNoChecks that failed or warned, in check order.
passingCountNo
undeterminedNo

TDQS

A4.5/5.0
Behavior4/5

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

Annotations already indicate read-only, idempotent, and non-destructive behavior. The description adds transparency about the output structure (verdict, checks, why, how to fix), which complements the annotations without contradicting them.

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 moderately verbose due to the category list, but it is well-organized with clear explanations. It avoids unnecessary fluff and stays focused on purpose, usage, and output, making it appropriately concise for the complexity.

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 comprehensive schema and annotations, the description provides sufficient context. It explains what the tool does, when to use it, and what it returns. The absence of output schema details is acceptable since the description already outlines the return content.

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

Parameters4/5

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

The schema already covers each parameter's meaning (url, category, failing_only). The description enriches the category parameter by explaining each enumerated value (e.g., 'ai' as AI crawlers and answer engines), improving semantic clarity beyond the schema.

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 clearly states it inspects a single area and returns verdicts, failed checks, reasons, and fixes. It explicitly distinguishes itself from audit_website for narrow questions, making the purpose and scope precise.

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

Usage Guidelines5/5

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

Provides explicit guidance on when to use this tool over audit_website (narrow questions) and gives concrete examples ('is my site secure', 'why is my SEO bad'). It also enumerates all categories, facilitating correct selection.

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

A4.4/5.0
Disambiguation4/5

Most tools have clearly distinct purposes: full audit vs. single-category check vs. score-only vs. comparison vs. badge embed vs. inventory vs. change tracking. However, check_ai_visibility overlaps with check_category's 'ai' area, potentially causing confusion for agents. Descriptions help delineate but the overlap is notable.

Naming Consistency4/5

Seven of eight tools follow a consistent verb_noun snake_case pattern (audit_website, check_ai_visibility, check_category, compare_websites, get_badge_embed, get_score, get_site_inventory). Only 'what_changed' breaks the pattern by using a question phrase. Otherwise naming is uniform and predictable.

Tool Count5/5

8 tools is well-scoped for a website intelligence server. Each tool addresses a distinct need (full audit, narrow check, AI visibility, comparison, score, badge, inventory, diff tracking) without being excessive or sparse. The set feels complete for its domain.

Completeness5/5

The tool surface covers the full lifecycle of analyzing a website: comprehensive audit (audit_website), granular category checks (check_category, check_ai_visibility), score retrieval (get_score), comparison (compare_websites), change monitoring (what_changed), asset inventory (get_site_inventory), and even a sharing artifact (get_badge_embed). No obvious dead ends or missing operations for the stated purpose.

Resources