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Front-End Checklist

Audit Live URL

audit_url
Read-onlyIdempotent

Fetches a public URL and audits its HTML against frontend best practice rules. Use this tool when you want to check a live website without manually pasting HTML. Automatically fetches the page source and runs the same heuristic checks as review_code.

Workflow: Call audit_url with a public https:// URL → get back a prioritized issue list → use fix_rule for remediation guidance on each issue.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
urlYesPublic URL to audit. Must use https://. Private IPs and localhost are blocked.
focusNoOptional: Focus review on specific categories (default: auto-detect from fetched HTML)
minPriorityNoOptional: Minimum priority level to report (default: medium)

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
errorNo
issuesNo
sourceNo
summaryNo
suggestionsNo

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A4.1/5.0
Behavior4/5

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

Annotations already declare readOnly, idempotent, openWorld, non-destructive, so safety is covered. The description adds real behavioral context: it automatically fetches page source over the network and returns a prioritized issue list, and the workflow tells the agent what the next step is. It does not mention fetch failures/timeouts or rate limits, keeping it short of a 5.

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?

Front-loaded with the core action, then scoping, then a compact workflow arrow-chain. Every sentence carries information, though the bolded '**Use this tool**' and '**Workflow:**' emphasis is slightly marketing-flavored for a tool definition.

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?

For a 3-parameter read tool with an output schema, the description covers purpose, network-fetch behavior, sibling differentiation and the follow-up tool. It leaves out failure modes (unreachable/blocked URLs, redirects) and whether results are cached, but nothing essential for correct invocation is missing.

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%, so url, focus and minPriority are all documented in the schema itself. The description adds no syntax or format detail beyond the schema (the https/private-IP restriction it mentions is already in the url parameter description). Baseline 3 applies.

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+resource ('Fetches a public URL and audits its HTML against frontend best practice rules') and immediately distinguishes itself from the sibling review_code by noting it works on a live site 'without manually pasting HTML'. An agent can route between audit_url and review_code from the description alone.

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?

Explicitly says when to use it (checking a live website) and names the alternative behavior it substitutes for (review_code's manual HTML path). The workflow line chains it to fix_rule for remediation. No explicit when-not condition (e.g. non-public or non-https URLs), which is the only gap.

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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