website-audit
Server Quality Checklist
Latest release: v1.0.0
- Disambiguation5/5
With only one tool, there is no possibility of confusion or overlap. The tool's purpose is clearly defined and distinct.
Naming Consistency5/5The single tool name 'audit_website' follows a clear verb_noun convention and is immediately understandable.
Tool Count3/5A single tool feels thin for a server claiming to audit multiple aspects of a website. However, the tool bundles all checks into one comprehensive call, so it may be acceptable for a focused utility.
Completeness4/5The tool covers a wide range of audit dimensions (speed, mobile, SEO, contact, AI copy, design) and returns a score with categorized findings. Minor gaps exist, such as no way to drill into individual metrics or get historical data, but the core audit lifecycle is complete.
Average 3.9/5 across 1 of 1 tools scored.
See the Tool Scores section below for per-tool breakdowns.
- No community issues in the last 6 months
- 2 commits in the last 12 weeks
- No stable releases found
- No critical vulnerability alerts
- No high-severity vulnerability alerts
- No code scanning findings
- CI status not available
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How is the quality score calculated?
The overall quality score combines two components: Tool Definition Quality (70%) and Server Coherence (30%).
Tool Definition Quality measures how well each tool describes itself to AI agents. Every tool is scored 1–5 across six dimensions: Purpose Clarity (25%), Usage Guidelines (20%), Behavioral Transparency (20%), Parameter Semantics (15%), Conciseness & Structure (10%), and Contextual Completeness (10%). The server-level definition quality score is calculated as 60% mean TDQS + 40% minimum TDQS, so a single poorly described tool pulls the score down.
Server Coherence evaluates how well the tools work together as a set, scoring four dimensions equally: Disambiguation (can agents tell tools apart?), Naming Consistency, Tool Count Appropriateness, and Completeness (are there gaps in the tool surface?).
Tiers are derived from the overall score: A (≥3.5), B (≥3.0), C (≥2.0), D (≥1.0), F (<1.0). B and above is considered passing.
Tool Scores
- Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full burden of behavioral disclosure. It does disclose the output format (0-100 score, findings grouped by category) and the nature of the analysis. However, it never explicitly states that the tool makes network requests to the target site, whether it is read-only, or how it handles failures like downtime, password-protected pages, or non-existent domains. These are meaningful gaps for an audit tool that fetches remote content.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is longer than a headline but every clause earns its place: the purpose is stated first, followed by a compact list of the checks, then the scoring output. The enumerations are comma-separated and easy to parse quickly. It is dense but not padded, and the key output information is front-loaded.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Since there is no output schema, the description correctly takes on the job of explaining return values, and it does — a 0-100 score with findings grouped by category. For a single-parameter, non-nested tool, the description covers the checks, output, and scope. It only misses edge-case behavior (unreachable sites, slow audits), which is minor given the tool's simplicity.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, and the single url parameter is already well documented in the schema with examples and format ('example.com' or 'https://example.com'). The description reinforces that the target must be a public website, which is a minor addition. Per the baseline for full schema coverage, 3 is appropriate — the schema does the heavy lifting for the sole parameter.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description states a specific verb (audit) plus a well-defined resource (any public website) and a clear outcome (report what is costing its owner customers). It goes further by enumerating the concrete checks performed — page speed, mobile-friendliness, SEO readability, contactability, AI-sounding copy, and dated-looking build — and the 0-100 scoring output. This is specific enough for an agent to know exactly what the tool does and what it returns.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5Does the description explain when to use this tool, when not to, or what alternatives exist?
There are no sibling tools to differentiate from, so the absence of explicit exclusions is acceptable. The description clearly scopes when to use it — any public website — and the enumerated checks imply the use case: understanding conversion/revenue problems from an owner's perspective. It lacks an explicit 'use this when…' statement, but for an isolated tool the context is clear and complete enough.
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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