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belzorash

cleanfetch

by belzorash
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Server Quality Checklist

67%
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  • Latest release: v0.1.0

  • Disambiguation5/5

    Each tool targets a distinct aspect of web page analysis: links, metadata, and clean content. There is no functional overlap between extract_links, extract_metadata, and fetch_clean.

    Naming Consistency4/5

    Tools follow a verb_noun pattern, but fetch_clean uses 'fetch' while the other two use 'extract'. This is a minor inconsistency but still clear and predictable.

    Tool Count5/5

    Three tools is a well-scoped set for a clean fetching utility, covering the essential operations without unnecessary complexity.

    Completeness5/5

    The tools cover all key aspects of web page extraction: links, metadata, and clean content. No obvious gaps for the stated purpose of agent navigation and analysis.

  • Average 4/5 across 3 of 3 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
    • Last stable release on
    • No critical vulnerability alerts
    • No high-severity vulnerability alerts
    • No code scanning findings
    • CI status not available

  • This repository is licensed under MIT License.

  • This repository includes a README.md file.

  • No tool usage detected in the last 30 days. Usage tracking helps demonstrate server value.

    Tip: use the "Try in Browser" feature on the server page to seed initial usage.

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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, the description carries the full burden. It describes the read-only fetch and return of metadata but omits any potential limitations, error conditions, or side effects. Behavior is implied but not fully disclosed.

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

    Conciseness5/5

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

    The description is two sentences with clear structure: action first, then list of outputs, then purpose. No unnecessary words; front-loaded with key information.

    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 a single required parameter and no output schema, the description sufficiently explains the tool's function and return content. It could be more complete by noting that output is in JSON or similar, but not essential.

    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%, so baseline is 3. The tool description adds no extra meaning beyond the schema's parameter description 'The page URL to fetch'. No additional context is provided.

    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 the tool fetches a page and returns structured metadata, listing specific elements (title, description, etc.). It distinguishes from siblings by implying extract_links and fetch_clean serve different purposes.

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

    Usage Guidelines3/5

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

    The description mentions analyzing structure without reading the whole body, which implies a use case. However, it provides no explicit when-to-use or when-not-to-use guidance, nor does it compare directly to siblings.

    Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

  • Behavior3/5

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

    No annotations are provided, so the description should disclose more behavioral details. It states it fetches a page and classifies links, but does not mention potential blocking, error handling, or the return format. Basic transparency is present but not comprehensive.

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

    Conciseness5/5

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

    The description is concise with two sentences. The first sentence communicates the core functionality, and the second adds usage context. No unnecessary words.

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

    Completeness3/5

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

    With no output schema and no annotations, the description gives output details (links, anchor text, classification) but does not specify the return structure, pagination, or error behavior. Adequate but not fully complete.

    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 the baseline is 3. The description adds no additional parameter-specific meaning beyond what the schema already provides.

    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 the tool fetches a page and returns hyperlinks with anchor text and internal/external classification. It distinguishes from siblings like extract_metadata and fetch_clean by focusing on links.

    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 mentions 'Useful for crawling and agent navigation', providing clear context but does not explicitly state when to avoid using this tool or mention alternatives.

    Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

  • Behavior3/5

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

    With no annotations, the description carries full burden. It mentions stripping navigation, ads, and scripts, but does not disclose potential issues like rate limits, authentication, error handling, or what happens if the page fails to parse correctly. The description is adequate but could be more transparent.

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

    Conciseness5/5

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

    The description is two concise sentences with no wasted words. It front-loads the main purpose and provides just enough detail for the agent to understand the tool's core functionality.

    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 simplicity (2 parameters, no output schema), the description is fairly complete. It explains the purpose, what is stripped, and what is returned. However, for completeness, it could mention behavior on errors or redirects, but this is not critical.

    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?

    Schema coverage is 100% (both parameters described). The description adds meaning by specifying the output format (clean Markdown) and included metadata (title, byline), which is not in the schema. This adds value beyond the parameter names and types.

    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 the verb ('Fetch'), the resource ('web page'), and the output ('clean Markdown plus core metadata'). It also implicitly distinguishes from siblings like extract_links and extract_metadata by focusing on content extraction.

    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 explains the intended use case: fetching a page to get clean, readable content for an agent. It does not explicitly state when not to use it or mention alternatives, but the context of sibling tools provides some differentiation.

    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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  • Confirm that there are no obvious security issues.
  • Evaluate tool definition quality.

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