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chasesaurabh

mcp-page-capture

by chasesaurabh
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TypeScript
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Server Quality Checklist

67%
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  • Latest release: v1.5.1

  • Disambiguation5/5

    The two tools have clearly distinct purposes: one captures a rendered screenshot with optional interactions, the other extracts raw HTML/text/DOM. There is no overlap in functionality, making it easy for an agent to choose the correct tool.

    Naming Consistency5/5

    Both tool names follow the same camelCase verb+noun pattern ('captureScreenshot', 'extractDom'), which is consistent and predictable. The naming clearly conveys the action and target.

    Tool Count4/5

    With only two tools, the server is very focused and minimal. This is appropriate for a simple 'page capture' utility that handles both visual and textual extraction. It's slightly on the low side, but the scope is narrow enough that two tools feel sufficient.

    Completeness4/5

    The tool surface covers the primary needs for capturing webpage content: visual (screenshot) and textual (DOM extraction). A potential minor gap might be a dedicated tool for downloading assets or getting page metadata, but for most use cases, the two tools provide complete coverage.

  • Average 4.4/5 across 2 of 2 tools scored.

    See the Tool Scores section below for per-tool breakdowns.

    • 0 of 1 community issues answered or closed in the last 6 months
    • 0 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.

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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

  • Behavior4/5

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

    With no annotations, the description effectively discloses behavior: step auto-ordering, auto-addition of screenshot step, error types (ELEMENT_NOT_FOUND, etc.), and HTTP auth usage. It does not cover rate limits or permissions, but the core behaviors are well-explained.

    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 relatively long but well-organized with headings (PARAMS, 6 STEPS, COMMON ERRORS, EXAMPLE). It front-loads the purpose and uses bullet points. Some redundancy exists (e.g., repeating step definitions already in schema), but overall it is efficient for the tool's complexity.

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

    Completeness5/5

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

    For a complex tool with 6 step types, nested objects, and no output schema, the description covers all necessary aspects: parameter descriptions, step details, error handling, ordering, and an example. It is complete enough for an AI agent to correctly select and invoke the tool.

    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 input schema has 100% description coverage, so baseline is 3. The description adds significant value beyond schema: details on step interactions, auto-ordering, common errors, and an example. This includes error handling tips that are not in schema descriptions.

    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's purpose: 'Capture webpage screenshot with optional pre-capture interactions.' It uses a specific verb ('Capture') and resource ('webpage screenshot'), and is distinct from the sibling tool 'extractDom', which is for DOM 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 provides explicit guidelines for using steps, including ordering, error handling (with specific COMMON ERRORS & FIXES), and an example. It explains when to add certain steps (e.g., wait before failing step). However, it does not explicitly compare to the sibling tool 'extractDom' or state when not to use this tool.

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

  • Behavior4/5

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

    With no annotations, description must cover behavior. It states extraction scope but does not explicitly mention that it is non-destructive or any potential limits. However, for a read operation, the description is adequate.

    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?

    Efficient use of space: purpose stated first, then usage guidance, then parameter summary, then example. No wasted words.

    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?

    Simple tool with no output schema; description mentions extracted content types (HTML, text, DOM structure). Could be more explicit about return format but sufficient for common use cases.

    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 baseline is 3. The description adds a brief note on selector usage and example, but does not significantly enhance schema-provided parameter info.

    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?

    Clearly states 'Extract HTML, text, and DOM structure from a webpage', uses specific verb and resource. Distinguishes from sibling tool captureScreenshot by stating when to use each (text vs visual).

    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?

    Explicit 'USE WHEN' and 'USE captureScreenshot WHEN' sections provide clear context and alternatives. Includes an example invocation.

    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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