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dengfeng-0908

web-gpt

by dengfeng-0908
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Server Quality Checklist

67%
Profile completionA complete profile improves this server's visibility in search results.

  • Latest release: v0.1.0

  • Disambiguation5/5

    ask_chatgpt sends tasks and awaits responses, while read_chatgpt only restores and reads previous chats without sending. Their purposes are distinct and unlikely to be confused.

    Naming Consistency5/5

    Both tools follow a consistent verb_chatgpt snake_case pattern: ask_chatgpt and read_chatgpt. The naming convention is predictable and clear.

    Tool Count3/5

    With only 2 tools, the surface feels thin even though both tools are clearly useful. The server covers a narrow scope, but the count is at the low end of the acceptable range.

    Completeness4/5

    The core workflow of sending a task and reading a previous chat is well covered. Minor gaps exist, such as no explicit delete or list-chats operation, but agents can work around them using session_id handling.

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

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

    • No community issues in the last 6 months
    • 1 commit 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

  • 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.

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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?

    Annotations are minimal (readOnly false, openWorld true, destructive false), so the description adds meaningful context: Chrome starts with a saved login, session_id restores/continues chats, project_url overrides the default project, and timeout is bounded at 1–840 seconds. It does not contradict annotations and adds behavioral detail beyond them.

    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 three compact sentences with no filler. It front-loads the core action, then efficiently covers effort selection, session handling, project override, and timeout.

    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 tool with five parameters and no output schema, the description covers invocation, effort choices, session lifecycle, project selection, authentication context, and timeout. The main gap is that it does not describe the return value or response format, and it does not mention the relationship to read_chatgpt.

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

    Parameters5/5

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

    Schema description coverage is 0%, but the description compensates comprehensively: it explains effort options, session_id semantics, project_url behavior, and the timeout range. Even though 'prompt' is not explicitly described, it is clearly implied by 'Send one task'.

    Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

    Purpose4/5

    Does the description clearly state what the tool does and how it differs from similar tools?

    The description clearly states the action as 'Send one task and wait', naming a specific verb and resource (ChatGPT). It does not explicitly distinguish itself from the sibling tool read_chatgpt, so it misses the full differentiation criterion.

    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 practical usage guidance: when to choose instant/medium/high vs pro effort, how to start a new chat, how to continue one with session_id, and how to override the project with project_url. It does not explicitly state when to use this tool instead of read_chatgpt, so it lacks explicit exclusions.

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

  • Behavior5/5

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

    The description adds valuable behavioral context beyond the annotations: Chrome starts automatically, a saved login is used, timeout has a 0–840 second range, and timeout 0 produces a snapshot after loading. This aligns with readOnlyHint and destructiveHint and provides concrete operational expectations.

    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 compact and front-loaded with the core purpose in the first sentence. The second sentence adds essential behavioral details without unnecessary filler.

    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 simple read-only tool with two parameters, the description is largely complete: it explains side effects, timeout behavior, and the fact that no message is sent. It could more explicitly describe what session_id should contain or how it relates to prior chats, but the overall picture is sufficient.

    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?

    With 0% schema description coverage, the description must compensate for parameter documentation. It explains timeout semantics well, including range and special value 0, but the required session_id is left mostly to inference from 'previous chat' and the property name.

    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 function: restoring and reading a previous chat without sending a message. This distinguishes it from the sibling ask_chatgpt by explicitly noting that no message is sent.

    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 phrase 'without sending a message' provides clear context for when to use this tool rather than ask_chatgpt. However, it does not explicitly name the alternative or state when to choose ask_chatgpt instead.

    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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