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huj28-creator

WeChat FastBridge

by huj28-creator
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JavaScript

Server Quality Checklist

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  • Latest release: v1.7.1

  • Disambiguation2/5

    Tools 'wechat_read' and 'wechat_wait' both deal with delta and smart context, and their descriptions are too similar, causing potential confusion. 'wechat_status' is distinct.

    Naming Consistency4/5

    All tool names follow a consistent 'wechat_verb' pattern with snake_case, which is clear and predictable. Minor deviation is that verbs are not part of a full verb_noun structure, but overall consistent.

    Tool Count2/5

    Only 3 tools for a messaging bridge server feels too few. Core operations like sending messages or managing chats are missing, making the set feel thin.

    Completeness1/5

    The tool surface is severely incomplete for a WeChat bridge. It lacks essential operations such as sending messages, listing chats, or managing contacts. Only read/wait and a status check are provided.

  • Average 2.7/5 across 3 of 3 tools scored. Lowest: 2/5.

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

    • 0 of 1 community issues answered or closed in the last 6 months
    • 18 commits in the last 12 weeks
    • Last stable release on
    • No critical vulnerability alerts
    • No high-severity vulnerability alerts
    • No code scanning findings
    • CI is passing

  • 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

  • Behavior2/5

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

    Annotations provide readOnlyHint=true and openWorldHint=true, but the description adds little beyond 'Wait for ...'. It does not describe whether the tool blocks, how it returns, or what triggers completion. With annotations, the bar is lower, but the description still lacks behavioral details.

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

    Conciseness2/5

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

    The description is very short (one sentence), but it is under-specified rather than concise. It fails to convey essential information, so it is not effectively condensed.

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

    Completeness1/5

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

    Given the tool has 4 parameters, no output schema, and no param descriptions, the description is severely incomplete. It does not explain key concepts like 'delta', 'smart context', or how parameters interact. The tool is likely complex, but the description provides almost no value.

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

    Parameters1/5

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

    Schema description coverage is 0%, meaning the description explains none of the 4 parameters. The schema itself has constraints (e.g., default values, min/max), but the description adds no meaning for 'chat', 'after', 'context', or 'timeoutMs'. This is a critical gap.

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

    Purpose3/5

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

    The description states 'Wait for one chat's delta and smart context,' which identifies the action (wait) and resource (chat's delta and context). However, 'delta' and 'smart context' are vague and not clearly defined. It differentiates somewhat from siblings wechat_read and wechat_status by implying a waiting/blocking behavior.

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

    Usage Guidelines2/5

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

    No explicit guidance on when to use this tool vs alternatives like wechat_read or wechat_status. The description does not mention prerequisites, use cases, or when not to use it.

    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?

    Annotations already declare readOnlyHint=true and openWorldHint=true, signaling a safe read operation with dynamic results. The description adds 'delta and smart context' but does not explain these terms or any other behavioral traits. It does not contradict annotations.

    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 a single concise sentence, front-loading the key action. However, it may be overly terse, sacrificing completeness for brevity.

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

    Completeness2/5

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

    With 4 parameters, no output schema, and a mention of delta/context, the description is insufficient. It does not cover return values, pagination via limit, or the meaning of context parameter. Given the tool's medium complexity, the description is incomplete.

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

    Parameters1/5

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

    Schema description coverage is 0%, so the description must explain parameters. It only mentions 'after' without defining it, and ignores 'chat', 'limit', and 'context'. The agent gets no meaningful parameter guidance from the description.

    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 states 'Read a chat' with specific verb and resource, and adds a detail about returning 'delta and smart context' with a parameter 'after'. It clearly distinguishes from sibling tools 'wechat_status' and 'wechat_wait' which have 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 Guidelines2/5

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

    The description provides no explicit guidance on when to use this tool versus alternatives, nor any conditions, prerequisites, or exclusions. The agent must infer usage solely from the verb 'Read', which is insufficient.

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

  • Behavior2/5

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

    The description adds no behavioral context beyond what annotations already provide (readOnlyHint: true). It does not mention side effects, response behavior, or any constraints, so the burden remains largely on annotations.

    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?

    Exceptionally concise: two words, no fluff. Every word earns its place, and the description is front-loaded with the core action.

    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?

    For a simple status check with no parameters or output schema, the description is minimally complete. However, it fails to clarify what 'readiness' entails or what the response looks like, leaving some ambiguity.

    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?

    With zero parameters and 100% schema coverage, the schema fully documents the parameter space. The description adds no parameter meaning, but the baseline for 0 parameters is 4.

    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 'Check readiness' clearly states the purpose: to check readiness of something (likely WeChat service). It uses a specific verb and resource, and distinguishes from sibling tools 'wechat_read' and 'wechat_wait' by implying a status check rather than data reading or waiting.

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

    Usage Guidelines2/5

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

    No guidance on when to use this tool versus siblings or alternatives. The description does not specify prerequisites, context, or exclusions, leaving the agent to infer usage.

    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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  • Evaluate tool definition quality.

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