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Server Quality Checklist

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  • Latest release: v1.0.0

  • Disambiguation5/5

    The three tools have clearly distinct purposes: synchronous execution, asynchronous execution, and result polling. An agent can easily select the right tool based on whether it wants to wait or run in the background.

    Naming Consistency5/5

    All tools share the claude_code_ prefix and follow a snake_case imperative verb style: check_result, execute, execute_async. The family is predictable and consistent.

    Tool Count5/5

    With only three tools, each serves a distinct and necessary function for the server's purpose. The count is well-scoped and not padded with redundant operations.

    Completeness5/5

    The server covers the full execution lifecycle: start a task synchronously, start a task asynchronously, and check the result of an async task. There are no obvious dead ends or missing core operations for this focused domain.

  • Average 3.7/5 across 3 of 3 tools scored.

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

    • No community issues in the last 6 months
    • 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 is passing
  • 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

  • Behavior2/5

    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, but it only states that execution is synchronous and returns a result. It does not mention side effects, the skip_permissions default, output shape variability, or error/timeout behavior, which are material for a code-execution tool.

    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 short, front-loaded with the core synchronous behavior, and ends with a practical usage example. The phrase 'full control over parameters' is somewhat vague, but overall it is concise and direct.

    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?

    Given no annotations and no output schema, the description is adequate for basic synchronous execution with a prompt, and the input schema covers all parameters. It is incomplete around return formats, the async alternative, and safety implications, which are important for this kind of tool.

    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 schema already documents all seven parameters. The description adds only a common-usage example with prompt and working_dir; this is mildly helpful but does not meaningfully extend the schema's parameter explanations.

    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 identifies the tool as executing Claude Code synchronously and returning the result after completion. This distinguishes it from the async sibling by emphasizing blocking behavior, though it does not explicitly name or contrast with claude_code_check_result.

    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 synchronous wording and 'returns the result after completion' imply it should be used when the caller wants to wait for Claude Code's output. However, there is no explicit guidance about when to prefer execute_async or check_result, leaving the selection largely implicit.

    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 must carry the full behavioral burden. It does disclose the returned states ('running/completed') and that a result is only available when done, but it omits details about error conditions, polling behavior, response structure, or whether the task result is cleared after being read.

    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 a single sentence that front-loads the action and then summarizes the output. Every clause contributes useful information with no redundancy or filler.

    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 one-parameter polling tool, the description is concise and covers the core behavior, but since there is no output schema it should explain more about the return format and possible status values. 'The result if available' is vague and an agent may not know how to interpret the returned payload.

    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?

    The schema covers task_id fully with the description 'The task_id returned by claude_code_execute_async', so the baseline is 3. The tool description adds no additional parameter semantics 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 uses a specific verb ('Check') and a clear resource ('status of an async Claude Code task'), and explicitly states the return value ('running/completed status and the result if available'). It clearly distinguishes this tool from the execute siblings by focusing on status checking rather than execution.

    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 implies this tool is for polling an async task by mentioning 'async' and 'status', and the schema parameter references claude_code_execute_async. However, it does not explicitly state when to prefer this tool over alternatives or provide any exclusion criteria, leaving the usage context largely implicit.

    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, the description carries the burden of behavioral disclosure. It clearly states the non-blocking nature, immediate return, task_id handoff, and deferred result retrieval. It does not mention safety implications like skipped permissions or failure handling, but the core async behavior is 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?

    Three tight sentences with no filler. The key behavioral fact (background execution and immediate task_id return) is front-loaded, and the retrieval-next step is stated immediately.

    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 an async task-launch tool, the description provides the essential workflow: start, get task_id, check result later. It does not define the exact shape of the result, but there is no output schema and the absence is mitigated by pointing to the sibling check_result tool.

    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 little beyond the schema, and no parameter is given deeper meaning, but the schema already documents every parameter adequately.

    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 identifies a specific action: starting a Claude Code task in the background and returning immediately with a task_id. This distinguishes it from synchronous execution and from result retrieval via claude_code_check_result.

    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 async workflow well, telling the agent to use claude_code_check_result later and that it can continue working. It does not explicitly compare against claude_code_execute or state when not to use the tool, so it stops short of full exclusion guidance.

    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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