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woffko

codex-mcp-longrun

by woffko
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Python
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Server Quality Checklist

58%
Profile completionA complete profile improves this server's visibility in search results.

  • Latest release: v0.2.0

  • Disambiguation5/5

    Each tool has a distinct role: health checks server status, run_and_wait executes a process and returns a result, and read_log_tail retrieves logs for a specific job. There is no overlap or ambiguity between them.

    Naming Consistency2/5

    Tool names are inconsistent in style: 'health' is a simple noun, 'run_and_wait' is a verb phrase, and 'read_log_tail' is a verb-noun-noun compound. No uniform pattern (e.g., verb_noun) is followed.

    Tool Count3/5

    Three tools is a minimal set, but it covers the core needs of a long-run execution server: health check, run a command, and read logs. It feels slightly thin but is not unreasonably sparse for a focused utility.

    Completeness3/5

    The surface covers the basic workflow of running a process and checking its logs, but lacks obvious lifecycle management tools like cancel, list jobs, or check status. The domain is narrow, yet significant gaps remain for robust long-running job handling.

  • Average 3.8/5 across 3 of 3 tools scored.

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

    • No community issues in the last 6 months
    • 8 commits 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

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  • 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?

    Annotations already indicate destructive behavior, but the description adds valuable context: the process must be 'approved' and 'non-interactive', and the result is 'bounded'. This goes beyond annotations by conveying safety and output-limitation constraints.

    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?

    A single, front-loaded sentence with zero wasted words. Every term ('approved', 'non-interactive', 'bounded') carries meaning.

    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?

    Although an output schema exists and annotations provide a safety baseline, the description fails to mention critical operational details such as waiting behavior, timeouts, output truncation, or success/failure matching. Given the tool's nine parameters, this is insufficient for a new agent to use it effectively.

    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?

    With only 22% schema description coverage and no parameter details in the description, the agent receives no help understanding the seven undocumented parameters (tail_bytes, timeout_sec, success_contains, etc.). The description adds no parameter semantics beyond what the schema already provides for cwd and argv.

    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 ('Run') and resource ('one approved non-interactive process') and clearly distinguishes this tool from siblings health and read_log_tail, which are about reading logs/state rather than executing commands. The phrase 'bounded terminal result' further clarifies the scope.

    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 use for running approved non-interactive commands and implies it waits for a result, but it does not explicitly state when to prefer this tool over alternatives or when not to use it. No exclusions or sibling comparisons are provided.

    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 provide readOnlyHint=true, so the description's 'Read only' adds no new safety info. It does add that the tail is 'stored' and 'bounded', which hints at behavior (not live streaming, limited size), but lacks details on error handling or response structure.

    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, efficient sentence with no redundancy. It front-loads the core action and resource without waste.

    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?

    The tool is relatively simple with an output schema (so return values are covered), but the description lacks parameter semantics and usage guidance. It is not fully complete for a 3-parameter tool with zero schema description coverage.

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

    Parameters2/5

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

    Schema coverage is 0%, so the description must compensate by explaining parameters. It only mentions 'known job ID' and 'bounded tail', but does not explain tail_bytes or tail_lines, their defaults, or how they interact. The agent must rely on schema names/types alone, which is insufficient.

    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 a specific action ('Read only') and resource ('bounded tail stored for a known job ID'), distinguishing it from siblings like health (status) and run_and_wait (execution). The title reinforces the longrun job context.

    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 phrase 'known job ID' implies this tool is used after a job has been created (likely via run_and_wait), but no explicit when/when-not guidance or alternatives are mentioned. Usage context is implied rather than stated.

    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?

    The annotations already provide readOnlyHint=true, establishing this as a safe read operation. The description adds useful specifics about the returned data (paths, versions, guardrails) without contradicting the annotations. It does not disclose potential side effects, but none are expected given the read-only nature.

    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, focused sentence that conveys all necessary information. There is no redundancy or filler.

    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?

    Given the tool has no parameters, includes an output schema, and is annotated as read-only, the description is fully adequate. It states what the tool returns, and the output schema handles the rest. Nothing essential is missing.

    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 zero parameters, and the description rightly omits parameter details. Since there are no parameters to document, the baseline of 4 for a zero-parameter tool is appropriate.

    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 the specific verb 'Return' and enumerates the exact resources (server paths, versions, guardrails), making the tool's purpose unmistakable. It is clearly distinct from siblings run_and_wait and read_log_tail, which involve execution and log reading respectively.

    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?

    No explicit guidance is given for when to use this tool versus alternatives. However, the name 'health' and description imply it is for status checks, which serves as a weak implicit usage signal. No alternatives are mentioned or exclusions stated.

    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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