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charlesmichaelbaird

2Bot

by charlesmichaelbaird
OverviewSchemaRelated ServersScoreDiscussions
Python
Hybrid

Server Quality Checklist

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

  • Latest release: v0.1.0

  • Disambiguation5/5

    With only one tool, there is zero ambiguity—no other tools exist to confuse with run_codex_prompt. The tool's purpose is distinct by default.

    Naming Consistency5/5

    The single tool name 'run_codex_prompt' follows a clean verb_noun pattern, making it clear and predictable. With only one tool, consistency is inherently maintained.

    Tool Count2/5

    A single tool is extremely thin for an MCP server, even for a narrow purpose. While it might serve a specific need, it feels like a minimal wrapper rather than a coherent tool set, earning a low score.

    Completeness3/5

    The tool covers the basic action of running a codex prompt, but the surface is incomplete—no ability to list past runs, check status, cancel, or configure the CLI. For the implied domain, notable operations are missing.

  • Average 3.3/5 across 1 of 1 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
    • 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.

    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

  • Behavior3/5

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

    No annotations are provided, so the description carries full burden. It discloses two key behaviors: non-interactive mode and sending the prompt over stdin. However, it does not mention side effects, required permissions, error behavior, or the significance of sandbox/approval parameters. This is partial disclosure but not comprehensive for a potentially mutating tool.

    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 two sentences long, with each sentence adding distinct value: first purpose, then a critical behavioral detail. It is front-loaded and contains no fluff or repetition of structured data.

    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?

    Despite having an output schema, the tool is complex (12 parameters, many affecting safety and policy). The description omits any explanation of parameter semantics, usage context, or behavioral limitations. For an agent to invoke this tool correctly, it would need additional knowledge about sandbox modes, approval policies, and other settings that the description does not provide.

    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?

    The input schema has 12 parameters with 0% description coverage, and the tool description does not explain any of them. While 'prompt' is implicitly referenced via 'sends the prompt over stdin', no parameter semantics are clarified. The description fails to compensate for the schema's lack of descriptions, leaving the agent to guess the meaning of cwd, model, sandbox, approval_policy, etc.

    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: 'Run a prompt via local Codex CLI (`codex exec`) and return structured automation output.' It specifies the verb, resource, and expected output. Since there are no sibling tools, differentiation is not needed, and the purpose is unambiguous.

    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 does not provide explicit when-to-use guidance or mention alternatives (no siblings exist). The line '2Bot always uses non-interactive mode and sends the prompt over stdin' gives context about invocation but not about when to select this tool over others. Usage is implied by the purpose, but there is no clear context or exclusions.

    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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  • Confirm that there are no obvious security issues.
  • Evaluate tool definition quality.

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