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wmatragi

rollout-playbook-mcp

by wmatragi
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Server Quality Checklist

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

  • Latest release: v1.0.0

  • Disambiguation5/5

    The two tools have clearly distinct purposes: one searches existing playbooks, the other generates new plans. No overlap or confusion possible.

    Naming Consistency5/5

    Both tools follow a consistent verb_noun pattern: search_playbooks and generate_rollout_plan. Naming is clear and predictable.

    Tool Count2/5

    With only 2 tools, the server feels very thin for a 'rollout-playbook' domain. A typical set would include at least listing, retrieving, creating, and updating playbooks.

    Completeness2/5

    The domain of rollout playbooks is missing fundamental operations like create, read, update, delete, and execute playbooks. Only search and generate are present, leaving significant gaps.

  • Average 3.6/5 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.

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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?

    No annotations are provided, so the description must fully disclose behavioral traits. It only states that the tool 'generates a tailored checklist', but provides no information about mutability, authentication requirements, rate limits, or side effects. The lack of disclosure beyond purpose is a significant gap.

    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 efficiently conveys the core purpose. It is front-loaded with the action and resource, containing no redundant or irrelevant information.

    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?

    Given the absence of an output schema and annotations, the description should provide clues about the checklist format or structure. However, it only mentions the generation action without describing the return value or any behavioral aspects, making it incomplete for a tool that produces a plan.

    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 coverage is 100%, with each parameter having a description. The description adds 'tailored' and reaffirms the three parameters, but does not provide additional semantic detail beyond what the schema already offers. A baseline score of 3 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 clearly states the verb 'generate' and the specific resource 'deployment rollout plan checklist', and identifies the input factors (project type, team size, risk level). It distinguishes from the sibling tool 'search_playbooks', which searches existing playbooks rather than generating new plans.

    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 usage when a deployment rollout plan checklist is needed, but does not explicitly state when to use this tool versus the sibling 'search_playbooks'. No 'when not to use' or alternative guidance is provided.

    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?

    No annotations are provided, so the description must carry the full burden. It lacks details on scope (e.g., full-text search?), case sensitivity, or performance implications. The description only states the basic function without additional behavioral traits.

    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 conveys all essential information without unnecessary words. It is front-loaded and efficient.

    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 the tool has one parameter, no output schema, and no annotations, the description adequately states the purpose but lacks details about search behavior (e.g., partial matches, case sensitivity) that would enhance completeness for an agent.

    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% with the single 'query' parameter already having a description and example. The tool description adds no new information beyond that. Baseline 3 applies.

    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 verb 'search', the resource 'rollout/deployment playbooks', and the result 'return matching sections'. It distinguishes from the sibling tool 'generate_rollout_plan' which is about creation, not search.

    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 implies use for searching across all playbooks by keyword or phrase. It does not explicitly list when not to use or alternatives, but the sibling is clearly different, so context is clear.

    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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