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jmcdice

Superpowers MCP Server

by jmcdice

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: 'find_skills' is for listing available skills, while 'use_skill' is for loading and reading a specific skill. There is no overlap or ambiguity between them.

    Naming Consistency5/5

    Both tools follow a consistent verb_noun pattern with snake_case naming: 'find_skills' and 'use_skill'. The naming is uniform and predictable throughout the set.

    Tool Count2/5

    With only 2 tools, the server feels thin for a 'Superpowers MCP Server' that implies managing skills and workflows. This minimal set may not adequately cover the domain's potential scope, such as creating, updating, or deleting skills.

    Completeness2/5

    The tool set is severely incomplete for skill management. It only supports listing and reading skills, lacking essential CRUD operations like creating, updating, or deleting skills, which are likely needed for a comprehensive skill library system.

  • Average 3.3/5 across 2 of 2 tools scored.

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

    • No community issues in the last 6 months
    • 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.

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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 carries full burden. It mentions that skills 'guide your work' and contain 'proven workflows, mandatory processes, and expert techniques,' which gives some behavioral context about the content. However, it doesn't disclose critical traits like whether this is a read-only operation, if it requires authentication, what happens on invocation (e.g., if it modifies state), or any rate limits—leaving significant gaps for a tool that loads resources.

    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 appropriately sized with two sentences that are front-loaded: the first states the core action, and the second elaborates on what skills contain. There's no wasted text, though it could be slightly more structured (e.g., by explicitly mentioning the parameter).

    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 with full schema coverage and no output schema, the description provides basic purpose and content context. However, for a tool that loads resources to 'guide your work,' it lacks details on what the output entails (e.g., structured data, instructions), behavioral traits, or differentiation from siblings, making it minimally adequate but with clear gaps.

    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 parameter 'skill_name' fully documented in the schema. The description doesn't add any meaning beyond what the schema provides (e.g., it doesn't explain skill naming conventions or provide examples beyond the schema's 'e.g.'). Baseline 3 is appropriate as the schema does the heavy lifting.

    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 states the tool's purpose with specific verbs ('Load and read') and resource ('a specific skill'), explaining it provides workflows, processes, and techniques. However, it doesn't explicitly distinguish this from the sibling 'find_skills' tool, which likely searches for skills rather than loading one.

    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 context by stating skills 'guide your work' and contain workflows, suggesting this tool is for accessing predefined guidance. However, it doesn't explicitly state when to use this versus 'find_skills' or provide any exclusions or prerequisites for usage.

    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?

    With no annotations provided, the description carries full burden for behavioral disclosure. It states this is a list operation but doesn't mention whether it requires authentication, has rate limits, returns paginated results, or what format the output takes. For a tool with zero annotation coverage, this leaves significant behavioral gaps.

    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 that immediately communicates the core functionality without any wasted words. It's appropriately sized for a simple list tool with no parameters, and every element of the sentence contributes to understanding what the tool does.

    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 zero-parameter list tool, the description adequately covers the basic purpose. However, without annotations or an output schema, it doesn't address important behavioral aspects like authentication requirements, rate limits, or return format. The description is minimally complete but could provide more context about the operation's characteristics.

    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 tool has zero parameters with 100% schema description coverage, so the schema already fully documents the lack of inputs. The description appropriately doesn't add parameter information beyond what's in the schema, maintaining focus on the tool's purpose rather than unnecessary parameter details.

    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 states the action ('List') and target resources ('all available skills in the personal and superpowers skill libraries'), making the purpose immediately understandable. It doesn't explicitly differentiate from the sibling tool 'use_skill', but the distinction is implied through the different verbs (list vs use).

    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 context by specifying what skills are listed (personal and superpowers libraries), suggesting this is for discovery rather than application. However, it doesn't provide explicit guidance on when to choose this over 'use_skill' or any prerequisites for accessing these libraries.

    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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