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mrbkrustamov

@21st-dev/magic

by mrbkrustamov

Server Quality Checklist

67%
Profile completionA complete profile improves this server's visibility in search results.
  • Latest release: v0.1.1-beta.1

  • Disambiguation5/5

    Each tool has a clearly distinct purpose: builder creates new component snippets, inspiration fetches data/previews from 21st.dev, refiner improves existing components, and logo_search specifically handles logo lookup. There is no overlap or ambiguity between them.

    Naming Consistency4/5

    The three component tools follow a consistent naming pattern with the '21st_magic_component_' prefix, but logo_search deviates from this convention. While readable and mostly predictable, the mixed pattern prevents a perfect score.

    Tool Count5/5

    With 4 tools, the server is well-scoped for its purpose of assisting with React component workflows (create, inspire, refine, and logos). Each tool earns its place without unnecessary redundancy.

    Completeness5/5

    The tool surface covers the core workflow for a UI component assistant: building new components, gathering inspiration, refining existing ones, and searching logos. There are no obvious gaps for the stated niche, and the server's purpose is fully addressed.

  • Average 4.3/5 across 4 of 4 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 ISC License.

  • This repository includes a README.md file.

  • No tool usage detected in the last 30 days. Usage tracking helps demonstrate server value.

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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?

    With no annotations, the description carries the burden of disclosing behavior. It states the tool only returns a snippet and does not modify files, requiring the agent to edit/add files afterward. This is honest and useful, though it doesn't cover error cases or output format details.

    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 three sentences, front-loaded with the usage trigger, and every sentence serves a purpose. The 'ONLY' emphasis is efficient and no filler is present.

    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?

    The description covers the tool's purpose, when to use it, what it returns, and the required follow-up action (edit/add files). It lacks an explicit description of the snippet's format or error behavior, but for a simple snippet builder this is acceptable given the schema and absent output schema.

    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 itself does not add parameter-specific meaning beyond what the schema already provides, so it does not exceed the baseline.

    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 builds new UI components and that it 'ONLY returns the text snippet', which differentiates it from the inspiration and refiner siblings. Trigger examples (button, input, dialog) make its scope unambiguous.

    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?

    It explicitly tells when to use the tool ('when the user requests a new UI component' with examples like /ui and /21st). It does not mention when not to use it or name alternatives, but the guidance is clear enough for an agent to decide.

    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 must fully disclose behavior. It does so by stating the tool returns JSON data and only a text snippet, does not generate code, and requires integration steps. This provides a clear behavioral profile, though it could have mentioned potential edge cases like no-matches or authentication, but for a straightforward fetch tool, the transparency is solid.

    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 three sentences, each earning its place: a usage trigger, a statement of return type, and a mandatory follow-up note. It is front-loaded with the primary use case and avoids fluff, making it highly concise and well-structured.

    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 a tool with two parameters, no output schema, and no annotations, the description covers all essential aspects: purpose, return format, and necessary post-actions. It is complete enough for an agent to invoke it correctly, though it could add a note on error handling or that the tool only applies to 21st.dev components, but these are minor 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%, as both 'message' and 'searchQuery' have detailed descriptions including format constraints. The tool description adds no extra parameter semantics beyond what the schema already provides, so the score aligns with the baseline of 3 for high schema coverage.

    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 purpose: it fetches and returns component snippets from 21st.dev when the user wants inspiration or a specific component. It distinguishes itself from siblings by explicitly stating 'without generating new code' and 'ONLY returns the text snippet,' making it clear this is a lookup tool, not a builder.

    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 specifies when to use the tool ('when the user wants to see component, get inspiration, or /21st fetch data and previews') and provides a clear post-condition ('After calling this tool, you must edit or add files'). It does not explicitly name alternative tools or provide exclusion criteria, but the 'without generating new code' phrasing implies a contrast with the builder, offering adequate usage guidance.

    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?

    No annotations are provided, so the description carries the behavioral burden. It discloses that the tool returns a redesigned version and implementation instructions, implying a non-mutating output. It also sets expectations around scope (components/molecules only, not big pages). It doesn't detail permissions or side effects, but for a UI refinement tool, the key behavior is clearly stated.

    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, front-loaded with the usage condition, and contains zero fluff. Every clause adds value: trigger commands, scope, output, and exclusion.

    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?

    Given the tool's moderate complexity (3 params, no output schema, no annotations), the description covers the essential aspects: what it does, when to use it, and what it returns. It could elaborate on the structure of the 'instructions' or the exact form of the redesigned version, but it is sufficiently complete for an agent to understand the tool's role among siblings.

    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 each parameter having a detailed description (e.g., context extraction rules). The tool description adds no additional parameter-level semantics, so the schema already does the heavy lifting. Baseline 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 tool's purpose: to refine/improve existing UI components for React components or molecules, distinguishing it from building new ones (sibling builder). It explicitly mentions the trigger commands (/ui, /21) and the scope limitation (NOT for big pages), making it unambiguous.

    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 provides explicit usage context: when the user requests re-design/refinement of a current UI component or when context is about improving a React component/molecule. It also includes an exclusion (NOT for big pages). However, it doesn't explicitly name alternative tools, relying on the 'current' vs 'new' distinction to differentiate from the builder sibling.

    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?

    No annotations supplied, so the description carries full burden. It discloses return formats (JSX/TSX/SVG), theme availability, and result structure (component name, code, import instructions). This goes well beyond a generic 'search' but could further state read-only nature or external data source.

    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?

    Well-organized with a summary line followed by targeted sections (when to use, examples, formats, results). Every bullet earns its place, and the structure makes it easy to scan. Length is justified by the richness of needed context.

    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?

    For a two-parameter tool with no output schema, the description is fully comprehensive. It explains purpose, usage triggers, parameter semantics, expected outputs, and even return value shape, leaving no obvious gaps for an agent to invoke it correctly.

    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?

    Schema coverage is 100%, so baseline is 3. The description adds substantial meaning by explaining each format option ('TSX: Returns TypeScript React component') and providing realistic query examples for the 'queries' parameter, including command style and phrase variants.

    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 opens with 'Search and return logos in specified format (JSX, TSX, SVG),' a specific verb+resource+scope statement. It clearly distinguishes from sibling tools (component builder/inspiration/refiner) by focusing on logo search and retrieval.

    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?

    Explicit 'When to use this tool' section lists two concrete scenarios (user types '/logo' command or requests a non-local logo). Clear context and example queries, but it does not mention when not to use or name alternative tools, so misses the top tier.

    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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