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apolosan

Design Patterns MCP Server

by apolosan

Server Quality Checklist

67%
Profile completionA complete profile improves this server's visibility in search results.
  • Latest release: v1.0.0

  • Disambiguation2/5

    Multiple tools have overlapping purposes that could cause confusion. 'find_patterns' and 'search_patterns' both appear to search for patterns, with descriptions that are nearly identical ('semantic search' vs 'keyword or semantic similarity'), making them difficult to distinguish. 'count_patterns' and 'get_pattern_details' are clearer, but the overlap between the two search tools significantly reduces disambiguation.

    Naming Consistency5/5

    All tool names follow a consistent verb_noun pattern with snake_case, such as 'count_patterns', 'find_patterns', 'get_pattern_details', and 'search_patterns'. This uniformity makes the tool set predictable and easy to understand, with no deviations in naming conventions.

    Tool Count3/5

    With only 4 tools, the set feels thin for a server focused on design patterns, which typically involve operations like creating, updating, or categorizing patterns. While basic retrieval functions are covered, the low count may limit functionality for more complex agent tasks, placing it in the borderline range for appropriateness.

    Completeness2/5

    The tool set is severely incomplete for a design patterns domain, as it only supports read operations (counting, searching, and getting details) with no ability to create, update, delete, or manage patterns. This lack of CRUD coverage creates significant gaps that will likely cause agent failures when trying to perform full lifecycle tasks.

  • Average 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
    • 4 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 the full burden of behavioral disclosure. It mentions 'semantic search' but doesn't explain what this entails—e.g., how results are ranked, whether it's a read-only operation, or any limitations like rate limits or authentication needs. For a tool with no annotation coverage, this leaves critical behavioral traits unspecified.

    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 directly states the tool's function without unnecessary words. It is front-loaded with the core purpose ('Find design patterns...'), making it easy to understand at a glance. Every part of the sentence earns its place by conveying essential 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 tool's complexity (semantic search with 4 parameters) and the absence of both annotations and an output schema, the description is insufficient. It doesn't cover behavioral aspects like result format, error handling, or how semantic search works, nor does it explain the relationship between parameters and outcomes. This leaves significant gaps for an AI agent to use the tool effectively.

    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%, meaning all parameters are documented in the schema itself. The description adds no additional meaning beyond the schema, such as explaining the 'semantic search' process in relation to the 'query' parameter or how 'categories' affect results. Since the schema does the heavy lifting, the baseline score of 3 is appropriate, but no extra value is provided.

    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: 'Find design patterns matching a problem description using semantic search.' It specifies the verb ('Find'), resource ('design patterns'), and method ('semantic search'), making the intent unambiguous. However, it doesn't explicitly differentiate from sibling tools like 'search_patterns' or 'count_patterns,' which prevents a perfect score.

    Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

    Usage Guidelines2/5

    Does the description explain when to use this tool, when not to, or what alternatives exist?

    The description provides no guidance on when to use this tool versus alternatives. With siblings like 'search_patterns' and 'count_patterns' available, it fails to indicate scenarios where this tool is preferred, such as for semantic versus keyword-based searches, or how it differs from 'get_pattern_details.' This lack of comparative context leaves the agent without clear usage direction.

    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 carries the full burden. It states it 'gets' information, implying a read-only operation, but doesn't disclose any behavioral traits such as error handling, permissions needed, rate limits, or what 'detailed information' includes. This is a significant gap for a tool with no annotation coverage.

    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 directly states the tool's purpose without any wasted words. It is appropriately sized and front-loaded, making it easy to understand quickly.

    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 lack of annotations and output schema, the description is incomplete. It doesn't explain what 'detailed information' entails, potential return values, or any behavioral context. For a tool with no structured data beyond the input schema, this leaves significant gaps in understanding its full functionality.

    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?

    The input schema has 100% description coverage, with the parameter 'patternId' clearly documented. The description adds no additional meaning beyond what the schema provides, such as format examples or constraints. With high schema coverage, the baseline score of 3 is appropriate.

    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 verb 'Get' and the resource 'detailed information about a specific pattern', which is specific and understandable. However, it doesn't differentiate from sibling tools like 'find_patterns' or 'search_patterns' that might also retrieve pattern information, so it doesn't reach the highest score.

    Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

    Usage Guidelines2/5

    Does the description explain when to use this tool, when not to, or what alternatives exist?

    The description provides no guidance on when to use this tool versus alternatives like 'find_patterns' or 'search_patterns'. It lacks context about whether this is for retrieving details of a known pattern ID versus searching for patterns, leaving usage unclear.

    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 the full burden of behavioral disclosure. It mentions search functionality but fails to describe critical behaviors such as pagination, rate limits, authentication needs, or what happens on no matches. For a search tool with zero annotation coverage, this is a significant gap in transparency.

    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 extremely concise at one sentence with zero waste, front-loading the core functionality. Every word earns its place, making it easy for an agent to parse quickly without unnecessary elaboration.

    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 tool's complexity as a search function with 3 parameters, no annotations, and no output schema, the description is incomplete. It lacks information on return values, error handling, and behavioral traits, leaving the agent with insufficient context to use the tool effectively beyond basic invocation.

    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 low at 33%, with only the 'query' parameter documented. The description adds value by explaining that searches can be by keyword or semantic similarity, which helps interpret the 'searchType' enum, but it doesn't clarify the 'limit' parameter or provide details beyond what the schema implies. This partial compensation justifies a baseline score.

    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 as searching patterns using keyword or semantic similarity, which is specific and actionable. However, it doesn't explicitly distinguish this from sibling tools like 'find_patterns' or 'count_patterns', leaving some ambiguity about when to choose one over another.

    Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

    Usage Guidelines2/5

    Does the description explain when to use this tool, when not to, or what alternatives exist?

    The description provides no guidance on when to use this tool versus alternatives like 'find_patterns' or 'count_patterns'. It mentions search methods but doesn't specify scenarios, prerequisites, or exclusions, leaving the agent to guess based on tool names alone.

    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 carries the full burden of behavioral disclosure. It states the tool 'Get[s] the total number', implying a read-only operation, but doesn't mention any behavioral traits such as performance considerations, error handling, or whether it's a simple count versus an aggregated query. For a tool with zero annotation coverage, this is a significant gap in transparency.

    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 directly states the tool's purpose without any unnecessary words. It is appropriately sized and front-loaded, making it easy for an agent to parse quickly. Every part of the sentence earns its place by conveying essential information.

    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's low complexity (one optional parameter) and high schema coverage, the description is adequate but has clear gaps. It lacks output schema information, usage guidelines, and behavioral context, which could help an agent use it correctly. However, for a simple counting tool, it meets the minimum viable threshold without being fully comprehensive.

    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?

    The input schema has 100% description coverage, with the parameter 'includeDetails' clearly documented in the schema. The description adds no additional meaning beyond what the schema provides, as it doesn't mention parameters at all. According to the rules, when schema_description_coverage is high (>80%), the baseline score is 3, which is appropriate here.

    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 a specific verb ('Get') and resource ('total number of design patterns in the database'), making it easy to understand what it does. However, it doesn't explicitly differentiate from sibling tools like 'find_patterns' or 'search_patterns', which might also retrieve pattern information, so it doesn't reach the highest score.

    Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

    Usage Guidelines2/5

    Does the description explain when to use this tool, when not to, or what alternatives exist?

    The description provides no guidance on when to use this tool versus alternatives like 'find_patterns', 'get_pattern_details', or 'search_patterns'. It lacks any context about use cases, prerequisites, or exclusions, leaving the agent to infer usage based on the name alone.

    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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