Skip to main content
Glama

Server Quality Checklist

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

  • Disambiguation5/5

    Each tool has a distinct, non-overlapping purpose: approvals manages approval requests, log-implementation records implementation details, spec-status shows progress, spec-workflow-guide provides workflow instructions, and steering-guide handles steering documents. The descriptions clearly differentiate their roles, with no ambiguity in selection.

    Naming Consistency3/5

    Naming is mixed with no clear pattern: 'approvals' and 'spec-status' use noun phrases, 'log-implementation' uses a verb-noun format, and 'spec-workflow-guide' and 'steering-guide' use noun-noun compounds. While readable, the conventions vary without a consistent verb_noun or other predictable structure.

    Tool Count5/5

    With 5 tools, this is well-scoped for a spec workflow server. Each tool serves a specific function in the workflow lifecycle (e.g., guidance, logging, approvals, status tracking), and none feel redundant or missing for the domain, making the count appropriate.

    Completeness4/5

    The toolset covers key aspects of spec workflow management: guidance (spec-workflow-guide), progress tracking (spec-status), implementation logging (log-implementation), approvals (approvals), and steering documents (steering-guide). A minor gap is the lack of a tool for directly creating or editing spec tasks, but agents can work around this by reading files as indicated.

  • Average 4.1/5 across 5 of 5 tools scored.

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

    • 6 of 9 community issues answered or closed 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 GPL 3.0.

  • 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.

  • Add a glama.json file to provide metadata about your server.

  • If you are the author, simply .

    If the server belongs to an organization, first add glama.json to the root of your repository:

    {
      "$schema": "https://glama.ai/mcp/schemas/server.json",
      "maintainers": [
        "your-github-username"
      ]
    }

    Then . Browse examples.

  • Add related servers to improve discoverability.

How to sync the server with GitHub?

Servers are automatically synced at least once per day, but you can also sync manually at any time to instantly update the server profile.

To manually sync the server, click the "Sync Server" button in the MCP server admin interface.

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?

    With no annotations provided, the description carries the full burden of behavioral disclosure. It describes what the tool does (displays progress overview, shows completion status) and mentions the relationship to tasks.md for detailed task status. However, it doesn't disclose important behavioral aspects like whether this is a read-only operation, what format the output takes, whether it requires specific permissions, or if there are any rate limits or side effects.

    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 main sections: a purpose statement and usage instructions. The first sentence clearly states the core function. The instructions section is useful but could be more concise. Overall, most sentences earn their place, though the relationship to tasks.md could be integrated more smoothly.

    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 2-parameter tool with no annotations and no output schema, the description provides adequate but incomplete context. It explains the purpose and usage scenarios well, but doesn't describe the output format or behavioral constraints. Given the tool's moderate complexity (status overview with parameters), the description should ideally provide more information about what the agent can expect as a result.

    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 schema already documents both parameters thoroughly. The description doesn't add any meaningful parameter semantics beyond what's in the schema - it doesn't explain how 'projectPath' and 'specName' interact, what format 'specName' should take, or provide examples. The baseline of 3 is appropriate when 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: 'Display comprehensive specification progress overview' with specific verbs ('display', 'shows') and resources ('specification progress overview', 'phases', 'task implementation progress'). It distinguishes from potential siblings by focusing on status overview rather than approvals, logging, or guidance functions. However, it doesn't explicitly differentiate from all sibling tools by name.

    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 clear context for when to use the tool: 'when resuming work on a spec or checking overall completion status.' It also provides guidance on next steps: 'After viewing status, read tasks.md directly to see all tasks and their status markers.' However, it doesn't explicitly state when NOT to use this tool or name specific alternatives among the sibling tools.

    Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

  • Behavior3/5

    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 mentions that the tool 'Provides templates and guidance' and emphasizes following the workflow 'exactly to avoid errors,' which hints at behavioral constraints. However, it lacks details on what 'errors' might occur, whether it's read-only or mutative, or any permissions/rate limits, leaving gaps in behavioral disclosure.

    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 well-structured and front-loaded with the main purpose, followed by instructions. It uses two paragraphs efficiently, with no wasted sentences. However, the second paragraph could be slightly more concise by combining some points, but overall, it's clear and to the point.

    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 no annotations, no output schema, and 0 parameters, the description provides good usage guidelines and purpose clarity. However, it lacks details on what the 'guide' output entails (e.g., format, content), and the behavioral aspects are under-specified. For a tool with no structured data, this leaves some contextual gaps, making it adequate but not fully complete.

    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 input schema has 0 parameters with 100% coverage, so no parameter documentation is needed. The description doesn't discuss parameters, which is appropriate. However, it could slightly improve by noting the lack of inputs, but this is minor; thus, a baseline score of 4 is given for adequate handling in a parameterless context.

    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: 'Load guide for creating project steering documents' and specifies the resources involved ('templates and guidance for product.md, tech.md, and structure.md creation'). However, it doesn't explicitly differentiate from sibling tools like 'spec-workflow-guide' beyond stating 'Not part of standard spec workflow,' which is somewhat indirect.

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

    Usage Guidelines5/5

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

    The description provides explicit usage guidelines: 'Call ONLY when user explicitly requests steering document creation or asks about project architecture docs. Not part of standard spec workflow.' It clearly defines when to use the tool and distinguishes it from alternatives by noting it's not part of the standard workflow, though it doesn't name specific sibling tools.

    Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

  • Behavior3/5

    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 discloses that this is a read operation ('load') and emphasizes the workflow sequence, but lacks details on behavioral traits like error handling, response format, or performance. It adds some context (e.g., 'to avoid errors'), but is minimal for a tool with no annotation coverage, resulting in an average score.

    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 front-loaded with the core purpose in the first sentence, followed by structured instructions. It uses bullet points effectively but includes some redundancy (e.g., repeating the importance of calling first). Overall, it's efficient with minimal waste, though could be slightly more streamlined.

    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 complexity (simple, no parameters) and lack of annotations or output schema, the description is reasonably complete. It covers purpose, usage sequence, and importance, but could improve by detailing the workflow content or potential outputs. It's sufficient for basic understanding but not exhaustive.

    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 0 parameters, and schema description coverage is 100%, so no parameter documentation is needed. The description doesn't mention parameters, which is appropriate. A baseline of 4 is applied as it compensates adequately for the lack of parameters by focusing on usage context.

    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: 'Load essential spec workflow instructions to guide feature development from idea to implementation.' It specifies the verb ('load'), resource ('workflow instructions'), and scope ('feature development from idea to implementation'). However, it doesn't explicitly distinguish from sibling tools like 'steering-guide' or 'spec-status', which might also provide guidance, keeping it from 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 Guidelines5/5

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

    The description provides explicit usage guidelines: 'Call this tool FIRST when users request spec creation, feature development, or mention specifications' and 'Always load before any other spec tools to ensure proper workflow understanding.' It specifies when to use (for spec-related requests) and when not to use (after other spec tools), with a clear sequence requirement, earning the highest score.

    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 provided, the description carries full burden and adds significant behavioral context beyond the schema. It discloses critical constraints: dashboard interface usage, filePath-only parameter for requests (no content), deletion restrictions, and workflow dependencies ('Wait for user to review and approve before continuing'). However, it doesn't mention error handling, rate limits, or authentication requirements.

    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 and well-structured with clear sections. The first sentence states the purpose, followed by usage instructions and critical warnings. Every sentence adds value, though the 'CRITICAL' section could be more concise by integrating with the action descriptions.

    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 complexity (8 parameters, multiple operations) and lack of annotations/output schema, the description provides substantial context about usage patterns, constraints, and workflow integration. It covers the main behavioral aspects but doesn't address potential edge cases, error responses, or the format of status results.

    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 adds some value by clarifying action-specific parameter requirements (e.g., 'Only provide filePath parameter for requests', 'approvalId required for status and delete', 'title required for request'), but doesn't provide additional semantic context beyond what's already documented in the schema descriptions.

    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: 'Manage approval requests through the dashboard interface' and lists specific operations (request, check status, delete). It distinguishes from siblings by focusing on approval management rather than logging, spec status, or workflow guidance. However, it doesn't explicitly contrast with each sibling tool's specific domain.

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

    Usage Guidelines5/5

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

    The description provides explicit usage guidance: 'Use this tool to request, check status, or delete approval requests' with clear action-specific rules. It specifies when to use each action (e.g., 'request' after creating documents, 'delete' for completed/rejected/needs-revision requests) and includes critical exclusions ('cannot delete pending requests', 'Never include document content').

    Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

  • Behavior5/5

    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 thoroughly explains that this tool creates persistent records for future searchability, emphasizes the critical requirement of artifacts, and details the consequences of misuse (technical debt from duplication). It also implicitly indicates this is a write operation (recording details) without contradicting any annotations.

    Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

    Conciseness3/5

    Is the description appropriately sized, front-loaded, and free of redundancy?

    The description is overly verbose with extensive examples, markdown formatting, and repetitive emphasis. While the front-loaded purpose is clear, the length (multiple sections like '# WHY DETAILED LOGGING MATTERS', '# REQUIRED FIELDS', examples) reduces conciseness. Some content (e.g., detailed bad examples) could be condensed without losing clarity.

    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?

    Given the tool's complexity (8 parameters, nested objects) and lack of annotations/output schema, the description is highly complete. It covers the tool's purpose, usage context, parameter details (especially for 'artifacts'), behavioral implications, and examples. The only minor gap is no explicit mention of authentication or error handling, but this is reasonable for a logging tool.

    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 description coverage is 100%, so the baseline is 3. The description adds significant value by elaborating on the 'artifacts' parameter with detailed sub-field requirements (e.g., apiEndpoints, components), examples, and formatting guidelines. However, it doesn't provide additional context for other parameters like 'projectPath' or 'statistics' beyond what the schema already describes.

    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 explicitly states the tool's purpose: 'Record comprehensive implementation details for a completed task' and emphasizes creating 'a searchable knowledge base that future AI agents use to discover existing code and avoid duplication.' This clearly distinguishes it from sibling tools like approvals or spec-status, which appear unrelated to logging implementation artifacts.

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

    Usage Guidelines5/5

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

    The description provides explicit guidance on when to use this tool: 'After completing a task, review what you implemented' and 'Identify all artifacts (APIs, components, functions, classes, integrations).' It also includes strong warnings about when not to use it (e.g., 'Incomplete logs = Duplicated code = Technical debt') and contrasts good vs. bad examples to guide proper usage.

    Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

GitHub Badge

Glama performs regular codebase and documentation scans to:

  • Confirm that the MCP server is working as expected.
  • Confirm that there are no obvious security issues.
  • Evaluate tool definition quality.

Our badge communicates server capabilities, safety, and installation instructions.

Card Badge

spec-workflow-mcp MCP server

Copy to your README.md:

Score Badge

spec-workflow-mcp MCP server

Copy to your README.md:

Latest Blog Posts

MCP directory API

We provide all the information about MCP servers via our MCP API.

curl -X GET 'https://glama.ai/api/mcp/v1/servers/Pimzino/spec-workflow-mcp'

If you have feedback or need assistance with the MCP directory API, please join our Discord server