workflow-generator
Server Quality Checklist
Latest release: v0.3.1
- Disambiguation4/5
Both tools deal with workflow analysis, but they produce different outputs: analyze_workflow returns JSON, generate_workflow creates an HTML file. The descriptions make the distinction clear, though some conceptual overlap remains.
Naming Consistency5/5Both tool names follow a consistent verb_noun pattern with snake_case, making them predictable and easy to understand.
Tool Count2/5Only two tools for a 'workflow generator' server feels thin. The domain likely requires more operations (e.g., update, delete, validate) to be useful.
Completeness2/5The server provides analysis and generation but lacks update, delete, or customization tools. Basic lifecycle coverage is missing, limiting agent workflows.
Average 4.1/5 across 2 of 2 tools scored.
See the Tool Scores section below for per-tool breakdowns.
- No community issues in the last 6 months
- 29 commits in the last 12 weeks
- Last stable release on
- No critical vulnerability alerts
- No high-severity vulnerability alerts
- No code scanning findings
- CI is passing
This repository is licensed under MIT 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
- Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided. The description indicates read-only behavior ('no file written') and lists return fields, but lacks details on permissions, side effects, or other 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.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
One sentence covering the main action and a bulleted list of returns. Front-loaded, efficient, no wasted words.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a tool with one simple parameter and no output schema, the description is fairly complete: it explains the return value exactly. Could be enhanced by more explicit guidance on sibling tool differentiation.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100% (the only parameter 'project_dir' is described in the schema as 'Absolute path to the project root.'). The description adds no additional meaning beyond the schema.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the verb 'Scan' and resource 'project', specifies output format 'structured JSON', and distinguishes from sibling 'generate_workflow' by noting no file is written.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implicitly suggests use for analysis vs. generation via 'no file written' and listing of analysis fields, but does not explicitly contrast with 'generate_workflow' or provide when-to-use/alternatives.
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 provided, so description carries full burden. It discloses the tool scans directories, reads project files, and produces an HTML file. Could mention nondestructive nature or that it doesn't modify files, but current detail is sufficient.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5Is the description appropriately sized, front-loaded, and free of redundancy?
Description is a single paragraph that efficiently conveys purpose, supported projects, and detection capabilities. Every sentence adds value, though slightly lengthy; could be more structured but not wasteful.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given no output schema, description thoroughly explains what the generated HTML contains and lists many detectable components. Provides complete understanding of tool's capabilities and output.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100% and parameters are well-described in schema. Description adds context that output file is a visual workflow, but doesn't enhance meaning beyond schema definitions for the three parameters.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
Description clearly states the tool scans a project directory and generates a visual workflow HTML file. Verb 'generate' with specific resource 'WORKFLOW.html' and explicit detection capabilities distinguish it from sibling 'analyze_workflow'.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5Does the description explain when to use this tool, when not to, or what alternatives exist?
Description specifies supported project types (Python, Node.js, Go, mixed) and frameworks, giving clear context for when to use. However, lacks explicit 'when not to use' or comparison to alternatives like analyze_workflow.
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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