PictMCP
Server Quality Checklist
Latest release: v0.6.0
- Disambiguation5/5
Only one tool exists, so there is no possibility of confusion between tools.
Naming Consistency5/5The single tool name 'generate-test-cases' follows a clear verb_noun snake_case pattern, consistent in itself.
Tool Count2/5A single tool is below the typical 3-15 range for a well-scoped server, feeling too limited for most use cases.
Completeness2/5Only one operation is provided; missing complementary tools for managing configurations, viewing results, or iterative testing makes the surface incomplete.
Average 2.9/5 across 1 of 1 tools scored.
See the Tool Scores section below for per-tool breakdowns.
This repository is archived. Archived repositories automatically receive an F maintenance tier.
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 must convey behavioral traits. It only states that it executes PICT to generate test cases, but does not disclose side effects (e.g., file system changes, network calls), destructive potential, rate limits, or authentication needs. This is insufficient for a tool that executes external processes.
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?
The description is a single sentence that conveys the core action concisely. It is front-loaded but could benefit from slightly more context without losing conciseness. Currently, it is efficient.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given 2 parameters, one required array, and an optional string, the description is too brief. It does not explain the output format (despite an output schema being present), error handling, or any process details. An agent would lack important context for successful invocation.
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%, so baseline is 3. The description says 'with the given parameters and options' but adds no new meaning beyond the schema descriptions. It does not clarify how the two parameters relate or provide default behavior. Thus, it provides no extra value.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5Does the description clearly state what the tool does and how it differs from similar tools?
The description specifies 'Executes PICT' which is a specific tool for combinatorial test generation, clearly stating the action and resource. It mentions inputs and output (generate test cases). However, it assumes knowledge of what PICT is, and without sibling tools, differentiation is not needed.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance on when to use this tool vs alternatives, prerequisites, or when not to use it. The description lacks any usage context or exclusion criteria, leaving the agent without decision support.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
GitHub Badge
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- Confirm that the MCP server is working as expected.
- Confirm that there are no obvious security issues.
- Evaluate tool definition quality.
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