maturity_assessmentRun a TMMi maturity assessment for a project by providing the project name and optional area scores to identify maturity levels and guide quality improvements.
Run a TMMi maturity assessment for a project.
| Name | Required | Description | Default |
|---|---|---|---|
| scores | No | Optional dict mapping assessment areas to scores (1-5) | |
| project | Yes | Project name |
| Name | Required | Description | Default |
|---|---|---|---|
No arguments | |||
Changes observed during successful MCP inspections.
v0.1.0Does 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 only says an assessment is run; it does not state whether the operation is read-only, whether it consumes the optional 'scores' input, what data it accesses, or whether it produces side effects. The presence of an output schema covers the return shape but not broader behavior.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, front-loaded sentence with no wasted words. It is concise and easy to parse, though it is terse to the point of omitting useful context.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the low parameter count, 100% schema coverage, and existing output schema, the description is minimally adequate for invoking the tool. However, it lacks any explanation of TMMi context, how the optional scores are used, or when this assessment is appropriate, so it is not fully complete for an AI agent without external domain knowledge.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
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 'project' and 'scores'. The description adds no additional parameter meaning; 'TMMi maturity assessment' only weakly implies why 'scores' might be provided. Baseline 3 is appropriate because the schema does the heavy lifting.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description states a specific action ('Run a TMMi maturity assessment') and a resource ('a project'), making the tool's core function clear. It also distinguishes this tool from sibling analysis tools focused on coverage, defects, and code quality, though it does not explicitly name any alternatives.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
There is no guidance on when to use this tool versus alternatives such as analyze_code_quality or generate_quality_report. The description does not provide context, prerequisites, or exclusions, leaving the agent to infer appropriate usage solely from the tool name.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.