Inspectrum
Server Quality Checklist
Latest release: v0.2.3
- Disambiguation5/5
With only one tool, there is no possibility of confusion or overlapping purposes. The tool's purpose is clearly distinct within the server.
Naming Consistency5/5The lone tool follows a clear verb_noun pattern (review_plan), which is consistent and readable. Since there are no other tools, there is no inconsistency.
Tool Count3/5The server has only one tool, which feels thin for a typical MCP server. While it may be intentional for a narrow purpose, the count is on the borderline.
Completeness5/5The stated purpose is reviewing a plan, and the single tool directly accomplishes that with no apparent gaps. The domain is narrow and fully covered.
Average 4.2/5 across 1 of 1 tools scored.
See the Tool Scores section below for per-tool breakdowns.
- No community issues in the last 6 months
- 37 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.
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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
- Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Beyond annotations, the description discloses that it runs configured reviewer CLIs and writes a local session log, adding specific side-effect information that the annotations only hint at. This provides useful transparency about external behavior.
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?
The description is two sentences, front-loaded with the core purpose in the first sentence and side effects in the second. No wasted words, making it highly concise and well-structured.
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?
The description covers the primary purpose, side effects, and output summary. The presence of an output schema handles return value specifics. Minor gaps remain (e.g., configuration details) but are not critical given the richness of the schema and annotations.
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?
All parameters are fully described in the JSON schema (100% coverage), so the description does not add parameter-specific meaning. The baseline of 3 applies because the schema carries the load.
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 tool reviews a development/architecture plan, using a specific verb and resource, and describes the output as a consolidated verdict with prioritized findings. It is unambiguous and distinguishes the tool's function even without siblings.
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 context for use is clear: you review a plan. However, there are no explicit when-not-to-use instructions or alternative tools mentioned, given there are no siblings. The description implies usage effectively but lacks explicit exclusion guidance.
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.
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