CNPC JavaDoc MCP Server
Server Quality Checklist
Latest release: v1.1.0
- Disambiguation5/5
The two tools have clearly distinct purposes: 'search' handles querying the JavaDoc database with a powerful search syntax, while 'show-hierarchy' displays class inheritance. There is no overlap in functionality.
Naming Consistency5/5Both tool names follow a consistent verb pattern (imperative), with 'search' being a single verb and 'show-hierarchy' using a verb_noun format with hyphenation. The style is uniform and predictable.
Tool Count3/5With only two tools, the server feels somewhat thin for a JavaDoc browsing domain. While the search tool is powerful, additional tools like 'get_class_details' or 'list_versions' would enhance the coverage. The count is borderline acceptable but not optimal.
Completeness3/5The tool set covers search and hierarchy but misses direct access to detailed documentation for specific methods or fields. Users relying solely on these tools may face dead ends when needing comprehensive class or method info, indicating notable gaps.
Average 4.3/5 across 2 of 2 tools scored.
See the Tool Scores section below for per-tool breakdowns.
- No community issues in the last 6 months
- 2 commits 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 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?
Annotations already declare readOnlyHint, openWorldHint, idempotentHint, and non-destructive, so the tool's safety profile is clear. The description adds behavioral context by explaining the two return sections and providing an example output, going beyond what annotations offer.
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 concise, front-loads the purpose, and includes an example. It is efficiently structured, though it could be slightly tighter.
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 simple read-only tool with two well-documented parameters, the description covers the purpose, return structure, and provides an example. With no output schema, the description adequately compensates.
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 the schema already documents both parameters. The description mentions dot notation and lists supported versions, but these add little beyond the schema. The baseline of 3 is appropriate.
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 it displays a class inheritance hierarchy for CNPC, and distinguishes itself from the sibling tool 'search' by its specific function. It explicitly mentions the two output sections (Hierarchy and Subs) and provides an example.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies usage when needing class hierarchy, but does not provide explicit guidance on when to use this tool versus alternatives, nor does it mention when not to use it.
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?
Annotations declare read-only, open-world, idempotent, non-destructive. The description adds behavioral details like scoring, output deduplication, and format templates, enhancing transparency beyond annotations.
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 well-structured with clear sections for syntax, modifiers, scoring, patterns, and version format. Every sentence serves a purpose, and it is appropriately sized for the complexity.
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 5 parameters, no output schema, and complex query syntax, the description covers all necessary details: syntax, modifiers, scoring, common patterns, version format, and output template. No gaps.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters5/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
With 100% schema coverage, the description still adds substantial value by explaining expression syntax in depth, listing modifiers, providing examples, and detailing output variables, far exceeding baseline.
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 searches the CNPC JavaDoc API for methods and fields across versions and forks, distinguishing it from the sibling 'show-hierarchy' which likely displays hierarchy instead of searching.
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 provides extensive usage guidelines with syntax, modifiers, scoring, and common patterns. It lacks explicit when-not-to-use compared to the sibling, but the detail effectively guides correct usage.
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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