QA Prompts MCP Server

Server Quality Checklist

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Latest release: v1.0.0
Disambiguation5/5
Each tool has a clearly distinct purpose: converting page source, analyzing failures, formatting bug reports, generating initialization code, converting manual tests, and reviewing code. No overlap.
Naming Consistency4/5
Five tools follow a consistent hyphen-separated lowercase pattern (e.g., xml-to-pom-locators), but 'Automation-initialization-code' starts with a capital letter, breaking the pattern.
Tool Count5/5
With 6 tools, the set covers the core QA automation workflow—locator generation, failure analysis, bug reporting, test generation, manual conversion, and code review—without being too sparse or bloated.
Completeness4/5
The tools cover the main stages of Appium automation: setup, analysis, reporting, and refactoring. Missing potential tools like test data generation or execution, but the scope is reasonable.
Average 3.4/5 across 6 of 6 tools scored.
See the Tool Scores section below for per-tool breakdowns.
- No community issues in the last 6 months
- 0 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 Apache 2.0.
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 provided. Description does not disclose whether the tool modifies code or is read-only, nor any side effects or required permissions. The phrase 'generates a report' implies non-destructive, but this is not explicit.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
Single sentence clearly states purpose and context. No extra words, but could benefit from bullet points for readability.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given no output schema and no annotations, the description covers the input adequately but does not explain what the PR Review Report contains (e.g., sections, metrics). For a report-generating tool, this is a moderate gap.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100% with the only parameter 'code' having a description that adds meaning: 'Paste the full class or relevant code blocks.' This clarifies the expected input format. However, baseline is 3 due to high coverage, and the description adds modest value.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
Description states a specific verb 'Performs a deep technical PR review' and resource 'automation code', with context (Appium + Java + TestNG). Distinguishes from siblings like 'analyze-test-failure' and 'convert-manual-to-automation'. However, name says 'refactor' but description says 'review', which is slightly inconsistent.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
No explicit guidance on when to use this tool versus alternatives. Does not mention prerequisites, file types, or when not to use. Siblings are listed but not differentiated.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries full burden. It only states that it converts into a template, but does not disclose safety (e.g., whether it is idempotent), side effects, or behavior on invalid input.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single efficient sentence with no redundancy. It is front-loaded with the action and resource.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
No output schema is provided, and the description omits details about the output format or potential errors. The reference to 'organization's template' assumes prior knowledge, leaving the agent underinformed.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100% with descriptions for both parameters. The description adds minor context (e.g., 'bug title or description' and example additional context) but does not significantly expand beyond the schema.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the verb 'converts' and identifies the resource (bug title/description) and output (standardized bug report). It distinguishes from sibling tools that handle XML, test failures, or automation code.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
No explicit guidance on when to use this tool versus alternatives. The description only implies conversion of unstructured reports, but fails to mention when not to use it or what alternatives exist.
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?
The description states it 'returns the prompt text', which implies a read-only, non-destructive operation. No annotations exist to contradict this. It clearly sets expectations about the tool's effect, though it could mention that no files are created.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single sentence that clearly conveys purpose and a key constraint (testsuite path). No redundant words. However, the long name and title add verbosity outside the description itself.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a tool that returns a prompt, the description does not explain the prompt's format, content, or how to use the output. It also lacks information about error cases or assumptions about the testsuite structure. Despite low complexity, important details are missing.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, and the schema already includes detailed guidance for className. The tool description adds only 'for class name: required' (redundant) and 'matching src/test/java/testsuite' (additional context). Overall marginal added value beyond schema.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states what the tool does: returns prompt text to generate Java test and page classes. The verb 'returns' clarifies it's a prompt-generator, distinguishing it from actual code generation despite the title using 'Generate'. It specifically mentions the testsuite path, aiding differentiation from sibling tools.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
No explicit guidance on when to use this tool versus alternatives. The description only says 'for class name: required' but does not explain prerequisites, context, or when to avoid using it. Given five sibling tools, more differentiation is needed.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
The description gives a high-level outcome but does not disclose behavioral details like whether it generates files, overwrites existing code, or requires specific input formats. With no annotations, the agent lacks critical context about the tool's side effects or constraints.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single sentence that efficiently communicates the tool's purpose and output characteristics without any extraneous information.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the moderate complexity (3 parameters, no output schema), the description adequately covers the core function but lacks details on return format, error handling, or integration context. It is minimally viable but could benefit from additional behavioral guidance.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
All three parameters are fully described in the schema (100% coverage). The description adds no additional semantic detail about the parameters beyond what the schema already provides, so baseline score of 3 is appropriate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool converts manual test cases into Appium + Java + TestNG automation scripts following POM architecture. It uses a specific verb and resource, and is well-differentiated from sibling tools like 'refactor-automation-code' or 'analyze-test-failure'.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides no guidance on when to use this tool versus alternatives, nor does it mention prerequisites or exclusions. The agent is left to infer context from tool names and sibling list.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description primarily informs behavior. It describes what the tool does (analyze, classify, assess, recommend) but does not disclose side effects, limitations, or whether it modifies logs or requires external dependencies. It is adequate but not thorough.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, well-structured sentence that conveys all key aspects without wasted words. It is appropriately sized and front-loaded with the primary action.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a tool with one simple input and no output schema, the description lists the conceptual outputs (root cause, severity, flakiness risk, fix recommendations) but does not specify the format or structure of the response. This may require the agent to infer the output nature. Adequate but could be more precise.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The schema describes the single parameter 'failureLogs' with sufficient detail. The tool description adds no additional depth about the parameter beyond what the schema already provides. With 100% schema coverage, baseline is 3.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's purpose: performing deep failure analysis of Appium test logs to determine root cause, classify severity, assess flakiness risk, and provide fix recommendations. It is specific with verb ('analyze') and resource ('Appium test logs'), and the outcomes distinguish it from unrelated sibling tools.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies usage for analyzing Appium test failures but does not explicitly state when to use versus alternatives or provide exclusions. Sibling tools are unrelated, so confusion is unlikely, but explicit guidance is missing.
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?
The description discloses the locator strategy priority (ID > Accessibility > XPath), which is a key behavioral trait. No annotations are provided, so the description carries the full burden. It does not mention any side effects, authentication, or limitations, but for a conversion tool this is acceptable.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single sentence that efficiently states the action, input, output, and key detail (priority strategy). It is front-loaded and contains no unnecessary words.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a tool with one parameter and no output schema or annotations, the description covers the purpose and strategy. However, it does not specify the output format (e.g., Java, Python) or any limitations, leaving some gaps. Overall adequate but could be more complete.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100% for the single parameter, and the schema description already explains it clearly. The tool description adds context about the conversion and strategy priority but does not enhance the parameter meaning beyond what the schema provides. Baseline score of 3 is appropriate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The title and description clearly state the tool converts Appium Inspector XML to POM locators with a specific priority strategy. The verb 'converts' and the resource 'Appium Inspector Page Source XML' are explicit, and it differentiates from sibling tools which handle analysis, bug reports, and initialization.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies usage when one has Appium Inspector XML and needs POM locators, but it lacks explicit guidance on when to use or not use this tool versus alternatives. No exclusions or prerequisites are mentioned.
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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