Claude Code Starter Kit MCP
Click on "Install Server".
Wait a few minutes for the server to deploy. Once ready, it will show a "Started" state.
In the chat, type
@followed by the MCP server name and your instructions, e.g., "@Claude Code Starter Kit MCPrun a security scan on the project"
That's it! The server will respond to your query, and you can continue using it as needed.
Here is a step-by-step guide with screenshots.
š¤ Claude Code Starter Kit
A production-ready boilerplate for integrating Claude Code into your development workflow. Automate testing, security scanning, code review, and routine maintenance tasks.
š¦ MCP Server
All commands and agents in this kit are also available as an MCP (Model Context Protocol) server, making them usable from Claude Desktop, Claude Code, or any MCP-compatible client.
Install
pip install claude-code-starter-kit-mcpSetup in Claude Code
Add to your project's .claude/settings.json (or ~/.claude/settings.json for global use):
{
"mcpServers": {
"claude-code-starter-kit": {
"command": "claude-code-starter-kit-mcp"
}
}
}Setup in Claude Desktop
Add to ~/Library/Application Support/Claude/claude_desktop_config.json (macOS) or %APPDATA%\Claude\claude_desktop_config.json (Windows):
{
"mcpServers": {
"claude-code-starter-kit": {
"command": "claude-code-starter-kit-mcp"
}
}
}Available MCP Tools
Tool | Maps to |
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| test-engineer agent |
| security-auditor agent |
| code-reviewer agent |
| bug-hunter agent |
All tools accept an optional arguments string (e.g. a file path or flags like --changed).
PyPI Auto-publish
Releases to PyPI are automated via GitHub Actions. Push a version tag to trigger a publish:
git tag v0.2.0
git push origin v0.2.0Requires a PyPI Trusted Publisher configured for the pypi environment in your repository settings.
Related MCP server: CodeSense MCP
šÆ What This Kit Provides
Feature | Description |
Automated Testing | Generate unit tests for new code automatically |
Security Scanning | Track vulnerabilities and get fix suggestions |
Code Review | AI-powered review on every PR |
Bug Detection | Monitor repo for common issues and anti-patterns |
Documentation | Auto-generate and update docs |
š Quick Start
1. Copy to Your Project
# Clone this repo
git clone https://github.com/dachivadachkoria/claude-code-starter-kit.git
# Copy the .claude directory to your project
cp -r claude-code-starter-kit/.claude your-project/
cp claude-code-starter-kit/CLAUDE.md your-project/
2. Customize CLAUDE.md
Edit CLAUDE.md in your project root to match your:
Tech stack
Testing conventions
Code style
Project structure
3. Start Using
cd your-project
claude
# Now use the commands:
/test src/myfile.py # Generate tests
/security-check # Check vulnerabilities
/detailed-review # Code review
/fix-bugs # Auto-fix common issuesš Repository Structure
.claude/
āāā settings.json # Claude Code configuration
āāā commands/ # Slash commands
ā āāā test.md # /test - Generate unit tests
ā āāā test-coverage.md # /test-coverage - Coverage analysis
ā āāā security-check.md # /security-check - Vulnerability check
ā āāā detailed-review.md # /detailed-review - Code review
ā āāā fix-bugs.md # /fix-bugs - Auto-fix issues
ā āāā docs.md # /docs - Generate documentation
ā āāā refactor.md # /refactor - Safe refactoring
āāā agents/ # Specialized AI agents
ā āāā test-engineer.md # Testing specialist
ā āāā security-auditor.md # Security expert
ā āāā code-reviewer.md # Review specialist
ā āāā bug-hunter.md # Bug detection expert
āāā knowledge-base/ # Project-specific guidelines
āāā testing-guide.md
āāā security-checklist.md
CLAUDE.md # Project context (customize this!)
.github/
āāā workflows/
āāā claude-review.yml # Optional: CI integrationš§ Available Commands
Testing Commands
Command | Description | Example |
| Generate tests for a file |
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| Test all changed files |
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| Analyze and improve coverage |
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Security Commands
Command | Description | Example |
| Full security audit |
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| Check dependencies only |
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| Auto-fix vulnerabilities |
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Code Quality Commands
Command | Description | Example |
| Review staged changes |
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| Review specific file |
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| Detect and fix issues |
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| Safe refactoring |
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Documentation Commands
Command | Description | Example |
| Generate/update docs |
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| Document specific file |
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š” Built-in Commands
Claude Code has excellent built-in commands you should know:
/security-review- AI-powered security scanning/review- Code review/init- Initialize project with CLAUDE.md/compact- Compress context when running low
š”ļø Safety Guidelines
What Claude Code CAN Do Safely
ā
Generate and run tests
ā
Analyze code for vulnerabilities
ā
Suggest fixes with explanations
ā
Create documentation
ā
Refactor with your approval
What Requires Your Review
ā ļø Any changes to authentication/authorization
ā ļø Database migrations
ā ļø Environment/config changes
ā ļø Dependency updates
ā ļø Production deployment scripts
Best Practices
Review before commit - Always review generated code
Use branches - Let Claude work on feature branches
Incremental changes - Small, focused tasks work best
Test first - Run tests before accepting changes
Version control - Commit frequently, revert if needed
š Language-Specific Setup
# Add to your CLAUDE.md
## Testing
- Framework: pytest
- Run: `pytest tests/ -v`
- Coverage: `pytest --cov=src --cov-report=html`
## Style
- Formatter: black, isort
- Linter: ruff or flake8
- Types: mypy# Add to your CLAUDE.md
## Testing
- Framework: jest or vitest
- Run: `npm test`
- Coverage: `npm test -- --coverage`
## Style
- Formatter: prettier
- Linter: eslint
- Types: TypeScript strict mode# Add to your CLAUDE.md
## Testing
- Framework: testing + testify
- Run: `go test ./...`
- Coverage: `go test -coverprofile=coverage.out ./...`
## Style
- Formatter: gofmt, goimports
- Linter: golangci-lintš¤ Contributing
Contributions welcome! Please read CONTRIBUTING.md for guidelines.
Ideas for Contributions
More language-specific templates
Framework-specific commands (Django, React, etc.)
CI/CD integration examples
IDE extension recommendations
Video tutorials
š Resources
š License
MIT License - feel free to use in personal and commercial projects.
Made with š¤ by the community, for the community
Star ā this repo if you find it useful!
Available Tools
12 toolsagent_bug_hunterC
Expert at detecting bugs, anti-patterns, and potential issues
| Name | Required | Description | Default |
|---|---|---|---|
| arguments | No | Optional arguments for the tool (e.g. a file path or flags like --changed, --dry-run). |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries full burden but discloses no behavioral traits. It does not state whether the tool scans files, modifies state, or requires permissions.
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 brief sentence, which is concise. However, it lacks structure or front-loading of key information.
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 no annotations, no output schema, and a vague description, the tool's behavior and use case are poorly explained. The description does not compensate for the lack of structured context.
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 coverage is 100% for the single optional 'arguments' parameter. However, the tool description adds no extra meaning beyond what the schema already provides, so baseline of 3 is appropriate.
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 'Expert at detecting bugs, anti-patterns, and potential issues' is vague and does not specify the tool's specific action or resource. It fails to distinguish from siblings like agent_code_reviewer or agent_security_auditor, which may have overlapping purposes.
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?
No guidance is provided on when to use this tool versus alternatives. Siblings exist but the description offers no selection criteria or context.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
agent_code_reviewerC
Expert code reviewer for quality and maintainability
| Name | Required | Description | Default |
|---|---|---|---|
| arguments | No | Optional arguments for the tool (e.g. a file path or flags like --changed, --dry-run). |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are present, and the description provides no behavioral details such as whether the tool is read-only, requires authentication, or has any side effects. It merely states the tool is an 'expert code reviewer' without any behavioral context.
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 short sentence, which is concise but underspecified. It lacks structure and key information, making it minimally adequate but not efficient for agent use.
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 no output schema and low parameter complexity, the description should still cover return values or limitations. It does not, and with sibling tools present, more context is needed to differentiate behavior.
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 coverage is 100% with one optional parameter 'arguments' that includes a description. The tool description adds no additional meaning beyond the schema, so it meets the baseline for high coverage but does not enhance understanding.
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 'Expert code reviewer for quality and maintainability' which indicates the tool reviews code for quality and maintainability. However, it is vague and does not distinguish from sibling tools like command_detailed_review or agent_bug_hunter, which may also involve code review.
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?
No guidance is provided on when to use this tool versus alternatives. It does not specify prerequisites, contexts, or exclusions, leaving the agent to infer usage from the name alone.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
agent_security_auditorD
Security expert for vulnerability detection and remediation
| Name | Required | Description | Default |
|---|---|---|---|
| arguments | No | Optional arguments for the tool (e.g. a file path or flags like --changed, --dry-run). |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are present, and the description gives no insight into behavior such as side effects, required permissions, or operational scope (e.g., file system access, network calls).
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 extremely short, but it is not concise in the sense of being information-rich. It omits critical details, making it under-specified.
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 lack of annotations, output schema, and detailed parameter info, the description is severely incomplete. An agent cannot determine what inputs to provide or what results to expect.
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 coverage is 100% with the parameter 'arguments' described appropriately. The description adds no further meaning beyond the schema's own parameter description.
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 'Security expert for vulnerability detection and remediation' indicates a general purpose but lacks specificity. It does not distinguish this tool from siblings like command_security_check or agent_bug_hunter, which likely have overlapping functions.
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?
The description provides no guidance on when to use this tool versus alternatives. No prerequisites, context, or exclusion criteria are mentioned.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
agent_test_engineerC
Specialized agent for comprehensive test generation
| Name | Required | Description | Default |
|---|---|---|---|
| arguments | No | Optional arguments for the tool (e.g. a file path or flags like --changed, --dry-run). |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, and the description fails to disclose any behavioral traits such as side effects, permissions, or behavior when called. The description only states a vague purpose without actionable behavioral details.
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 very short (one sentence) but lacks substance. It is concise but not informative, failing to earn its place with meaningful content.
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 tool is an agent with many siblings and no output schema, the description is severely incomplete. It does not explain what 'comprehensive test generation' entails, how arguments affect behavior, or what the agent returns.
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 coverage is 100% for the single parameter, and the description adds no extra meaning beyond the schema's own description. The baseline score of 3 is appropriate as the schema already handles parameter documentation.
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 indicates the tool is for test generation, which is clear but vague. It does not specify the type of tests (unit, integration, etc.) or how it differs from sibling tools like command_test or command_test_coverage.
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?
No guidance is provided on when to use this agent versus alternatives. With many sibling agents and commands, the lack of usage context makes it difficult for an AI agent to select the correct tool.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
command_detailed_reviewB
Structured code review with checklist and severity ratings
| Name | Required | Description | Default |
|---|---|---|---|
| arguments | No | Optional arguments for the tool (e.g. a file path or flags like --changed, --dry-run). |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description must disclose behavioral traits. It only mentions the output format (checklist, severity ratings) but omits whether the tool is read-only, requires permissions, or has side effects.
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?
One sentence with no unnecessary words. Could be slightly more explicit but is efficient.
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?
No output schema and no details on checklist format, severity scale, or expected return values. Incomplete for a tool performing a complex code review.
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 coverage is 100% and the parameter 'arguments' is documented. The description does not add additional meaning beyond the schema, so baseline 3 applies.
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 clearly states the tool performs a structured code review with a checklist and severity ratings, distinguishing it from generic code review or security-specific siblings.
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?
No guidance on when to use this tool vs alternatives like agent_code_reviewer or command_security_check; lacking contextual usage hints.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
command_docsC
Generate or update documentation for code
| Name | Required | Description | Default |
|---|---|---|---|
| arguments | No | Optional arguments for the tool (e.g. a file path or flags like --changed, --dry-run). |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries full burden but only states 'Generate or update documentation' without disclosing behavioral traits: whether it modifies files, required permissions, side effects, or how modes like --changed or --dry-run behave. The example arguments hint at modes but are not explained.
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 fluff. Every word is relevant to the tool's purpose.
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 single parameter, no output schema, and lack of annotations, the description is too minimal. It does not explain default behavior, output format, or how to effectively use the tool among many siblings.
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 coverage is 100%, and the schema description already explains the optional argument (file path or flags). The tool description adds no new meaning, so baseline of 3 is appropriate.
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 'Generate or update documentation for code' clearly states the tool's purpose with a specific verb-resource pair. It reasonably distinguishes from sibling tools like command_test or command_refactor, but could be more precise about scope (e.g., current project, commit).
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?
No guidance is provided on when to use this tool versus alternatives (e.g., agent_code_reviewer, command_detailed_review). The description does not mention when documentation generation is appropriate or any prerequisites.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
command_fix_bugsC
Detect and fix common bugs, anti-patterns, and code issues
| Name | Required | Description | Default |
|---|---|---|---|
| arguments | No | Optional arguments for the tool (e.g. a file path or flags like --changed, --dry-run). |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description must disclose behavioral traits. It indicates the tool 'fixes' issues implying mutation, but it does not explain side effects, reversibility, permission requirements, or scope of changes. This is insufficient for a tool that modifies code.
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 concise, consisting of a single sentence with no redundancy. However, it lacks front-loading of critical information such as whether it modifies files or requires arguments.
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 tool has only one optional parameter and no output schema, the description is partially complete. It explains the tool's purpose but omits important context like the extent of fixes, safety, and typical use cases.
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% (one parameter with a description). The description adds examples like '--changed' and '--dry-run', which help clarify usage beyond the schema. However, the tool description itself does not elaborate on parameter semantics, so baseline 3 is appropriate.
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 clearly states the tool detects and fixes bugs, anti-patterns, and code issues. It uses a specific verb-resource pair, but it does not differentiate from sibling tools like agent_bug_hunter or command_refactor, which may have overlapping purposes.
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?
The description provides no guidance on when to use this tool versus alternatives (e.g., agent_bug_hunter, command_refactor). There is no mention of context, prerequisites, or exclusion criteria.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
command_monitorC
Monitor repository health, track issues, and identify maintenance tasks
| Name | Required | Description | Default |
|---|---|---|---|
| arguments | No | Optional arguments for the tool (e.g. a file path or flags like --changed, --dry-run). |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, and the description does not disclose behavioral traits such as whether the tool is read-only, destructive, or requires special permissions. The term 'monitor' suggests read-only, but the 'arguments' parameter hints at command execution, creating uncertainty.
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 sentence, but it is vague and does not efficiently convey the tool's purpose. It could be more concise and informative.
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 tool's single parameter and lack of output schema, the description should clarify what specific repository health metrics are monitored or what tasks are identified. It falls short, leaving the agent with incomplete understanding.
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% (the 'arguments' parameter is described in schema). The tool description adds no additional meaning beyond the schema, so it meets the baseline but does not enhance understanding.
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 'Monitor repository health, track issues, and identify maintenance tasks' uses vague verbs and a broad resource, lacking specificity about the tool's exact action. It distinguishes somewhat from sibling tools focused on specific tasks like bug hunting or code review, but the purpose remains fuzzy.
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?
No explicit guidance on when to use this tool versus siblings. The description does not mention alternatives or provide context for when this tool is appropriate, leaving the agent to guess.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
command_refactorB
Safely refactor code with test verification
| Name | Required | Description | Default |
|---|---|---|---|
| arguments | No | Optional arguments for the tool (e.g. a file path or flags like --changed, --dry-run). |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description bears full responsibility for behavioral disclosure. 'Safely refactor' is vague; it does not clarify what 'safe' means, whether tests are run, if code is modified, or if the operation is destructive. Minimal transparency beyond the headline.
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, focused sentence with no wasted words. It is efficient and front-loaded with the key purpose.
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?
For a refactoring tool, the description lacks detail on required prerequisites, side effects, return values, or error conditions. Given no output schema and sparse annotations, more context (e.g., 'requires passing tests', 'modifies files in place') would be needed for complete understanding.
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?
The input schema already describes the single 'arguments' parameter with examples (file path, flags). The tool description adds no additional meaning or constraints beyond what the schema provides. Schema coverage is 100%, so baseline 3 is appropriate.
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 clearly states the verb ('refactor'), the resource ('code'), and the method ('with test verification'). It distinguishes itself from sibling tools like command_fix_bugs or command_test by indicating a safe, test-verified refactoring approach.
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?
The description implies usage for safe refactoring with tests, but it does not explicitly state when to use this tool versus alternatives like command_detailed_review or command_fix_bugs. No exclusions or context are provided.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
command_security_checkC
Scan for security vulnerabilities in code and dependencies
| Name | Required | Description | Default |
|---|---|---|---|
| arguments | No | Optional arguments for the tool (e.g. a file path or flags like --changed, --dry-run). |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations exist, so the description must fully disclose behavior. It only states 'scan for security vulnerabilities', implying a non-destructive read, but fails to detail whether it requires specific permissions, produces output, or affects the system. Key behavioral traits are missing.
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 sentence, very concise with no unnecessary words. It is front-loaded with the core action, but could benefit from additional context without adding significant length.
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 single optional parameter and lack of output schema or annotations, the description is too minimal. It does not explain the scanning process, output format, or safety considerations, making it insufficient for an agent to invoke correctly.
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% with one parameter 'arguments' already described. The description adds no extra meaning beyond what the schema provides, so a baseline score of 3 is appropriate.
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 clearly states the tool scans for security vulnerabilities in code and dependencies, providing a specific verb and resource. It differentiates from siblings like 'agent_security_auditor' by implying a command-line scanning tool, but lacks explicit distinction.
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?
No guidance is provided on when to use this tool versus alternatives like 'agent_security_auditor' or 'command_detailed_review'. There are no exclusions, prerequisites, or context for when it is appropriate to invoke.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
command_testB
Generate comprehensive unit tests for files. Use /test or /test --changed
| Name | Required | Description | Default |
|---|---|---|---|
| arguments | No | Optional arguments for the tool (e.g. a file path or flags like --changed, --dry-run). |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, and the description does not disclose behavioral details such as whether the tool modifies files, requires permissions, or has side effects.
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 concise with two sentences, front-loaded with the purpose, and contains no unnecessary words.
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 lack of output schema and annotations, the description adequately covers usage but misses details on behavioral outcomes and error conditions.
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?
The single parameter 'arguments' is well-described in the schema (100% coverage). The description adds usage examples but does not provide additional semantic value beyond the schema.
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 clearly states it generates unit tests for files and provides a usage example. However, it does not differentiate from sibling tools like 'command_test_coverage' or 'agent_test_engineer'.
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?
The description includes usage examples ('Use /test <file> or /test --changed') but lacks explicit guidance on when not to use this tool or how it compares to alternatives.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
command_test_coverageC
Analyze test coverage and generate tests for uncovered code
| Name | Required | Description | Default |
|---|---|---|---|
| arguments | No | Optional arguments for the tool (e.g. a file path or flags like --changed, --dry-run). |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are present, so the description must fully disclose behavior. While it states the tool analyzes coverage and generates tests, it omits important traits such as whether it modifies files, runs tests, requires permissions, or has side effects. This is a significant gap for a generative tool.
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, concise sentence that front-loads the core purpose. It is appropriately short for a low-complexity tool, though it could include slightly more detail without losing conciseness.
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 complexity (one optional parameter, no output schema), the description is minimally viable but incomplete. It lacks details on input format, expected output, and behavioral constraints, leaving the agent uncertain about how to invoke the tool correctly.
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?
The schema has 100% description coverage for its single parameter, and the parameter description provides examples (file path, --changed, --dry-run). However, the tool description adds only marginal value beyond the schema, as the examples are generic and do not explain how to use them effectively or what each flag does.
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 clearly identifies the tool's purpose: analyzing test coverage and generating tests for uncovered code. It uses a specific verb ('analyze', 'generate') and resource ('test coverage'). However, it does not explicitly distinguish itself from similar siblings like command_test or agent_test_engineer, which could also handle coverage tasks.
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?
The description provides no guidance on when to use this tool versus alternatives (e.g., command_test or agent_test_engineer). There are no exclusions, prerequisites, or context provided. Usage is only implied by the tool's name.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Tool Schema Changelog
Recent tool additions, removals, and schema changes observed during successful MCP inspections. Dates show when Glama detected each change.
12 tool updates
v0.1.0- First observed
agent_bug_hunter - First observed
agent_code_reviewer - First observed
agent_security_auditor - First observed
agent_test_engineer - First observed
command_detailed_review - First observed
command_docs - First observed
command_fix_bugs - First observed
command_monitor - First observed
command_refactor - First observed
command_security_check - First observed
command_test - First observed
command_test_coverage
TDQS
There is overlap between agent tools (e.g., agent_bug_hunter, agent_code_reviewer) and command tools (e.g., command_fix_bugs, command_detailed_review) that cover similar concerns. However, descriptions differentiate detection vs. action, so some ambiguity remains.
Tools follow two consistent prefixes ('agent_' and 'command_') and use snake_case throughout. While the pattern is clear, the split between role-based and action-based naming could be more uniform.
With 12 tools covering code review, bug detection, security, testing, documentation, refactoring, and monitoring, the count is well-scoped for a comprehensive code quality assistant.
The toolkit covers the full lifecycle of code quality: analysis (agents), fixes, tests, documentation, monitoring, and refactoring. No obvious gaps for its stated purpose.
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