GitMCP
This server provides comprehensive Git repository management and GitHub/Gitea integration through the Model Context Protocol (MCP), enabling AI assistants to interact with repositories programmatically.
Local Git Operations
Initialize, clone, stage, commit, push, pull, and check status of repositories
Branch management: create, list, switch, and merge branches
GitHub & Gitea Integration
Create, list, and get repositories on both GitHub and Gitea platforms
Authentication management: set tokens, retrieve token info, and test provider connections
Release & Version Management
Create and list releases on GitHub/Gitea
Bump version numbers (major/minor/patch) and validate semantic versions
Backup Operations
Create backups of repositories (optionally including issues and pull requests) and list existing backups
Configuration & Diagnostics
Set, get, and list server configuration values
Ping, health checks, version info, and environment variable inspection
AI Assistant Integration
Transform any public GitHub repository or GitHub Pages site into an AI-accessible documentation hub
Retrieve the latest documentation and code directly from source, reducing hallucinations
Smart search for documentation and code, optimizing token usage
Fetch content from external URLs referenced in documentation
Works with AI assistants such as Cursor, Claude Desktop, and other MCP-compatible clients.
Enables AI assistants to access and understand any GitHub project's documentation through semantic search capabilities, without requiring any setup or modifications to the repository.
Provides AI assistants with access to GitHub Pages sites' documentation through a dedicated subdomain format, offering the same semantic search capabilities as regular GitHub repositories.
Mentioned as an example project that can be accessed through the GitMCP service, specifically through the GitHub Pages integration.
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., "@GitMCPexplain how to use the three.js scene creation API"
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.
GitMCP
🤔 What is GitMCP?
Stop vibe-hallucinating and start vibe-coding!
GitMCP is a free, open-source, remote Model Context Protocol (MCP) server that transforms any GitHub project (repositories or GitHub pages) into a documentation hub. It enables AI tools like Cursor to access up-to-date documentation and code, even if the LLM has never encountered them, thereby eliminating code hallucinations seamlessly.
GitMCP supports two flavors -
Specific Repository (
gitmcp.io/{owner}/{repo}or{owner}.gitmcp.io/{repo}): Use these when you primarily work with a select number of libraries. This ensures your AI assistant always targets the correct project, enhancing security and relevance by preventing access to unintended repositories.Generic Server (
gitmcp.io/docs): Use this for maximum flexibility when you need to switch between different repositories frequently. The AI assistant will prompt you (or decide based on context) which repository to access for each request. Be mindful that this relies on correctly identifying the target repository each time.
With GitMCP:
AI assistants access the latest documentation and code directly from the source.
Get accurate API usage and reliable code examples.
Work effectively even with niche, new, or rapidly changing libraries.
Significantly reduced hallucinations and improved code correctness.
For example, this side-by-side comparison shows the result for the same one-shot prompt in Cursor when creating a three.js scene -
https://github.com/user-attachments/assets/fbf1b4a7-f9f0-4c0e-831c-4d64faae2c45
Related MCP server: GitMCP
✨ Features
😎 Latest Documentation on ANY GitHub Project: Grant your AI assistant seamless access to the GitHub project's documentation and code. The built-in smart search capabilities help find exactly what the AI needs without using too many tokens!
🧠 No More Hallucinations: With GitMCP, your AI assistant can provide accurate and relevant answers to your questions.
☁️ Zero Setup: GitMCP runs in the cloud. Simply add the chosen GitMCP URL as an MCP server in your IDE — no downloads, installations, signups, or changes are required.
💬 Embedded Chat: Start quickly by chatting directly with the repository's documentation through our in-browser chat!
✅ Open, Free, and Private: GitMCP is open-source and completely free to use. It doesn't collect personal information or store queries. You can even self-host it!
🚀 Getting Started
Using GitMCP is easy! Simply follow these steps:
Step 1: Choose the type of server you want
Choose one of these URL formats depending on what you want to connect to:
For GitHub repositories:
gitmcp.io/{owner}/{repo}For GitHub Pages sites:
{owner}.gitmcp.io/{repo}For a generic tool that supports any repository (dynamic):
gitmcp.io/docs
Replace {owner} with the GitHub username or organization name, and {repo} with the repository name.
For your convenience, you can also use the conversion tool on the landing page to format the GitHub URL into an MCP URL!
Step 2: Connect your AI assistant
Select your AI assistant from the options below and follow the configuration instructions:
Connecting Cursor
Update your Cursor configuration file at ~/.cursor/mcp.json:
{
"mcpServers": {
"gitmcp": {
"url": "https://gitmcp.io/{owner}/{repo}"
}
}
}Connecting Claude Desktop
In Claude Desktop, go to Settings > Developer > Edit Config
Replace the configuration with:
{ "mcpServers": { "gitmcp": { "command": "npx", "args": [ "mcp-remote", "https://gitmcp.io/{owner}/{repo}" ] } } }
Connecting Windsurf
Update your Windsurf configuration file at ~/.codeium/windsurf/mcp_config.json:
{
"mcpServers": {
"gitmcp": {
"serverUrl": "https://gitmcp.io/{owner}/{repo}"
}
}
}Connecting VSCode
Update your VSCode configuration file at .vscode/mcp.json:
{
"servers": {
"gitmcp": {
"type": "sse",
"url": "https://gitmcp.io/{owner}/{repo}"
}
}
}Connecting Cline
Update your Cline configuration file at ~/Library/Application Support/Code/User/globalStorage/saoudrizwan.claude-dev/settings/cline_mcp_settings.json:
{
"mcpServers": {
"gitmcp": {
"url": "https://gitmcp.io/{owner}/{repo}",
"disabled": false,
"autoApprove": []
}
}
}Connecting Highlight AI
Open Highlight AI and click the plugins icon (@ symbol) in the sidebar
Click Installed Plugins at the top of the sidebar
Select Custom Plugin
Click Add a plugin using a custom SSE URL
Plugin name: gitmcp
SSE URL: https://gitmcp.io/{owner}/{repo}
For more details on adding custom MCP servers to HighlightAI, refer to the documentation.
Connecting Augment Code
Open Augment Code settings
Navigate to the MCP section
Add a new MCP server with the following details:
Name the MCP server: git-mcp Docs
Use this command:
npx mcp-remote https://gitmcp.io/{owner}/{repo}Or use the following configuration:
{
"mcpServers": {
"git-mcp Docs": {
"command": "npx",
"args": [
"mcp-remote",
"https://gitmcp.io/{owner}/{repo}"
]
}
}
}Connecting Msty AI
Open Msty Studio
Go to Tools > Import Tools from JSON Clipboard
Paste the following configuration:
{
"mcpServers": {
"git-mcp Docs": {
"command": "npx",
"args": [
"mcp-remote",
"https://gitmcp.io/{owner}/{repo}"
]
}
}
}For more details on configuring MCP servers in Augment Code, visit the Augment Code documentation.
Note: Remember to replace
{owner}and{repo}with the actual GitHub username/organization and repository name. You can also use the dynamic endpointhttps://gitmcp.io/docsto allow your AI to access any repository on demand.
⚙ How It Works
GitMCP connects your AI assistant to GitHub repositories using the Model Context Protocol (MCP), a standard that lets AI tools request additional information from external sources.
What happens when you use GitMCP:
You provide the GitMCP URL to your AI assistant (e.g.,
gitmcp.io/microsoft/typescript). GitMCP exposes tools like documentation fetching, smart search, code search, etc.Prompt the AI assistant on documentation/code-related questions.
Your AI sends requests to GitMCP to use its tools (with your approval).
GitMCP executes the AI's request and returns the requested data.
Your AI receives the information and generates a more accurate, grounded response without hallucinations.
Supported Documentation
GitMCP currently supports the following documents (in order of priority):
AI-optimized version of the project's documentation
README.md/root
💡 Examples
Here are some examples of how to use GitMCP with different AI assistants and repositories:
Example 1: Using Windsurf with a specific repository
For the GitHub repository https://github.com/microsoft/playwright-mcp, add https://gitmcp.io/microsoft/playwright-mcp as an MCP server to Windsurf.
Prompt to Claude:
"How do I use the Playwright MCP"
Windsurf will pull the relevant documentation from GitMCP to implement the memory feature correctly.
Example 2: Using Cursor with a GitHub Pages site
For the GitHub Pages site langchain-ai.github.io/langgraph, add https://langchain-ai.gitmcp.io/langgraph as an MCP server to Cursor.
Prompt to Cursor:
"Add memory to my LangGraph agent"
Cursor will pull the relevant documentation and code from GitMCP to correctly implement the memory feature.
Example 3: Using Claude Desktop with the dynamic endpoint
You don't have to pick specific repositories. The generic gitmcp.io/docs endpoint allows AI to pick the GitHub project on the fly!
Prompt to any AI assistant:
"I want to learn about the OpenAI Whisper speech recognition model. Explain how it works."
Claude will pull the data from GitMCP and answer the question.
🛠️ Tools
GitMCP provides AI assistants with several valuable tools to help them access, understand, and query GitHub repositories.
fetch_<repo-name>_documentation
This tool gets the primary documentation from a GitHub repository. It works by retrieving relevant documentation (e.g., llms.txt). This gives the AI a good overview of what the project is about
When it's useful: For general questions about a project's purpose, features, or how to get started
search_<repo-name>_documentation
This tool lets the AI search through a repository's documentation by providing a specific search query. Instead of loading all the documentation (which could be very large), it uses intelligent search to find just the relevant parts.
When it's useful: For specific questions about particular features, functions, or concepts within a project
fetch_url_content
This tool helps the AI get information from links mentioned in the documentation. It retrieves the content from those links and converts it to a format the AI can easily read.
When it's useful: When documentation references external information that would help answer your question
search_<repo-name>_code
This tool searches through the actual code in the repository using GitHub's code search. It helps AI find specific code examples or implementation details.
When it's useful: When you want examples of how something is implemented or need technical details not covered in documentation
Note: When using the dynamic endpoint (
gitmcp.io/docs), these tools are named slightly differently (fetch_generic_documentation,search_generic_code, andsearch_generic_documentation) and need additional information about which repository to access.
📊 Badge
GitMCP has a badge for your repository's README. It allows users to quickly access your documentation through their IDE or browser (using the embedded chat). It also showcases how many times your documentation has been accessed through GitMCP.
Example (idosal/git-mcp):
Adding the Badge to Your Repository
Add the following to your README.md:
[](https://gitmcp.io/OWNER/REPO)Replace OWNER with your GitHub username or organization, and REPO with your repository name.
How We Count Views
Increment for each tool call on the specific repository.
Customizing the Badge
You can customize the badge's appearance with parameters:
Parameter | Description | Default | Example |
| Color for the badge value |
|
|
| Badge label |
|
|
Please reach out if you need help!
❓ FAQ
What is the Model Context Protocol?
The Model Context Protocol is a standard that allows AI assistants to request and receive additional context from external sources in a structured manner, enhancing their understanding and performance.
Does GitMCP work with any AI assistant?
Yes, GitMCP is compatible with any AI assistant supporting the Model Context Protocol, including tools like Cursor, VSCode, Claude, etc.
Is GitMCP compatible with all GitHub projects?
Absolutely! GitMCP works with any public GitHub repository without requiring any modifications. It prioritizes the llms.txt file and falls back to README.md or other pages if the former is unavailable. Future updates aim to support additional documentation methods and even generate content dynamically.
Does GitMCP cost money?
No, GitMCP is a free service to the community with no associated costs.
🔒 Privacy
GitMCP is deeply committed to its users' privacy. The service doesn't have access to or store any personally identifiable information as it doesn't require authentication. In addition, it doesn't store any queries sent by the agents. Moreover, as GitMCP is an open-source project, it can be deployed independently in your environment.
GitMCP only accesses content that is already publicly available and only when queried by a user. GitMCP does not automatically scrape repositories. Before accessing any GitHub Pages site, the code checks for robots.txt rules and follows the directives set by site owners, allowing them to opt out. Please note that GitMCP doesn't permanently store data regarding the GitHub projects or their content.
👥 Contributing
We welcome contributions, feedback, and ideas! Please review our contribution guidelines.
Local Development Setup
Clone the repository
git clone https://github.com/idosal/git-mcp.git cd git-mcpInstall dependencies
pnpm installRun locally for development
npm run dev # or pnpm dev
Using MCP Inspector for Testing
Install the MCP Inspector tool:
npx @modelcontextprotocol/inspectorIn the inspector interface:
Set Transport Type to
SSEEnter your GitMCP URL (e.g.,
http://localhost:5173/docs)Click "Connect"
📄 License
This project is licensed under the Apache License 2.0.
Disclaimer
GitMCP is provided "as is" without warranty of any kind. While we strive to ensure the reliability and security of our service, we are not responsible for any damages or issues that may arise from its use. GitHub projects accessed through GitMCP are subject to their respective owners' terms and conditions. GitMCP is not affiliated with GitHub or any of the mentioned AI tools.
Star History
Available Tools
32 toolsauth_get_token_infoC
Get token information for a provider
| Name | Required | Description | Default |
|---|---|---|---|
| provider | Yes | Provider name |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full burden of behavioral disclosure. It states this is a 'Get' operation, implying read-only behavior, but doesn't specify whether it requires authentication, what information is returned (e.g., token expiry, scopes), or any rate limits. This leaves significant gaps for a tool handling sensitive token data.
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, efficient sentence with no wasted words. It's front-loaded with the core purpose ('Get token information for a provider'), making it easy to parse quickly. Every word earns its place.
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 complexity of authentication tools and the lack of annotations and output schema, the description is insufficient. It doesn't explain what token information is retrieved, the response format, or error conditions. For a tool that likely returns sensitive data, this leaves the agent under-informed.
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 description coverage is 100%, with the single parameter 'provider' documented as 'Provider name'. The description adds no additional meaning beyond this, such as examples of valid providers or format requirements. Since the schema does the heavy lifting, the 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 verb ('Get') and resource ('token information for a provider'), making the purpose understandable. However, it doesn't distinguish this tool from potential siblings like 'auth_test_connection' or 'config_get' that might also retrieve authentication-related information, preventing a perfect score.
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. It doesn't mention prerequisites (e.g., whether a token must already exist), exclusions, or relationships to siblings like 'auth_set_token' or 'auth_test_connection', leaving the agent to infer usage context.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
auth_set_tokenC
Set authentication token for a provider
| Name | Required | Description | Default |
|---|---|---|---|
| provider | Yes | Provider name (gitea, github) | |
| token | Yes | Authentication token |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden. It states this is a 'Set' operation, implying mutation, but doesn't disclose behavioral traits like whether this persists tokens across sessions, requires specific permissions, overwrites existing tokens, or has side effects (e.g., testing the token). This is inadequate for a mutation tool with zero annotation coverage.
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, efficient sentence that directly states the tool's purpose without unnecessary words. It is front-loaded and wastes no space, making it easy to parse quickly.
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 complexity of an authentication mutation tool with no annotations and no output schema, the description is incomplete. It fails to explain what happens after setting the token (e.g., success response, error handling, or how it integrates with other tools like 'auth_test_connection'), leaving significant gaps for an AI agent to understand the tool's full 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?
The schema description coverage is 100%, with clear descriptions for both parameters ('provider' and 'token'). The description adds no additional meaning beyond what the schema provides (e.g., it doesn't explain provider options like 'gitea' or 'github' in more detail), so it meets the baseline of 3 for high schema coverage.
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 action ('Set') and resource ('authentication token for a provider'), making the purpose understandable. However, it doesn't distinguish this tool from its sibling 'auth_test_connection' or other auth-related tools, which could have overlapping purposes in authentication workflows.
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 like 'auth_test_connection' or 'config_set' (which might handle similar settings). It lacks context on prerequisites (e.g., whether a provider must be configured first) or exclusions, leaving usage unclear.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
auth_test_connectionC
Test connection to a provider
| Name | Required | Description | Default |
|---|---|---|---|
| provider | Yes | Provider name |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries full burden for behavioral disclosure. 'Test connection' implies a read-only diagnostic operation, but the description doesn't specify what constitutes a successful test, what output to expect, whether authentication is required, or any rate limits. It provides minimal behavioral context beyond the basic purpose.
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 concise at just 5 words, front-loading the essential information with zero wasted words. Every word earns its place in communicating the core functionality.
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 diagnostic tool with no annotations and no output schema, the description is insufficiently complete. It doesn't explain what a successful test looks like, what format results are returned in, whether authentication is needed, or what providers are supported. The minimal description leaves too many operational questions unanswered.
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 the single 'provider' parameter well-documented in the schema. The description doesn't add any additional parameter semantics beyond what's already in the structured schema, so it meets the baseline for adequate but not exceptional 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 clearly states the action ('Test connection') and target ('to a provider'), providing a specific verb+resource combination. However, it doesn't distinguish this tool from potential alternatives like 'health_check' or 'ping' that might also test connectivity, so it doesn't fully differentiate from 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?
The description provides no guidance on when to use this tool versus alternatives. There are sibling tools like 'health_check' and 'ping' that might serve similar connectivity testing purposes, but the description doesn't indicate when this specific provider connection test is appropriate versus those general health checks.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
backup_createC
Create a backup
| Name | Required | Description | Default |
|---|---|---|---|
| includeIssues | No | Include issues | |
| includePRs | No | Include pull requests | |
| provider | Yes | Provider name | |
| repo | Yes | Repository name |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries full burden for behavioral disclosure but offers none. It doesn't indicate whether this is a read or write operation, what permissions are required, whether it's destructive, what happens during execution, or what the expected outcome is. 'Create a backup' implies a write operation but lacks all 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 extremely concise at just two words, with zero wasted text. It's front-loaded with the core action, though this brevity comes at the cost of completeness. Every word earns its place by stating the essential function.
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 tool with 4 parameters, no annotations, and no output schema, the description is completely inadequate. It doesn't explain what a 'backup' entails, what resource it operates on, what the output looks like, or any behavioral characteristics. The minimal description fails to compensate for the lack of structured metadata.
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 all four parameters (provider, repo, includeIssues, includePRs) with their types and descriptions. The description adds no additional parameter semantics beyond what's in the schema, maintaining the baseline score of 3 for adequate schema coverage.
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 'Create a backup' is a tautology that restates the tool name without specifying what resource is being backed up or distinguishing it from sibling tools like backup_list. It lacks a specific verb+resource combination and doesn't clarify what type of backup this creates (e.g., repository backup vs. configuration backup).
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. It doesn't mention sibling tools like backup_list, doesn't specify prerequisites (e.g., authentication status), and offers no context about appropriate use cases or limitations.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
backup_listC
List backups
| Name | Required | Description | Default |
|---|---|---|---|
| provider | Yes | Provider name | |
| repo | No | Repository name |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full burden of behavioral disclosure. 'List backups' implies a read-only operation, but it doesn't specify if it requires authentication, rate limits, pagination, or what the output format looks like (e.g., list of backup names or detailed metadata). This leaves significant gaps for a tool with potential complexity.
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 concise at two words, with zero wasted language. It's front-loaded and to the point, making it efficient for an agent to parse, though this brevity contributes to gaps in other dimensions.
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 and output schema, the description is incomplete. It doesn't explain what 'backups' entail, how results are returned, or any behavioral traits, making it inadequate for a tool that likely interacts with backup systems and has two parameters.
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 has 100% description coverage, with clear parameter descriptions ('Provider name', 'Repository name'). The description adds no additional meaning beyond the schema, so it meets the baseline of 3 by not contradicting but not enhancing parameter 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 'List backups' clearly states the verb ('List') and resource ('backups'), providing a basic purpose. However, it doesn't specify what kind of backups (e.g., system, database, file) or differentiate from sibling tools like 'backup_create', making it somewhat vague but still understandable.
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 doesn't mention prerequisites (e.g., needing authentication or specific configurations) or compare to related tools like 'backup_create' or 'config_list', leaving the agent with no usage context.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
config_getC
Get a configuration value
| Name | Required | Description | Default |
|---|---|---|---|
| key | Yes | Configuration key |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries full burden. It states 'Get' which implies a read operation, but doesn't disclose behavioral traits such as permissions needed, error handling (e.g., if key doesn't exist), or rate limits. It's minimal and lacks context beyond the basic action.
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 concise with a single sentence 'Get a configuration value', which is front-loaded and wastes no words. It efficiently conveys the core purpose without unnecessary details.
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 simple parameter, the description is incomplete. It doesn't explain what the tool returns (e.g., value type, structure), error conditions, or how it fits with siblings like 'config_set'. For a tool with minimal structured data, more context is needed.
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 the parameter 'key' documented as 'Configuration key'. The description adds no additional meaning beyond this, as it doesn't explain key formats, examples, or constraints. Baseline 3 is appropriate since 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 'Get a configuration value' clearly states the action (get) and resource (configuration value), but it's vague about scope and doesn't differentiate from sibling tools like 'config_list' or 'config_set'. It doesn't specify what kind of configuration or where it's stored.
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 'config_list' (which might list all configs) or 'config_set' (for setting values). The description implies retrieval but doesn't specify prerequisites, context, or exclusions.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
config_listB
List all configuration values
| Name | Required | Description | Default |
|---|---|---|---|
No parameters | |||
TDQS
Does 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. 'List all configuration values' implies a read-only operation, but it doesn't specify whether this requires authentication, what format the output takes, if there are rate limits, or if the list is paginated. For a tool with zero annotation coverage, this leaves significant behavioral gaps.
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, efficient sentence that gets straight to the point: 'List all configuration values'. There's no wasted words, repetition, or unnecessary elaboration. It's perfectly front-loaded and appropriately sized for this simple tool.
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 simplicity (0 parameters, no output schema, no annotations), the description is minimally adequate. It states what the tool does but lacks details about output format, authentication needs, or error conditions. For a basic list operation, this might suffice, but it doesn't provide complete context for reliable agent use.
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 tool has 0 parameters, and schema description coverage is 100%, so there's no need for parameter documentation in the description. The description correctly avoids discussing parameters, which is appropriate. A baseline of 4 is assigned for zero-parameter tools that don't mislead about inputs.
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 'List all configuration values' clearly states the verb ('List') and resource ('configuration values'), making the tool's purpose immediately understandable. It distinguishes itself from sibling tools like 'config_get' (which retrieves specific values) and 'config_set' (which modifies values) by focusing on comprehensive listing. However, it doesn't explicitly mention that it returns all values without filtering, which would make it a perfect 5.
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 like 'config_get' for retrieving specific values or 'config_set' for modifying values. There's no mention of prerequisites, context for usage, or explicit exclusions. The agent must infer usage from the tool name and sibling relationships alone.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
config_setC
Set a configuration value
| Name | Required | Description | Default |
|---|---|---|---|
| key | Yes | Configuration key | |
| value | Yes | Configuration value |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries full burden for behavioral disclosure. It states 'Set a configuration value,' implying a write/mutation operation, but doesn't disclose critical traits like required permissions, whether changes are persistent or reversible, error handling, or side effects. This is a significant gap for a mutation 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, efficient sentence with zero waste. It's front-loaded and appropriately sized for a simple tool, making it easy to parse quickly.
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 this is a mutation tool with no annotations and no output schema, the description is incomplete. It doesn't explain what happens after setting (e.g., success confirmation, error responses), nor does it cover behavioral aspects like security or persistence, leaving gaps for agent 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%, with both parameters ('key' and 'value') documented in the schema. The description adds no additional meaning beyond the schema, such as examples of valid keys/values or formatting rules. Baseline 3 is appropriate since the schema handles parameter documentation adequately.
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 'Set a configuration value' clearly states the action (set) and resource (configuration value), making the purpose understandable. However, it lacks specificity about what kind of configuration (e.g., system, application, user) and doesn't distinguish from sibling tools like 'config_get' or 'config_list' beyond the verb difference.
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. It doesn't mention prerequisites (e.g., authentication), exclusions, or compare it to siblings like 'config_get' for reading or 'config_list' for listing, leaving usage context unclear.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
env_checkC
Check environment variables
| Name | Required | Description | Default |
|---|---|---|---|
No parameters | |||
TDQS
Does 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. 'Check environment variables' implies a read-only operation, but it does not specify what the tool returns (e.g., a list, a status report), whether it has side effects, or any constraints like permission requirements or rate limits. This leaves significant gaps in understanding the tool's behavior beyond the basic action.
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 'Check environment variables' is a single, efficient phrase that directly states the tool's purpose without unnecessary words. It is appropriately sized for a simple tool, though it could be slightly more informative without losing conciseness. There is no structural waste, but it lacks depth that might be beneficial for clarity.
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 simplicity (0 parameters, no output schema, no annotations), the description is incomplete. It does not explain what 'checking' entails or what the output might be, leaving the agent unsure of the tool's full functionality. For a tool with no structured data to rely on, the description should provide more context to be fully helpful.
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 tool has 0 parameters, with 100% schema description coverage, meaning the schema fully documents the absence of inputs. The description does not add any parameter information, which is appropriate since there are no parameters to explain. This meets the baseline for tools with no parameters, as there is no need to compensate for schema gaps.
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 'Check environment variables' clearly states the verb ('Check') and resource ('environment variables'), providing a basic understanding of the tool's function. However, it lacks specificity about what 'checking' entails (e.g., listing all variables, verifying specific ones, validating values) and does not distinguish it from potential sibling tools like 'config_get' or 'config_list', which might overlap in functionality. This makes it vague but not misleading.
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. It does not mention any context, prerequisites, or exclusions, such as whether it's for debugging, configuration validation, or system health checks. With sibling tools like 'config_get' and 'health_check' that might serve similar purposes, the lack of differentiation leaves the agent without clear usage instructions.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
git_addC
Add files to Git staging area
| Name | Required | Description | Default |
|---|---|---|---|
| path | Yes | Repository path | |
| patterns | No | File patterns to add |
TDQS
Does 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 states the action ('Add files') but doesn't mention critical behaviors like whether this is a read-only or mutating operation (it's mutating), what happens on success/failure, or if there are side effects (e.g., staging files for commit). This leaves significant gaps for an agent to understand the tool's impact.
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, efficient sentence with zero waste—'Add files to Git staging area' is front-loaded and directly conveys the core action. Every word earns its place, making it highly concise and well-structured for quick comprehension.
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 complexity (a mutating operation with no annotations and no output schema), the description is incomplete. It doesn't explain the return values, error conditions, or behavioral nuances (e.g., how patterns work, what 'staging area' entails). For a tool that modifies state, this lack of context could lead to misuse by an agent.
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 both parameters ('path' and 'patterns') well-documented in the schema. The description adds no additional semantic context about parameters beyond implying files are involved, so it meets the baseline of 3 where the schema does the heavy lifting without compensating for gaps.
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 'Add files to Git staging area' clearly states the verb ('Add') and resource ('files to Git staging area'), making the purpose immediately understandable. However, it doesn't differentiate from sibling tools like git_commit or git_status, which also interact with the staging area in different ways.
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 like git_commit (which commits staged files) or git_status (which shows staging status). It lacks context about prerequisites (e.g., needing a git repository initialized) or exclusions, leaving the agent to infer usage from the tool name alone.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
git_branch_createC
Create a new branch
| Name | Required | Description | Default |
|---|---|---|---|
| name | Yes | Branch name | |
| path | Yes | Repository path |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries full burden but only states the basic action without behavioral details. It doesn't disclose whether this requires write permissions, if it's destructive to existing branches, potential errors (e.g., duplicate branch names), or what happens on success (e.g., branch creation confirmation). This is inadequate for a mutation tool with zero annotation coverage.
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 concise with just three words, front-loading the core purpose without any wasted text. Every word earns its place, making it efficient for quick comprehension.
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 this is a mutation tool with no annotations and no output schema, the description is incomplete. It lacks crucial context like what the tool returns, error conditions, or behavioral implications, which are essential for an agent to use it effectively in a Git workflow.
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 has 100% description coverage, with clear documentation for both parameters (name and path). The description adds no additional semantic context beyond what the schema provides, such as format examples or constraints, so it meets the baseline for high schema coverage without compensating value.
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 'Create a new branch' clearly states the action (create) and resource (branch), making the purpose immediately understandable. However, it doesn't differentiate from sibling tools like git_branch_list or git_branch_switch, which would require mentioning it's specifically for creation rather than listing or switching branches.
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. It doesn't mention prerequisites (e.g., needing an initialized repository), exclusions, or related tools like git_branch_switch for moving between branches, leaving the agent to infer usage from context alone.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
git_branch_listC
List all branches
| Name | Required | Description | Default |
|---|---|---|---|
| path | Yes | Repository path |
TDQS
Does 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. 'List all branches' implies a read-only operation, but it doesn't specify output format (e.g., list of branch names, details), pagination, error conditions, or dependencies like requiring git to be installed. For a tool with no annotation coverage, this leaves significant gaps in understanding its 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 'List all branches' is extremely concise—three words that directly convey the core action. It's front-loaded with the verb and resource, with zero wasted words. This efficiency makes it easy for an agent to parse and understand quickly, earning a top score for 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 tool's complexity (a Git operation with one parameter) and the lack of annotations and output schema, the description is incomplete. It doesn't explain what 'all branches' entails (e.g., local, remote, or both), the return format, or error handling. For a tool interacting with version control, more context is needed to ensure correct usage by an agent.
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 has 100% description coverage, with the 'path' parameter documented as 'Repository path'. The description adds no additional parameter semantics beyond what the schema provides, such as clarifying path format (e.g., absolute vs. relative) or examples. Given the high schema coverage, a baseline score of 3 is appropriate, as the description doesn't compensate but doesn't need to heavily.
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 'List all branches' clearly states the verb ('List') and resource ('branches'), making the tool's purpose immediately understandable. It distinguishes from siblings like git_branch_create or git_branch_switch by focusing on listing rather than creation or switching. However, it doesn't specify the scope (e.g., local vs. remote branches), which prevents a perfect score.
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. It doesn't mention prerequisites (e.g., needing an initialized repository), contrast with similar tools like git_status for repository state, or specify use cases. Without any contextual hints, the agent must infer usage solely from the tool name and schema.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
git_branch_switchC
Switch to a branch
| Name | Required | Description | Default |
|---|---|---|---|
| name | Yes | Branch name | |
| path | Yes | Repository path |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries full burden for behavioral disclosure. 'Switch to a branch' implies a mutation (changing the active branch), but it doesn't disclose potential side effects (e.g., requiring a clean working directory), authentication needs, error conditions, or what happens if the branch doesn't exist. This leaves significant gaps for a mutation 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 extremely concise with just three words, front-loading the core action without any wasted text. Every word earns its place by directly conveying 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?
For a mutation tool with no annotations and no output schema, the description is incomplete. It doesn't explain what the tool returns (e.g., success confirmation or error), behavioral constraints, or integration with sibling tools. Given the complexity of Git operations, more context is needed for safe and effective use.
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 both parameters clearly documented in the schema. The description doesn't add any meaningful context beyond what the schema provides (e.g., explaining that 'path' is the local repository directory or 'name' must be an existing branch). Baseline 3 is appropriate when 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 clearly states the verb ('switch to') and resource ('a branch'), making the purpose immediately understandable. However, it doesn't differentiate from sibling tools like git_branch_create or git_branch_list, which would require mentioning this specifically changes the active/current branch rather than creating or listing branches.
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. It doesn't mention prerequisites (e.g., needing an existing branch or repository), when not to use it (e.g., during conflicts), or refer to related tools like git_branch_create for creating branches before switching.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
git_cloneC
Clone a repository
| Name | Required | Description | Default |
|---|---|---|---|
| dest | Yes | Destination path | |
| url | Yes | Repository URL |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries full burden for behavioral disclosure. 'Clone a repository' implies a read/write operation that creates local files, but it doesn't specify permissions needed, whether it overwrites existing directories, error handling, or output format. This leaves significant gaps for a tool that modifies the filesystem.
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 concise with just three words, front-loading the core action and resource. There's zero wasted text, making it easy to parse quickly while still conveying the essential 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 complexity of cloning (filesystem changes, network operations) and lack of annotations or output schema, the description is incomplete. It doesn't cover behavioral aspects like what happens on failure, whether 'dest' must not exist, or what the tool returns, leaving the agent with insufficient context for safe invocation.
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 both parameters (url, dest) clearly documented in the schema. The description adds no additional parameter semantics beyond what's in the schema, so it meets the baseline of 3 for adequate coverage without extra value.
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 'Clone a repository' clearly states the action (clone) and resource (repository), making the purpose immediately understandable. However, it doesn't differentiate from sibling tools like 'git_init' (which creates a new repository) or 'git_pull' (which updates an existing clone), missing explicit sibling 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?
The description provides no guidance on when to use this tool versus alternatives. It doesn't mention prerequisites (e.g., needing a repository URL), when not to use it (e.g., for existing repositories), or direct alternatives among siblings like 'git_init' for new repositories or 'git_pull' for updates.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
git_commitC
Commit staged changes
| Name | Required | Description | Default |
|---|---|---|---|
| message | Yes | Commit message | |
| path | Yes | Repository path |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries full burden for behavioral disclosure. 'Commit staged changes' implies a write operation that modifies repository history, but it lacks details on permissions needed, whether it's reversible (e.g., via git reset), error conditions (e.g., no staged changes), or output format. For a mutation tool with zero annotation coverage, this is a significant gap.
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, efficient phrase ('Commit staged changes') with zero wasted words. It's front-loaded and directly conveys the core action without unnecessary elaboration, 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.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given this is a mutation tool with no annotations, no output schema, and 2 required parameters, the description is incomplete. It doesn't cover behavioral aspects like safety, reversibility, or error handling, nor does it explain the commit's effect or return values. For a Git operation that alters repository state, more context is needed.
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 both parameters ('message' and 'path') clearly documented in the schema. The description doesn't add any meaning beyond what the schema provides (e.g., it doesn't explain message conventions or path requirements). Baseline 3 is appropriate when 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 'Commit staged changes' clearly states the verb ('commit') and resource ('staged changes'), making the purpose immediately understandable. It doesn't explicitly distinguish from siblings like git_add (which stages changes) or git_push (which pushes commits), but the core action is unambiguous.
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. It doesn't mention prerequisites (e.g., requiring staged changes via git_add), exclusions (e.g., not for uncommitted changes), or relationships with sibling tools like git_push for remote sharing. Usage is implied but not articulated.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
gitea_create_repoC
Create a new repository on Gitea
| Name | Required | Description | Default |
|---|---|---|---|
| description | No | Repository description | |
| name | Yes | Repository name | |
| private | No | Private repository |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full burden of behavioral disclosure. It indicates a write operation ('Create') but lacks details on permissions needed, error conditions, rate limits, or what happens on success (e.g., returns a repo object). This leaves significant gaps for an agent to understand the tool's 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, direct sentence that efficiently conveys the core purpose without any wasted words. It is appropriately sized and front-loaded, making it easy to parse quickly.
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 creation tool with no annotations and no output schema, the description is incomplete. It doesn't explain what the tool returns, potential side effects, or error handling, which are critical for an agent to use it effectively. The high schema coverage helps with inputs but doesn't compensate for the lack of output and behavioral 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?
The input schema has 100% description coverage, clearly documenting all three parameters (name, description, private). The description adds no additional parameter semantics beyond what the schema provides, such as format constraints or examples, so it meets the baseline for high schema coverage without adding value.
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 action ('Create') and resource ('new repository on Gitea'), making the purpose immediately understandable. However, it doesn't differentiate from the sibling tool 'github_create_repo', which performs a similar function on a different platform, so it doesn't achieve full sibling 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?
The description provides no guidance on when to use this tool versus alternatives like 'github_create_repo' or 'git_init', nor does it mention prerequisites such as authentication or context requirements. It simply states what the tool does without usage context.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
gitea_get_repoC
Get repository information from Gitea
| Name | Required | Description | Default |
|---|---|---|---|
| owner | Yes | Repository owner | |
| repo | Yes | Repository name |
TDQS
Does 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 states the action ('Get repository information') without detailing aspects like whether this is a read-only operation, potential rate limits, error conditions, or the format of the returned information. This leaves significant gaps in understanding the tool's 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, efficient sentence that directly states the tool's purpose without unnecessary words. It is front-loaded and wastes no space, making it highly concise and well-structured for quick understanding.
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 complexity (a read operation with 2 parameters) and the lack of annotations and output schema, the description is incomplete. It doesn't explain what information is returned, how errors are handled, or any behavioral traits, leaving the agent with insufficient context to use the tool effectively beyond basic parameter input.
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 has 100% description coverage, clearly documenting both parameters ('owner' and 'repo') as required strings. The description adds no additional semantic context beyond what the schema provides, such as examples or constraints, so it meets the baseline for high schema coverage without compensating value.
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 the tool's purpose as 'Get repository information from Gitea', which includes a clear verb ('Get') and resource ('repository information from Gitea'). However, it doesn't distinguish this tool from its sibling 'gitea_list_repos' or specify what type of information is retrieved (e.g., metadata, settings, or full details), making it somewhat vague.
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 like 'gitea_list_repos' or 'github_list_repos'. There's no mention of prerequisites, such as needing authentication or specific permissions, or when this tool is preferred over others for retrieving repository data.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
gitea_list_reposB
List repositories on Gitea
| Name | Required | Description | Default |
|---|---|---|---|
| user | No | Username to list repos for |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full burden of behavioral disclosure. It states the action is to 'list' repositories, which implies a read-only operation, but does not specify whether it requires authentication, how results are returned (e.g., pagination, format), or any rate limits. This is a significant gap for a tool with zero annotation coverage.
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, efficient sentence with zero waste—'List repositories on Gitea'—making it front-loaded and appropriately sized for its purpose. Every word earns its place, achieving optimal 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 tool's low complexity (one optional parameter) and high schema coverage, the description is minimally adequate. However, with no annotations and no output schema, it lacks details on authentication needs, result format, or behavioral traits, which are important for a read operation in a multi-tool environment. It meets the minimum viable threshold but has clear gaps.
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 has 100% description coverage, with the 'user' parameter documented as 'Username to list repos for'. The description does not add any meaning beyond this, such as explaining default behavior if 'user' is omitted or detailing output structure. Baseline 3 is appropriate when 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 'List repositories on Gitea' clearly states the action (list) and resource (repositories on Gitea), providing a specific verb+resource combination. However, it does not differentiate from sibling tools like 'github_list_repos' or 'gitea_get_repo', which would require mentioning scope or filtering details to earn a 5.
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. It does not mention when to choose 'gitea_list_repos' over 'github_list_repos' or 'gitea_get_repo', nor does it specify any prerequisites or exclusions, leaving usage context implied at best.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
github_create_repoC
Create a new repository on GitHub
| Name | Required | Description | Default |
|---|---|---|---|
| description | No | Repository description | |
| name | Yes | Repository name | |
| private | No | Private repository |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries full burden for behavioral disclosure. It states it creates a repository but doesn't mention authentication requirements, rate limits, error conditions, or what happens on success (e.g., returns repository details). This leaves significant gaps for a mutation 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, clear sentence with zero wasted words. It's front-loaded with the essential information (create repository) and doesn't include unnecessary details, making it highly 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?
For a mutation tool with no annotations and no output schema, the description is inadequate. It doesn't explain authentication needs, error handling, or what the tool returns, leaving the agent with insufficient information to use it effectively in 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 description coverage is 100%, so the schema already documents all three parameters (name, description, private) with their types and descriptions. The description adds no additional parameter information beyond what's in the schema, meeting the baseline for high schema coverage.
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 action ('Create') and resource ('new repository on GitHub'), making the purpose immediately understandable. However, it doesn't differentiate from the sibling tool 'gitea_create_repo' which performs a similar function for a different platform, so it doesn't reach the highest score.
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 like 'gitea_create_repo' or 'git_init', nor does it mention prerequisites such as authentication. It simply states what the tool does without contextual usage information.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
github_list_reposC
List repositories on GitHub
| Name | Required | Description | Default |
|---|---|---|---|
| user | No | Username to list repos for |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries full burden. 'List repositories on GitHub' implies a read-only operation but doesn't disclose authentication requirements, rate limits, pagination behavior, or what happens if the 'user' parameter is omitted. For a tool with zero annotation coverage, this is inadequate behavioral disclosure.
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, efficient sentence with zero wasted words. It's appropriately sized for a simple list operation and front-loads the core purpose immediately.
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 simple input schema, the description is incomplete. It doesn't explain authentication needs, return format, error conditions, or how it differs from sibling tools. For a GitHub API tool that likely requires authentication, this leaves significant gaps for an AI agent.
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 the single parameter 'user' documented as 'Username to list repos for'. The description adds no additional parameter semantics beyond what the schema provides. With high schema coverage, the baseline score of 3 is appropriate as 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 'List repositories on GitHub' clearly states the action (list) and resource (repositories on GitHub). It distinguishes from siblings like 'github_create_repo' (create vs list) and 'gitea_list_repos' (GitHub vs Gitea platform). However, it doesn't specify scope (e.g., all repos vs user-specific), which prevents a perfect score.
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. It doesn't mention whether it lists all GitHub repos, user-specific repos, or how it differs from 'gitea_list_repos' for similar functionality on a different platform. No explicit when/when-not or alternative tool references are provided.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
git_initC
Initialize a new Git repository
| Name | Required | Description | Default |
|---|---|---|---|
| path | Yes | Path to initialize repository |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries full burden for behavioral disclosure. It states the action but doesn't mention what happens when run (creates .git directory, sets up initial structure), potential side effects (overwrites existing .git?), error conditions, or output format. This leaves significant behavioral gaps for a mutation 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, efficient sentence that states the core purpose without unnecessary words. It's appropriately sized for a simple tool and front-loads the essential 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?
For a mutation tool with no annotations and no output schema, the description is insufficient. It doesn't explain what the tool actually does beyond the high-level action, what gets created, what the expected outcome is, or any behavioral characteristics. The agent would need to guess about implementation details.
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 the single parameter 'path' clearly documented in the schema. The description adds no additional parameter information beyond what the schema provides, so it meets the baseline for adequate but unenriched 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 clearly states the verb ('Initialize') and resource ('a new Git repository'), making the purpose immediately understandable. However, it doesn't differentiate from sibling tools like git_clone (which also creates repositories) or explain what distinguishes initialization from cloning.
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 like git_clone or gitea_create_repo. There's no mention of prerequisites (e.g., needing an empty directory) or typical use cases, leaving the agent to infer appropriate contexts.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
git_mergeC
Merge a branch into current branch
| Name | Required | Description | Default |
|---|---|---|---|
| path | Yes | Repository path | |
| source_branch | Yes | Source branch to merge |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full burden of behavioral disclosure. While 'merge' implies a write operation, the description doesn't disclose critical behavioral traits: whether this creates a merge commit, what happens with conflicts, whether it requires a clean working directory, or what the expected output looks like. For a mutation tool with zero annotation coverage, this is inadequate.
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 concise - a single sentence that directly states the tool's purpose. There's zero wasted language, and the information is front-loaded. This is an example of efficient communication.
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 git merge operation with no annotations and no output schema, the description is incomplete. It doesn't explain the behavioral implications of merging, potential side effects, error conditions, or what constitutes success. Given the complexity of git operations and the lack of structured safety information, this description leaves too many questions unanswered.
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 both parameters are documented in the schema. The description doesn't add any parameter semantics beyond what the schema already provides (repository path and source branch). It doesn't explain what 'current branch' means or how it's determined. Baseline 3 is appropriate when 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 clearly states the action ('merge') and target ('a branch into current branch'), providing a specific verb+resource combination. However, it doesn't distinguish this tool from potential alternatives like 'git_rebase' or explain how it differs from sibling tools like 'git_pull' that also involve merging.
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. It doesn't mention prerequisites (like being in a git repository), when merging is appropriate versus rebasing, or what happens if there are conflicts. With multiple git-related sibling tools available, this lack of differentiation is a significant gap.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
git_pullC
Pull changes from remote repository
| Name | Required | Description | Default |
|---|---|---|---|
| branch | No | Branch name | main |
| path | Yes | Repository path | |
| remote | No | Remote name | origin |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries full burden for behavioral disclosure. It states the action but doesn't describe what happens (e.g., merges changes into current branch, may create merge commits, requires network connectivity, could fail on conflicts). For a mutation tool with zero annotation coverage, this is a significant gap in explaining operational 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, efficient sentence with zero wasted words. It's front-loaded with the core action and resource, making it immediately scannable and understandable without unnecessary elaboration.
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 mutation tool with no annotations and no output schema, the description is incomplete. It doesn't explain what the tool returns (e.g., success status, merge results, error messages) or important behavioral aspects like side effects. Given the complexity of git operations and lack of structured data, more context is needed for effective agent use.
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 all three parameters (branch, path, remote) with their types and defaults. The description adds no additional parameter semantics beyond what's in the schema, such as explaining relationships between parameters or special constraints. This meets the baseline for high schema coverage.
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 ('pull') and resource ('changes from remote repository'), making the purpose immediately understandable. It distinguishes from siblings like git_push (which pushes changes) and git_clone (which creates a new repository). However, it doesn't specify what type of changes (commits, tags, etc.) or mention the local repository aspect, keeping it from a perfect score.
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. It doesn't mention prerequisites (e.g., needing an initialized repository), when not to use it (e.g., during merge conflicts), or compare to siblings like git_fetch (which retrieves changes without merging). This leaves the agent with minimal context for tool selection.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
git_pushC
Push commits to remote repository
| Name | Required | Description | Default |
|---|---|---|---|
| branch | No | Branch name | main |
| path | Yes | Repository path | |
| remote | No | Remote name | origin |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full burden of behavioral disclosure. It states the action ('push') but doesn't reveal critical traits: whether it requires authentication, what happens on conflicts (e.g., merge requirements), if it's destructive (overwrites remote history), rate limits, or error conditions. This is a significant gap for a mutation tool with zero annotation coverage.
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, efficient sentence with zero wasted words. It's front-loaded with the core action and resource, making it easy to parse quickly. Every word earns its place by conveying essential purpose without redundancy.
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 complexity of a git push operation (a mutation with potential side effects), no annotations, and no output schema, the description is incomplete. It lacks details on authentication needs, conflict handling, success/error responses, and how it interacts with siblings like git_commit or git_pull. For a tool with such behavioral nuances, this is inadequate.
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 has 100% description coverage, clearly documenting all three parameters (branch, path, remote) with defaults and types. The description adds no additional semantic context beyond implying these parameters might be involved in the push operation. This meets the baseline for high schema coverage but doesn't enhance understanding further.
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 action ('push') and resource ('commits to remote repository'), which distinguishes it from siblings like git_pull, git_commit, or git_add. However, it doesn't specify what type of commits (e.g., local, staged) or differentiate from potential alternatives like force-push operations, keeping it from a perfect score.
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. It doesn't mention prerequisites (e.g., needing commits ready to push, authentication status), exclusions (e.g., not for initial pushes or force pushes), or sibling tools like git_pull for fetching changes first. This leaves the agent to infer usage from context alone.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
git_statusC
Get repository status
| Name | Required | Description | Default |
|---|---|---|---|
| path | Yes | Repository path |
TDQS
Does 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. 'Get repository status' implies a read-only operation, but it doesn't specify whether it requires authentication, what the output format is (e.g., text summary, structured data), or if there are rate limits. The description lacks details on behavioral traits beyond the basic action.
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 concise with a single sentence 'Get repository status', which is front-loaded and wastes no words. It efficiently conveys the core purpose without unnecessary elaboration, making it easy to scan and understand quickly.
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 complexity (a Git operation with no annotations and no output schema), the description is incomplete. It doesn't explain what 'status' includes, the return format, or error conditions. For a tool that likely outputs detailed repository state information, more context is needed to guide effective use by an AI agent.
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 has 100% description coverage, with the 'path' parameter documented as 'Repository path'. The description doesn't add any meaning beyond this, such as clarifying path formats (e.g., absolute vs. relative) or examples. With high schema coverage, the baseline score of 3 is appropriate as the schema handles the parameter documentation adequately.
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 'Get repository status' clearly states the verb ('Get') and resource ('repository status'), making the purpose understandable. However, it's somewhat vague about what 'status' specifically entails (e.g., staged changes, untracked files, branch info) and doesn't differentiate from sibling tools like 'git_branch_list' or 'git_add', which might overlap in providing status-related information.
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. It doesn't mention prerequisites (e.g., needing an initialized repository), exclusions, or comparisons to siblings like 'git_branch_list' for branch-specific status. Usage is implied from the name but not explicitly stated.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
health_checkD
Perform health check
| Name | Required | Description | Default |
|---|---|---|---|
No parameters | |||
TDQS
Does 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. 'Perform health check' reveals nothing about what the tool actually does - whether it's a simple status check, a comprehensive system diagnostic, whether it has side effects, what permissions it requires, or what format the results take. This is completely inadequate for a tool with zero annotation coverage.
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?
While technically concise with just two words, this represents under-specification rather than effective conciseness. The description fails to provide the minimal necessary information about what the tool does. Every word should earn its place, but here the words don't provide enough value - they merely restate the tool name without adding useful context or differentiation.
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 complete lack of annotations and no output schema, the description is woefully incomplete. 'Perform health check' doesn't explain what constitutes a health check in this context, what systems are checked, what the expected output format is, or how to interpret results. For a diagnostic tool that presumably returns status information, this minimal description leaves critical gaps in 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 tool has 0 parameters with 100% schema description coverage, so the schema fully documents the parameter situation. The description doesn't need to compensate for any parameter gaps. While the description doesn't add any parameter information beyond what the schema provides, this is acceptable given the zero-parameter baseline. A score of 4 reflects that the description doesn't detract from the complete schema coverage.
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 'Perform health check' is a tautology that restates the tool name without adding meaningful context. It doesn't specify what kind of health check, what system or service is being checked, or what constitutes 'health' in this context. While it uses a verb ('perform'), it lacks the specificity needed to distinguish this from other diagnostic tools like 'ping' or 'env_check' in the sibling list.
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. It doesn't mention any prerequisites, appropriate contexts, or exclusions. With sibling tools like 'ping', 'env_check', and 'auth_test_connection' that might serve similar diagnostic purposes, the absence of usage guidance leaves the agent guessing about when this specific health check is appropriate.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
pingC
Test connectivity
| Name | Required | Description | Default |
|---|---|---|---|
No parameters | |||
TDQS
Does 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. 'Test connectivity' implies a read-only diagnostic operation, but it doesn't specify what happens during the test (e.g., whether it pings a network, checks API endpoints, or validates configurations), what the expected output looks like, or any side effects. This leaves significant gaps in understanding the tool's 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 extremely concise with just two words, 'Test connectivity', which is front-loaded and wastes no space. For a simple diagnostic tool with no parameters, this brevity is appropriate and 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?
Given the tool's simplicity (no parameters, no annotations, no output schema), the description is incomplete. It doesn't explain what 'connectivity' means in this context, what the test entails, or what result to expect. For a diagnostic tool, more context on behavior and output would be helpful, even without structured fields to compensate.
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 tool has zero parameters, and the schema description coverage is 100% (though trivial since there are no parameters). The description doesn't need to explain parameters, and it appropriately doesn't mention any. This meets the baseline expectation for a parameterless tool.
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 'Test connectivity' states what the tool does at a basic level, but it's vague about what exactly is being tested. It doesn't specify what resource or service connectivity is being tested, nor does it differentiate from sibling tools like 'health_check' or 'auth_test_connection' which might serve similar diagnostic 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. There's no mention of prerequisites, appropriate contexts, or comparisons to sibling tools like 'health_check' or 'env_check' that might also test system status. The agent must 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.
release_createC
Create a new release
| Name | Required | Description | Default |
|---|---|---|---|
| body | No | Release description | |
| name | Yes | Release name | |
| prerelease | No | Is prerelease | |
| provider | Yes | Provider name | |
| repo | Yes | Repository name | |
| tag | Yes | Release tag |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full burden of behavioral disclosure. 'Create a new release' implies a write operation but doesn't specify permissions required, whether it's idempotent, error handling, or what happens on success (e.g., returns a release ID). It misses critical details like rate limits, side effects, or response format, leaving significant gaps for a mutation 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, efficient sentence with zero waste—'Create a new release' is front-loaded and directly states the purpose without unnecessary elaboration. It earns its place by being maximally concise while conveying the core action.
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 complexity of a creation tool with 6 parameters, no annotations, and no output schema, the description is incomplete. It doesn't cover behavioral aspects, usage context, or return values, making it inadequate for an AI agent to reliably invoke the tool. More detail is needed to compensate for the lack of structured data.
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 fully documents all 6 parameters (e.g., 'body' as release description, 'prerelease' as boolean). The description adds no additional meaning beyond the schema, such as explaining parameter interactions or constraints. Baseline 3 is appropriate when the schema handles parameter documentation effectively.
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 'Create a new release' states the action and resource clearly but is vague about what a 'release' entails in this context. It distinguishes from siblings like 'release_list' by specifying creation vs. listing, but doesn't clarify the domain (e.g., software releases, database releases) or differentiate from other creation tools like 'backup_create' or 'gitea_create_repo'.
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 doesn't mention prerequisites (e.g., needing a repository setup), exclusions, or relationships with sibling tools like 'release_list' for viewing releases or 'version_bump' for version management. The description lacks context for appropriate usage scenarios.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
release_listD
List releases
| Name | Required | Description | Default |
|---|---|---|---|
| provider | Yes | Provider name | |
| repo | Yes | Repository name |
TDQS
Does 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. 'List releases' gives no information about permissions required, rate limits, pagination, error handling, or what the output looks like (e.g., format, fields). For a tool with no annotation coverage, this is a significant gap in transparency.
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?
While concise with only two words, the description is under-specified rather than efficiently structured. It lacks front-loaded critical information (e.g., what system or context) and doesn't earn its place by adding value beyond the tool name. Conciseness should not come at the cost of clarity.
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 complexity (a list operation with 2 required parameters), no annotations, and no output schema, the description is incomplete. It doesn't explain what 'releases' are, how results are returned, or any behavioral aspects. For a tool in a server with many sibling tools, more context is needed to guide proper use.
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 description adds no meaning beyond what the input schema provides. However, schema description coverage is 100%, with clear descriptions for both required parameters ('provider' and 'repo'), so the baseline score of 3 is appropriate. The description doesn't compensate but doesn't need to since the schema is fully documented.
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 'List releases' is a tautology that merely restates the tool name 'release_list' without adding any meaningful clarification. It doesn't specify what kind of releases (software releases, deployment releases, etc.) or from what system, nor does it distinguish this tool from sibling tools like 'release_create' or other list tools in the server.
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. It doesn't mention prerequisites (e.g., authentication), context for use (e.g., after cloning a repo), or differentiate it from similar tools like 'gitea_list_repos' or 'github_list_repos' that might handle releases differently. There's no explicit or implied usage advice.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
versionB
Get MCP version information
| Name | Required | Description | Default |
|---|---|---|---|
No parameters | |||
TDQS
Does 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. 'Get' implies a read-only operation, but it doesn't specify whether this requires authentication, has rate limits, returns structured data, or involves any side effects. For a tool with zero annotation coverage, this leaves critical behavioral traits undocumented.
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, efficient sentence: 'Get MCP version information.' It is front-loaded with the core action and resource, with zero wasted words. Every part of the sentence earns its place by directly conveying 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 tool's simplicity (0 parameters, no output schema, no annotations), the description is minimally adequate. It states what the tool does but lacks details on return format, error conditions, or integration context. For a basic informational tool, this is acceptable but leaves room for improvement in guiding effective use.
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 tool has 0 parameters, and the input schema has 100% description coverage (though empty). The description doesn't need to explain parameters, so it meets the baseline expectation. No additional parameter information is required or provided, which is appropriate for a parameterless tool.
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 'Get MCP version information' clearly states the verb ('Get') and resource ('MCP version information'), making the purpose immediately understandable. It distinguishes itself from siblings like 'version_bump' or 'version_validate' by focusing on retrieval rather than modification or validation. However, it doesn't explicitly contrast with these siblings, which prevents a perfect score.
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. It doesn't mention use cases like system diagnostics, compatibility checks, or prerequisites. With siblings like 'health_check' and 'ping' that might serve overlapping diagnostic purposes, the lack of explicit when-to-use or when-not-to-use context is a significant gap.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
version_bumpC
Bump version number
| Name | Required | Description | Default |
|---|---|---|---|
| current | Yes | Current version | |
| level | No | Bump level (major, minor, patch) | patch |
TDQS
Does 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. 'Bump version number' implies a mutation operation (incrementing a version), but it doesn't disclose any behavioral traits such as whether it modifies files in-place, requires specific permissions, has side effects (e.g., creating tags in version control), or handles errors. The description is too vague to inform the agent about how the tool behaves beyond the basic action implied by the name.
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 concise with just three words, making it front-loaded and free of unnecessary information. Every word ('Bump version number') directly relates to the tool's purpose, with zero waste or redundant phrasing. This minimalism is efficient, though it may contribute to gaps in other dimensions like clarity and guidelines.
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 complexity of a version-bumping tool (which typically involves mutation and versioning logic), the description is incomplete. No annotations are provided to clarify safety or behavior, and there's no output schema to explain return values (e.g., the new version string). The description lacks context on what the tool actually does beyond the basic action, failing to compensate for the missing structured data. This leaves significant gaps for an agent to understand and use the tool effectively.
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 has 100% description coverage, with clear documentation for both parameters ('current' as the current version and 'level' as the bump level with a default). The description adds no parameter semantics beyond what the schema provides—it doesn't explain format expectations (e.g., semantic versioning), constraints, or examples. Given the high schema coverage, the baseline score of 3 is appropriate, as the schema adequately covers parameter details without needing extra 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 'Bump version number' is a tautology that essentially restates the tool name 'version_bump'. It specifies the verb 'bump' and resource 'version number', but lacks any detail about what version is being bumped (e.g., software package, project, file) or how it operates. While it distinguishes from some siblings like 'version' or 'version_validate', it doesn't clearly differentiate from potential version-related tools not present in the sibling list.
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. It doesn't mention prerequisites, context (e.g., after code changes, for releases), or compare to siblings like 'version' (which might retrieve version info) or 'version_validate' (which might check version validity). There's no explicit or implied usage scenario, leaving the agent to guess based on the name alone.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
version_validateC
Validate semantic version
| Name | Required | Description | Default |
|---|---|---|---|
| version | Yes | Version to validate |
TDQS
Does 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. The description only states what the tool does ('Validate semantic version') without explaining what validation entails—e.g., whether it checks format compliance, returns success/failure, provides error details, or has side effects. For a tool with no annotation coverage, this leaves significant gaps in understanding its 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 extremely concise—just two words—and front-loaded with the core purpose. Every word earns its place, with no wasted text. It's appropriately sized for a simple validation tool, though this conciseness comes at the cost of completeness in other dimensions.
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 simplicity (1 parameter, no output schema, no annotations), the description is incomplete. It doesn't explain what validation means in practice, what the output might be (e.g., boolean result, error message), or how it differs from sibling tools. While the schema covers the parameter, the overall context for using the tool effectively is lacking.
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 has 100% description coverage, with the 'version' parameter documented as 'Version to validate'. The description doesn't add any meaning beyond this—it doesn't clarify what constitutes a valid semantic version, provide examples, or explain validation rules. With high schema coverage, the baseline score of 3 is appropriate, as 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 clearly states the tool's purpose as 'Validate semantic version', which is a specific verb ('validate') applied to a specific resource ('semantic version'). It distinguishes itself from sibling tools like 'version' and 'version_bump' by focusing on validation rather than retrieval or modification. However, it doesn't explicitly contrast with these siblings in the description text itself.
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. There are sibling tools like 'version' (likely retrieves version) and 'version_bump' (likely modifies version), but the description doesn't mention these or provide context about when validation is needed versus other version operations. Usage is implied only by the tool 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.
32 tool updates
v1.0.0- First observed
auth_get_token_info - First observed
auth_set_token - First observed
auth_test_connection - First observed
backup_create - First observed
backup_list - First observed
config_get - First observed
config_list - First observed
config_set - First observed
env_check - First observed
git_add - First observed
git_branch_create - First observed
git_branch_list - First observed
git_branch_switch - First observed
git_clone - First observed
git_commit - First observed
git_init - First observed
git_merge - First observed
git_pull - First observed
git_push - First observed
git_status - First observed
gitea_create_repo - First observed
gitea_get_repo - First observed
gitea_list_repos - First observed
github_create_repo - First observed
github_list_repos - First observed
health_check - First observed
ping - First observed
release_create - First observed
release_list - First observed
version - First observed
version_bump - First observed
version_validate
TDQS
Most tools have distinct purposes with clear resource-action pairs, such as git_add vs git_commit or config_get vs config_set. However, there is some overlap between health_check, ping, and auth_test_connection, which all test connectivity or status, potentially causing confusion. Additionally, version, version_bump, and version_validate are closely related but serve different functions, which might require careful selection.
Tool names follow a highly consistent verb_noun pattern throughout, with clear prefixes like git_, gitea_, github_, auth_, config_, backup_, release_, and version_ for grouping. All names use snake_case uniformly, making them predictable and easy to parse. This consistency aids in understanding the tool set's structure and purpose.
With 32 tools, the count feels excessive for a Git-focused MCP server, as it includes many utility functions like ping, health_check, and env_check that could be consolidated. The scope is broad, covering Git operations, provider integrations (Gitea/GitHub), and system utilities, leading to a bloated set that may overwhelm agents. A more focused set of 15-20 tools would be more appropriate.
The tool set provides comprehensive coverage for Git operations (e.g., clone, commit, push, merge) and repository management across providers like Gitea and GitHub, with CRUD-like actions for config, backup, and release. Minor gaps include missing update or delete operations for repositories and backups, but agents can likely work around these. The inclusion of utility tools like version and health checks adds to the completeness for the server's broad purpose.
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