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fovi-llc

Radicle + GitHub MCP Server

by fovi-llc

rad_issue_list

List issues in a Radicle repository to track bugs, tasks, and discussions within peer-to-peer code collaboration projects.

Instructions

List issues in a Radicle repository.

Args:
    repository_path: Path to the repository (default: current directory)

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
repository_pathNo.

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes

Implementation Reference

  • The main handler function for the 'rad_issue_list' tool. It is decorated with @mcp.tool() which also serves as the registration. Executes 'rad issue list' command using the run_rad_command helper and formats the output with success/error messages.
    @mcp.tool()
    async def rad_issue_list(repository_path: str = ".") -> str:
        """
        List issues in a Radicle repository.
        
        Args:
            repository_path: Path to the repository (default: current directory)
        """
        result = await run_rad_command(["rad", "issue", "list"], cwd=repository_path)
        
        if result["success"]:
            if result["stdout"]:
                return f"🐛 Issues in repository:\n{result['stdout']}"
            else:
                return "🐛 No issues found in repository"
        else:
            return f"❌ Failed to list issues: {result['stderr']}"
  • Supporting helper function that runs 'rad' CLI commands asynchronously and returns structured results (stdout, stderr, return_code, success). Used by rad_issue_list and other tools.
    async def run_rad_command(command: List[str], cwd: Optional[str] = None) -> Dict[str, Any]:
        """
        Run a rad command and return the result.
        
        Args:
            command: List of command arguments starting with 'rad'
            cwd: Working directory to run the command in
            
        Returns:
            Dictionary with stdout, stderr, and return_code
        """
        try:
            # Ensure command starts with 'rad'
            if not command or command[0] != "rad":
                command = ["rad"] + command
                
            logger.info(f"Running command: {' '.join(command)}")
            
            process = await asyncio.create_subprocess_exec(
                *command,
                stdout=asyncio.subprocess.PIPE,
                stderr=asyncio.subprocess.PIPE,
                cwd=cwd
            )
            
            stdout, stderr = await process.communicate()
            
            return {
                "stdout": stdout.decode("utf-8").strip(),
                "stderr": stderr.decode("utf-8").strip(),
                "return_code": process.returncode,
                "success": process.returncode == 0
            }
            
        except FileNotFoundError:
            return {
                "stdout": "",
                "stderr": "rad command not found. Please ensure Radicle is installed.",
                "return_code": 127,
                "success": False
            }
        except Exception as e:
            return {
                "stdout": "",
                "stderr": f"Error running command: {str(e)}",
                "return_code": 1,
                "success": False
            }
Behavior2/5

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 tool lists issues but doesn't describe any behavioral traits such as output format, pagination, error handling, or performance characteristics. This is a significant gap for a tool with no 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.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is appropriately sized and front-loaded, with the core purpose stated first. The two-sentence structure is efficient, though the second sentence could be more integrated. There's no wasted text, but it lacks depth, which affects completeness more than conciseness.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness3/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the tool's low complexity (1 parameter, no required params) and the presence of an output schema, the description is minimally adequate. It covers the basic purpose and parameter, but without annotations and with sparse parameter details, it doesn't fully prepare the agent for effective use. The output schema helps, but the description could benefit from more context.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The description adds minimal semantics beyond the input schema: it explains that 'repository_path' is the 'Path to the repository' with a default of 'current directory.' However, with 0% schema description coverage, the schema only provides a title and type. The description compensates slightly by clarifying the parameter's role, but it doesn't detail format constraints or usage examples, leaving room for improvement.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the tool's purpose: 'List issues in a Radicle repository.' It specifies the verb ('List') and resource ('issues in a Radicle repository'), making the action and target explicit. However, it doesn't differentiate from sibling tools like 'rad_patch_list' or 'rad_remote_list' beyond the resource type, 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.

Usage Guidelines2/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description provides no guidance on when to use this tool versus alternatives. It mentions the default parameter value ('current directory') but offers no context about prerequisites, when it's appropriate, or how it differs from other listing tools in the sibling set. This leaves the agent without usage direction.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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