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get_tool_documentation

Retrieve detailed documentation for Azure DevOps tools including parameters and usage examples to understand functionality and implementation.

Instructions

Gets detailed documentation for a specific tool including parameters and examples.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
tool_nameYesThe name of the tool to get documentation for.

Implementation Reference

  • Handler function that implements the logic for get_tool_documentation by retrieving the tool's metadata from the self.tools list.
    def _get_tool_documentation(self, tool_name: str) -> Dict[str, Any]:
        """Get documentation for a specific tool."""
        tool = next((t for t in self.tools if t.name == tool_name), None)
        if tool:
            return {
                "name": tool.name,
                "description": tool.description,
                "inputSchema": tool.inputSchema,
            }
        else:
            return {"error": f"Tool '{tool_name}' not found."}
  • Schema definition and registration of the get_tool_documentation tool, including input schema.
    types.Tool(
        name="get_tool_documentation",
        description="Gets detailed documentation for a specific tool including parameters and examples.",
        inputSchema={
            "type": "object",
            "properties": {
                "tool_name": {
                    "type": "string", 
                    "description": "The name of the tool to get documentation for."
                },
            },
            "required": ["tool_name"],
            "additionalProperties": False
        }
    ),
  • Dispatch/registration in the _execute_tool method that routes calls to the get_tool_documentation handler.
    elif name == "get_tool_documentation":
        return self._get_tool_documentation(arguments.get("tool_name"))
  • The list_tools handler that registers and exposes all tools, including get_tool_documentation, via MCP protocol.
    @self.server.list_tools()
    async def list_tools() -> List[types.Tool]:
        """Return the list of available tools."""
        logger.info(f"Tools requested - returning {len(self.tools)} tools")
        self.tools_registered = True
        return self.tools
Behavior2/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

No annotations are provided, so the description carries full burden. It mentions retrieving 'detailed documentation including parameters and examples,' which hints at a read-only operation, but doesn't disclose behavioral traits like error handling (e.g., if tool_name is invalid), response format, or any rate limits. This is 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.

Conciseness5/5

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

The description is a single, efficient sentence that front-loads the core purpose ('Gets detailed documentation') and specifies the scope ('for a specific tool including parameters and examples'). There is no wasted text, 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.

Completeness2/5

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

Given no annotations and no output schema, the description is incomplete. It doesn't explain what the detailed documentation includes beyond 'parameters and examples' (e.g., usage guidelines, return values), nor does it cover error cases or behavioral aspects. For a tool with rich potential output, this leaves significant gaps.

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 input schema has 100% description coverage, with 'tool_name' clearly documented. The description adds no additional parameter semantics beyond what the schema provides, such as format 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.

Purpose4/5

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

The description clearly states the verb ('Gets') and resource ('detailed documentation for a specific tool'), specifying what it retrieves. It distinguishes from siblings like 'list_tools' by focusing on detailed documentation rather than listing. However, it doesn't explicitly contrast with other documentation-related tools (none exist in siblings), so it's not 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.

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 doesn't mention prerequisites, such as needing to know the tool name beforehand, or compare it to 'list_tools' for discovery. Usage is implied but not explicitly stated, leaving gaps for an AI agent.

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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