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get_ai_tool_documentation

Retrieve documentation for DEVONthink AI tools, including examples and use cases, to understand their functionality and applications.

Instructions

Get detailed documentation for DEVONthink AI tools including examples and use cases. Optionally specify a toolName to get docs for a single tool; omit to get docs for all four.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
toolNameNoOptional name of the specific AI tool to document. One of: get_ai_tool_documentation, check_ai_health, ask_ai_about_documents, create_summary_document.

Implementation Reference

  • Implementation of the get_ai_tool_documentation MCP tool, including definition, schema, and run handler.
    export const getAiToolDocumentationTool = defineTool({
      name: "get_ai_tool_documentation",
      description:
        "Get detailed documentation for DEVONthink AI tools including examples and use cases. " +
        "Optionally specify a toolName to get docs for a single tool; omit to get docs for all four.",
      schema: z.object({
        toolName: z
          .enum(AI_TOOL_NAMES)
          .optional()
          .describe(
            "Optional name of the specific AI tool to document. " +
              "One of: get_ai_tool_documentation, check_ai_health, " +
              "ask_ai_about_documents, create_summary_document."
          ),
      }),
      run: async (args, _executor) => {
        const { toolName } = args;
    
        if (toolName) {
          const doc = AI_TOOL_DOCS[toolName];
          if (!doc) {
            return { error: `No documentation found for tool: ${toolName}` };
          }
          return doc;
        }
    
        // Return all tool docs as an array
        return AI_TOOL_NAMES.map((name) => AI_TOOL_DOCS[name]);
      },
    });
Behavior3/5

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

No annotations are provided, so the description carries the full burden. It adds context that the documentation includes 'examples and use cases,' hinting at the output structure. However, it fails to disclose safety characteristics (read-only vs. destructive), rate limits, or output format details that would help an agent understand the operational impact of calling this tool.

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 consists of exactly two sentences, both earning their place. The first establishes purpose and content scope; the second explains the parameter usage pattern. There is no redundant or extraneous text—every word contributes to agent understanding.

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

Completeness4/5

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

Given the tool's low complexity (1 optional parameter, no nested objects, no output schema), the description is appropriately complete. It explains what the tool does, what it returns conceptually (documentation with examples), and how to use its single parameter. It could be improved by explicitly listing the four AI tool names in the description text rather than relying solely on the schema enum.

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

Parameters4/5

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

With 100% schema description coverage, the baseline is 3. The description adds value by explaining the semantic consequence of omitting the parameter ('omit to get docs for all four'), which is not explicitly stated in the schema description. This clarifies the filtering behavior beyond the raw schema definition.

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 retrieves 'detailed documentation for DEVONthink AI tools' and mentions specific content types ('examples and use cases'). It distinguishes from the 20+ sibling tools by specifying the 'AI tools' scope and referencing 'all four' to limit the domain, though it doesn't explicitly name the four tools in the description text.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines4/5

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

The description provides clear guidance on parameter usage: 'Optionally specify a toolName to get docs for a single tool; omit to get docs for all four.' This effectively explains when to provide the parameter versus when to omit it. However, it lacks explicit guidance on when to use this tool versus general help resources or the other AI tools directly.

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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