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get_icp_profile

Read-only

Retrieve comprehensive ideal customer profiles with intelligence layers, buyer insights, and churn predictors to inform enterprise sales strategies.

Instructions

Returns everything Andru knows about your ideal customer — all 5 intelligence layers, the 7 critical buyer questions, and the patterns that predict churn. Optionally filter to specific layers.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
layersNoSpecific layers to include (1-5). Omit for all layers.
includeSevenAnswersNoInclude seven critical buyer answers (default: true)
includeAntiPatternsNoInclude anti-patterns and churn predictors (default: true)

Implementation Reference

  • src/catalog.js:266-282 (registration)
    The tool `get_icp_profile` is registered in `src/catalog.js`. It does not have local handler code because it is proxied to the Andru backend API by `src/server.js` using `src/client.js`.
    {
      name: 'get_icp_profile',
      description: 'Returns everything Andru knows about your ideal customer — all 5 intelligence layers, the 7 critical buyer questions, and the patterns that predict churn. Optionally filter to specific layers.',
      annotations: READ_ONLY,
      inputSchema: {
        type: 'object',
        properties: {
          layers: {
            type: 'array',
            items: { type: 'number', enum: [1, 2, 3, 4, 5] },
            description: 'Specific layers to include (1-5). Omit for all layers.',
          },
          includeSevenAnswers: { type: 'boolean', description: 'Include seven critical buyer answers (default: true)' },
          includeAntiPatterns: { type: 'boolean', description: 'Include anti-patterns and churn predictors (default: true)' },
        },
      },
    },
  • The actual execution of the tool is handled generically in `src/server.js` by calling `client.callTool(name, args)`.
    server.setRequestHandler(
      CallToolRequestSchema,
      async (request) => {
        if (!client) {
          return {
            content: [{ type: 'text', text: JSON.stringify({ error: 'ANDRU_API_KEY not configured. Tool execution requires an API key.' }) }],
            isError: true,
          };
        }
        const { name, arguments: args } = request.params;
        try {
          return await client.callTool(name, args || {});
        } catch (error) {
          return {
            content: [{
              type: 'text',
              text: JSON.stringify({ error: error.message }),
            }],
            isError: true,
          };
        }
      }
    );
Behavior4/5

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

Annotations already indicate read-only and open-world characteristics. The description adds valuable context about what information is returned (5 layers, 7 buyer questions, churn patterns) and the optional filtering capability, which goes beyond the annotations. No contradiction with annotations exists.

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 efficiently structured in two sentences: the first states the comprehensive return value, and the second mentions the optional filtering capability. Every element serves a purpose with no wasted words.

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?

For a read-only query tool with good annotations and full parameter documentation, the description provides adequate context about what intelligence is returned. However, without an output schema, it could benefit from more detail about the return format structure.

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?

With 100% schema description coverage, the schema fully documents all three parameters. The description mentions optional filtering to specific layers, which aligns with the 'layers' parameter but doesn't add meaningful semantic context beyond what's already in the schema descriptions.

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

Purpose5/5

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

The description clearly states the tool returns comprehensive ICP information with specific details about 'all 5 intelligence layers, the 7 critical buyer questions, and the patterns that predict churn.' It distinguishes itself from siblings by focusing on complete ICP profiles rather than specific aspects like fit scores, positioning, or disqualification signals.

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

Usage Guidelines3/5

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

The description implies usage for obtaining complete ICP intelligence but doesn't explicitly state when to use this tool versus alternatives like get_icp_fit_score, get_competitive_positioning, or get_disqualification_signals. No specific exclusions or prerequisites are mentioned.

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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