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shashwatgtm

ICP Intelligence MCP

by shashwatgtm

icp_interview_synthesizer

Extract ideal customer profile patterns from interview notes or transcripts by analyzing pain points, buying journey, and value propositions to identify target segments.

Instructions

Extract ICP patterns from customer interview notes or transcripts

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
analysis_focusNoWhat to focus on: pain_points, buying_journey, value_props, all
interview_notesNoStructured interview notes
raw_transcriptsNoAlternative: Paste raw interview transcripts or notes

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv1.0.0

TDQS

B3.4/5.0
Behavior2/5

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

No annotations are provided, so the description must carry the full burden. It only says 'extract', which implies a read operation, but it doesn't disclose whether the tool is read-only, what the output format is, or any side effects. This is a significant gap for a synthesis 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 is a single, front-loaded sentence with zero wasted words. It communicates the core function and input type immediately.

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?

There is no output schema, so the description should hint at what the tool returns (e.g., the nature of extracted patterns). It also doesn't mention any prerequisites or limitations. This leaves an agent unsure about the expected output and potential edge cases.

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?

Schema coverage is 100%, so the baseline is 3. The description adds a small amount of value by clarifying that interview_notes and raw_transcripts are alternative input methods ('or'), but it doesn't elaborate on parameter semantics beyond what the schema already states.

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 a specific action (extract) on a specific resource (ICP patterns) from customer interview notes or transcripts. It's unambiguous and distinguishes this tool from scoring or deep-dive tools, though it doesn't name alternatives.

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 when you have interview notes or transcripts, but it doesn't explicitly compare to siblings like icp_deep_dive or icp_scoring_model, nor does it state when not to use this tool. The context is clear but not prescriptive.

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