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icp-intelligence-mcp

ICP Scoring Model

icp_scoring_model
Read-only

Create a lead qualification scoring template: criteria with example point weights set by importance level, example points for each value you list, a scorecard and tier bands to adjust. Your success pattern is matched to your criteria; it does not set the weights. Sector notes are added when your inputs name one of the supported sectors

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
companyNoOptional: your company or product name, so the answer can name it
product_categoryNoOptional: what you sell, as a product category, so the scoring notes use your sector
scoring_criteriaNoCriteria for scoring with importance levels
success_correlationNoWhat correlates with success? (e.g., "deals with VP Sales champion close 2x faster")

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A3.8/5.0
Behavior4/5

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

Annotations already declare readOnlyHint=true, destructiveHint=false and openWorldHint=false, so the safety profile is covered. The description adds genuine behavioral context beyond that: success patterns are matched to supplied criteria rather than setting weights, and sector notes are conditionally added based on the named sector. It doesn't state what the template returns or whether weights are editable.

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?

Two tight sentences with no filler; the creation scope is front-loaded. The second sentence is somewhat dense and the list-like output enumeration reads awkwardly, but nothing is wasted.

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, zero-mandatory-parameter generation tool with all four params documented and no output schema, the description covers what gets produced and how inputs are consumed. Missing only explicit guidance on how the output differs from the sibling icp_* tools.

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?

Schema coverage is 100%, so the baseline is 3, but the description adds real meaning: importance level drives example point weights, points are generated per listed value, and success_correlation informs criteria rather than weights. This clarifies intended use of two parameters beyond their schema text.

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?

States a specific verb+resource: 'Create a lead qualification scoring template' and enumerates its output parts (criteria, weights, points, scorecard, tier bands). It does not name any sibling tool, so an agent can't tell from this alone when to pick it over icp_deep_dive or icp_gap_analysis.

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?

Usage is implied by the creation framing rather than stated: nothing says when to use this versus the other icp_* siblings, and no prerequisites are given. The only conditional-narrowing sentence ('Sector notes are added when your inputs name one of the supported sectors') describes behavior, not when to select the tool.

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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