Mach GTM MCP

score_lead

Score a B2B lead against your ICP criteria to get a 0–100 fit score, confidence level, and top reasons for or against pursuing the account.

Instructions

Score a B2B lead against your ICP criteria. Returns a fit score (0-100), a confidence level, and the top reasons for or against pursuing this account.

Tool call template

Replace each placeholder with a value matching the input schema. Only required parameters are included; add optional parameters as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {
      "company_name": "<company_name>",
      "industry": "<industry>",
      "icp": "<icp>"
    },
    "name": "score_lead"
  }
}

Input Schema

Name	Required	Description
`icp`	Yes	Your ICP criteria to score against.
`industry`	Yes
`tech_stack`	No	Known technologies they use (e.g. ["Salesforce", "HubSpot", "AWS"]).
`company_name`	Yes
`annual_revenue`	No	Estimated ARR/revenue (e.g. "$5M-$20M").
`buying_signals`	No	Observed signals (e.g. ["hiring SDRs", "posted about scaling sales"]).
`employee_count`	No	Number of employees.

Schema Changelog

Changes observed during successful MCP inspections.

First observedv1.0.0Nov 7, 2026

TDQS

B3.3/5.0

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 does useful work by disclosing the return shape — a 0-100 fit score, a confidence level, and ranked reasons — which is valuable given there is no output schema. It does not say whether scoring uses only the supplied fields or triggers external enrichment, nor whether results are deterministic or costly to produce.

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?

Two sentences, zero filler, with the operation front-loaded and the return values immediately after. Every sentence earns its place.

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

Completeness3/5

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

For a 7-parameter scoring tool with no annotations and no output schema, the description covers the output shape adequately but omits whether external research happens, what 'confidence' measures, and how it relates to build_icp. It is minimally sufficient but leaves real gaps for an agent deciding whether this call is cheap, safe, or self-contained.

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 description coverage is 71%, so most parameters (icp, tech_stack, annual_revenue, buying_signals, employee_count) are already documented with examples in the schema. The description adds no parameter-level meaning and leaves the required company_name and industry undocumented in both places, but the high coverage keeps this at baseline.

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 gives a specific verb and resource ('Score a B2B lead') plus the basis ('against your ICP criteria'), so the operation is unambiguous. It implicitly separates itself from build_icp (which creates the criteria) but never names that relationship, so it falls just short of explicit sibling differentiation.

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?

There is no when-to-use guidance, no exclusion conditions, and no mention of the prerequisite relationship with build_icp (you presumably need an ICP before scoring against one). An agent must infer sequencing and routing from the name alone.

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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