mcp-gtm-signals-aggregator

Aggregate GTM Signals

aggregate_gtm_signals

Read-onlyIdempotent

Aggregate a company's GTM signals into one composite score by running hiring and tech-stack detection in a single call, then return a Clay-ready JSON row with a recommended action.

Instructions

Aggregate a company's GTM signals into one composite score. Runs hiring-signal and tech-stack detection in a single call and returns a flat, Clay-ready JSON row with a composite GTM score, a recommended action, and an optional plain-English summary. Read-only; requires an APIFY_TOKEN and consumes Apify credits per call.

Input Schema

Name	Required	Description
`sources`	No	Which signals to aggregate. Default ["hiring", "tech_stack"], which is what this actor has always run. Each extra source is one more sub actor run on the caller's own Apify account, so this is the cost dial as well as the depth dial. The composite score is normalized over the sources you selected, so a funding only run is scored on its own scale rather than capped by absent sources.
`explain_mode`	No	If true, gtm_signal_summary becomes a longer, more detailed explanation instead of a 1 to 2 sentence summary.
`company_domain`	Yes	Bare company domain without https:// and without a trailing slash. Example: stripe.com
`include_summary`	No	Include a plain-English gtm_signal_summary field in the output. Defaults to the actor's default when omitted.

Schema Changelog

Changes observed during successful MCP inspections.

Changed2 schema fields changedv1.0.6Oct 13, 2026

removedInput schema / additionalProperties
```
Removed value: -false
```

addedInput schema / properties / sources

Added value: +{
+  "description": "Which signals to aggregate. Default [\"hiring\", \"tech_stack\"], which is what this actor has always run. Each extra source is one more sub actor run on the caller's own Apify account, so this is the cost dial as well as the depth dial. The composite score is normalized over the sources you selected, so a funding only run is scored on its own scale rather than capped by absent sources.",
+  "items": {
+    "enum": [
+      "hiring",
+      "tech_stack",
+      "funding",
+      "events",
+      "workplace"
+    ],
+    "type": "string"
+  },
+  "type": "array"
+}

First observedv1.0.3Jun 2, 2026

TDQS

A4/5.0

Behavior4/5

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

Annotations already cover the safety profile (readOnly, idempotent, non-destructive, open world), so the bar is lower. The description goes beyond them usefully by naming the required APIFY_TOKEN and the fact that each call consumes Apify credits, which is real operational context an agent should know before invoking.

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?

Three sentences, front-loaded with the core action, then output shape, then auth/cost caveat. No filler and nothing repeated from the title.

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?

With no output schema, the description does its job by naming the return payload (composite GTM score, recommended action, optional plain-English summary). It stops short of describing failure modes or latency, which would be nice but is not required for correct invocation.

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%, including rich prose on the 'sources' cost/depth dial and normalization behavior, so the schema carries parameter meaning fully. The description adds nothing parameter-specific beyond what the schema already documents; baseline 3 applies.

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?

States a specific verb and resource ('Aggregate a company's GTM signals into one composite score') and enumerates the concrete work performed ('runs hiring-signal and tech-stack detection in a single call'). Cheap to tell apart from anything else and leaves no ambiguity about the output artifact.

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?

Implies the usage context (call it to obtain a composite GTM score and recommended action) and notes the auth/cost precondition, but never says when to reach for this versus building the signals separately, nor when a narrower call would suffice. No sibling tools exist, so the routing burden is low and a 3 is fair.

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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Other Tools

aggregate_gtm_signalsA