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Signal Radar — AI Account Intelligence & ICP Scoring

signal_radar
Read-only

Turn Google Maps or LinkedIn scraper results into ICP-scored, signal-tagged…. Turn Google Maps or LinkedIn scraper results into ICP-scored, signal-tagged accounts. Paste domains, get fit scores. Works with any lead scraper output.

Input Schema

NameRequiredDescriptionDefault
inputNoInput for Signal Radar — AI Account Intelligence & ICP Scoring. See https://apify.com/noniner/signal-radar.

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

C2.7/5.0
Behavior2/5

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

Annotations already declare readOnlyHint=true and openWorldHint=true, but the description adds little beyond 'paste domains, get fit scores' — no mention of processing time, cost, data retention, or what happens to unmatched domains. For a scoring pipeline over arbitrary scraped input, the behavioral gaps (asynchronous? batch limits?) are left entirely unexplained.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness2/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The first sentence is truncated mid-phrase and then repeated verbatim in the second, burning space without adding information. What remains is short and front-loaded, but the duplication is clear waste.

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?

No output schema, no annotated properties on the nested input object, and no description of what a 'fit score' or 'signal tag' response looks like. For a tool whose entire value is a scoring output, the definition is not complete enough for an agent to invoke it confidently.

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?

There is one parameter and the schema nominally covers it at 100%, but that 'coverage' is a generic nested object pointing at an external URL with no defined sub-properties. The description only hints at the input shape ('paste domains', 'any lead scraper output'), which is somewhat useful but far from a usable contract. Baseline 3 given nominal full coverage.

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 concrete verb and resource: turns scraper output into ICP-scored, signal-tagged accounts, and mentions the input modality (paste domains). It is clear what the tool produces, but it never distinguishes itself from close siblings like ai_company_enrichment, b2b_intent_radar, or google_maps_lead_enricher. The duplicated/truncated opening sentence also slightly muddies the read.

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?

The only usage signal is the loose claim 'Works with any lead scraper output.' There is no statement of when to pick this over the many sibling enrichment/scoring tools, no prerequisites, and no exclusion criteria. An agent gets no routing help.

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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