Discover niche first-party signals that differentiate Closed Won vs Closed Lost accounts for ICP analysis. Use when the user provides won/lost customer domain lists and wants differential signals (website content, job listings, tech stack, maturity markers) to build account scoring models and prospecting criteria. Triggers: ICP analysis, niche signals, won vs lost analysis, differential signals, signal discovery, ICP signal report, account scoring signals, lead scoring, first-party signals, buyer signals. Before reading this file, first read deepline-gtm to understand the Deepline CLI tool and how to use it. Then read this file for guidance on the task.
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Low-risk findings worth noting
Low
Low-risk findings.
2 low severity findings. Worth noting, but not necessarily harmful.
The skill exposes the agent to untrusted, user-generated content from public third-party sources, creating a risk of indirect prompt injection. This includes browsing arbitrary URLs, reading social media posts or forum comments, and analyzing content from unknown websites.
SKILL.md Step 2.5–2b and Step 7 require the agent to scrape outsider-authored free text from the public web (multi-page website content and job listing pages discovered via Serper/Firecrawl and CrustData), then ingest that extracted text into the runtime CSV that `scripts/analyze_signals.py` parses for evidence quotes and scoring.
The skill fetches instructions or code from an external URL at runtime, and the fetched content directly controls the agent’s prompts or executes code. This dynamic dependency allows the external source to modify the agent’s behavior without any changes to the skill itself.
The SKILL.md includes a fallback npm install that uses the registry URL https://code.deepline.com/api/v2/npm/ (SKILL.md:7), which would fetch and install/execute remote CLI code that the skill requires to run.
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