Lead Scorer

v1.0.0

Score and qualify leads using customizable criteria. Prioritize your pipeline by fit, intent, and engagement to focus on deals most likely to close.

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MIT-0
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LicenseMIT-0 · Free to use, modify, and redistribute. No attribution required.
Security Scan
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Benign
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OpenClawOpenClaw
Benign
high confidence
Purpose & Capability
Name, description, README and SKILL.md all describe lead scoring, grading, and batch scoring. There are no unexpected required binaries, env vars, or credentials; the declared purpose matches what the skill asks the agent to do.
Instruction Scope
SKILL.md defines scoring criteria, qualification frameworks (BANT/MEDDIC), and expected outputs. It does not instruct the agent to read arbitrary files, access environment variables, or call external endpoints. Batch scoring implies the user will provide lead data (paste/upload) — the skill stays within that scope.
Install Mechanism
No install spec and no code files. This is the lowest-risk model: nothing is written to disk or fetched at install time.
Credentials
The skill declares no environment variables, credentials, or config paths. There is nothing disproportionate or unexplained for a lead-scoring helper.
Persistence & Privilege
always is false and there are no indications the skill requests persistent system privileges or modifies other skills. Autonomous invocation is allowed by platform default but is not combined with any broad privileges here.
Assessment
This skill is instruction-only and appears coherent with its stated purpose. Before using it, avoid pasting sensitive personally identifiable information or confidential account data into chat (use anonymized or synthetic examples if needed). The README references an external paid resource URL — review that site separately if you plan to follow up. If you need automated integration with your CRM, expect to supply explicit connectors or credentials (this skill does not provide them). Otherwise it's safe to try for manual/batch scoring workflows.

Like a lobster shell, security has layers — review code before you run it.

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License

MIT-0
Free to use, modify, and redistribute. No attribution required.

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