ads-audit
Full multi-platform paid advertising audit with parallel subagent delegation. Analyzes Google Ads, Meta Ads, LinkedIn Ads, TikTok Ads, and Microsoft Ads…
Qualify B2B leads against a user-defined Ideal Customer Profile (ICP). Use this skill whenever the user
$ npx -y skills add naveedharri/benai-skills --skill lead-qualification --agent claude-codeHow it fires
How this skill gets triggered: by you, by Claude, or both.
/lead-qualificationContext preview
The summary Claude sees to decide when to auto-load this skill.
Qualify B2B leads against a user-defined Ideal Customer Profile (ICP). Use this skill whenever the user
name: lead-qualification description: Qualify B2B leads against a user-defined Ideal Customer Profile (ICP). Use this skill whenever the user uploads a lead list (CSV, XLSX, JSON) and wants to filter or qualify leads based on any criteria: services, technologies, headcount, geography, niche, vertical, job title, revenue, or anything else. Also trigger when the user says "qualify leads", "filter my leads", "which leads match my ICP", "score these leads", "segment this list", "clean up my lead list", or "find the best leads". This skill handles lead lists of any size by automatically batching work across parallel sub-agents. disable-model-invocation: true
You are qualifying a list of B2B leads against the user's Ideal Customer Profile. Your job is to take a raw lead list, understand exactly what the user considers a "good" lead, and return a clean set of qualified leads with clear reasoning for each decision.
You need two things from the user. Do not proceed without both:
1. **The lead list** - a file (CSV, XLSX, or JSON) containing the leads 2. **The ICP definition** - the user's specific criteria for what makes a qualified lead
The ICP definition can be literally anything. Never assume what it looks like. Ask the user to describe their ideal customer in their own words. Here are examples of dimensions they might care about, but this list is not exhaustive:
If the user's ICP is vague (e.g., "good companies" or "people who would be interested"), push back. Ask: "What specifically makes a company a good fit? What would make you NOT want to reach out?" You need concrete, actionable criteria.
Sometimes the ICP has AND conditions ("must be US-based AND offer SEO AND have 11-50 employees") and sometimes it has OR conditions ("healthcare OR legal vertical"). Clarify the logic. Ask: "Do they need to meet ALL of these, or are some of these nice-to-haves?"
Read the file and understand its structure. Report to the user:
This lets the user confirm the data is loaded correctly and gives you a chance to spot issues early (missing columns, weird formatting, duplicates).
**CRITICAL RULE: NEVER rely on CSV/spreadsheet data alone for qualification.** CSV data is frequently wrong. Every lead MUST be verified through WebSearch across multiple sources.
The sub-agent's job for each lead: 1. Read the available CSV columns for the lead 2. Use WebSearch to research the company from multiple sources, not just the company's own website 3. Cross-reference findings from review sites (G2, Clutch, Trustpilot), industry directories, news articles, LinkedIn company pages, job boards, and other third-party sources 4. Check whether the combined evidence confirms the company matches the ICP
**ALWAYS use WebSearch and check multiple sources.** A company's own website only tells one side of the story. Third-party sources reveal actual services offered, real employee counts, recent news, client reviews, and other signals that are critical for accurate qualification. Aim for 2-3 WebSearch queries per lead to build a complete picture.
Qualification MUST happen via `lead-qualifier` sub-agents for any list larger than 10 leads. Here's the math:
Tell the user the plan before launching: "I have 606 leads to qualify. I'll launch 61 sub-agents, each handling 10 leads. Running in parallel, this should take roughly X minutes."
**Time estimation guidelines:**
**Record the start time** (use Python `time.time()` or bash `date +%s`).
Spawn ALL `lead-qualifier` sub-agents in a single message for maximum parallelism. Each sub-agent receives:
1. Its batch of leads (as JSON) 2. The full ICP definition (copy it verbatim, don't summarize) 3. Clear instructions on qualification logic (AND/OR conditions) 4. The output file path
**What to include in each sub-agent's prompt:**
[PASTE THE FULL ICP DEFINITION HERE] [SPECIFY AND/OR LOGIC: "A lead must meet ALL of these criteria to qualify" or whatever the logic is] Here are your leads (JSON): [LEAD BATCH] MANDATORY: Use WebSearch to research EVERY lead from multiple sources. Never qualify based on CSV data alone or just the company's own website. For each lead, run 2-3 WebSearch queries: one for the company website, and additional searches to cross-reference with review sites, industry directories, news articles, and LinkedIn. Third-party sources are essential for verifying actual services, employee count, and ICP fit. Save your results as a JSON array to: [file path]
**Critical: Spawn ALL `lead-qua
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Repo: naveedharri/benai-skills
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