Agent skill

Inbound Lead Qualifier

by OneWave-AI in OneWave-AI/claude-skills

Analyze inbound leads (form fills, demo requests) and score based on ICP fit, intent, and urgency.

MITAuto-check passedMarketing & SEO

Install Inbound Lead Qualifier

skills CLI
$ npx skills add OneWave-AI/claude-skills --skill inbound-lead-qualifier -a claude-code

Project install by default; add -g for ~/.claude/skills/.

GitHub CLI
$ gh skill install OneWave-AI/claude-skills inbound-lead-qualifier --agent claude-code

Project scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).

Manual copy
$ git clone --depth 1 https://github.com/OneWave-AI/claude-skills.git skills-src && mkdir -p .claude/skills && cp -r skills-src/inbound-lead-qualifier .claude/skills/inbound-lead-qualifier && rm -rf skills-src

Use ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.

Claude Code skills documentation · loads skills from .claude/skills/

Facts

Skill name
inbound-lead-qualifier
GitHub stars
336
Token cost
~1.4k tokens
SKILL.md length
279 words
Files
1
Skills in repo
69
Repo updated
First seen
Licence
MIT

At a glance

Analyze inbound leads (form fills, demo requests) and score based on ICP fit, intent, and urgency.

  • Works in 3 steps: [Question about pricing] → [Question about implementation] → [Question about integrations]
  • Qualifying and routing inbound leads at scale
  • Instructions only: no scripts, shell commands, URLs or credentials in SKILL.md
  • Tasks that involve Lead generation

What it does

Inbound Lead Qualifier is an agent skill from OneWave-AI/claude-skills. Analyze inbound leads (form fills, demo requests) and score based on ICP fit, intent, and urgency. Auto-generates qualification questions, routes to right rep, and suggests personalized first touch. Use for qualifying and routing inbound leads at scale.

Its SKILL.md is about 1.4k tokens, which your agent loads only when the skill is triggered. It is a single SKILL.md file with no bundled scripts.

It sits in Marketing & SEO, covering Lead generation. The repository describes itself as: 200+ production-ready Claude Code skills for sales, marketing, design, engineering, and AI agent architecture. Built and maintained by OneWave AI. The licence is MIT.

When your agent uses it

  • Qualifying and routing inbound leads at scale
  • Tasks that involve Lead generation

Example prompts

  • “/inbound-lead-qualifier”

Workflow steps

3 steps, taken from the first numbered list in SKILL.md.

  1. [Question about pricing]
  2. [Question about implementation]
  3. [Question about integrations]

What it can do on your machine

Read from SKILL.md and the folder at commit fc5b785. It shows what the files ask for, not the result of running them.

  • Tool permissions

    Pre-approves nothing: there is no allowed-tools line, so your agent's usual permission prompts apply.

    From allowed-tools in the SKILL.md frontmatter.

  • Runs code

    No scripts in the folder and no shell commands in SKILL.md (its code samples are markdown).

    From the folder's file list and the shell code blocks in SKILL.md.

  • Network

    No URLs in SKILL.md.

    From URLs in SKILL.md, links to its own repository left out.

  • Credentials

    Names no API keys, tokens, secrets or passwords.

    From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.

Context cost

Inbound Lead Qualifier loads about 1.4k tokens when it runs. Until then it costs about 69 tokens; SKILL.md has 279 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~69
When it runs · the whole SKILL.md, loaded when a task matches
~1.4k

Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.

Safety

Auto-check passed

The automated check found no risky patterns in SKILL.md.

Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); files beside SKILL.md are not scanned.

SKILL.md

The full file from OneWave-AI/claude-skills at commit fc5b785, republished under its MIT licence (© OneWave-AI). 279 words, ~1,378 tokens.

Download SKILL.mdSave it as .claude/skills/inbound-lead-qualifier/SKILL.md (or your agent's skills folder).
name
inbound-lead-qualifier
description
Analyze inbound leads (form fills, demo requests) and score based on ICP fit, intent, and urgency. Auto-generates qualification questions, routes to right rep, and suggests personalized first touch. Use for qualifying and routing inbound leads at scale.

Inbound Lead Qualifier & Router

Turn inbound leads into qualified opportunities in minutes, not days.

Instructions

You are an expert at lead qualification and routing who helps sales teams maximize conversion from inbound interest. Your mission is to instantly qualify leads, prioritize them, and route to the right rep with perfect context.

Lead Scoring Framework

ICP Fit (0-40 points):

  • Company size: 0-10
  • Industry match: 0-10
  • Tech stack fit: 0-10
  • Budget indicators: 0-10

Intent (0-30 points):

  • Demo request: 30
  • Pricing page visit: 20
  • Content download: 10
  • General inquiry: 5

Urgency (0-30 points):

  • "Need ASAP": 30
  • Timeline mentioned: 20
  • "Exploring": 10
  • No timeline: 5

Total Score: 0-100

  • 80-100: Hot lead - Call within 1 hour
  • 60-79: Warm lead - Call within 24 hours
  • 40-59: Cool lead - Email, then call
  • Below 40: Nurture, don't call
Output Format
markdown
# Inbound Lead Analysis

**Lead**: [Name] from [Company]
**Source**: [Form/Demo Request/etc.]
**Received**: [Date/Time]
**Lead Score**: [X]/100

---

## Quick Assessment

**Priority**: HOT / WARM / COOL / NURTURE

**Recommendation**: [Call now / Call today / Email first / Add to nurture]

**Assign To**: [Rep Name] (owns [territory/industry])

**First Message**: [Suggested opening line]

---

## Lead Scoring Breakdown

**ICP Fit**: 35/40 STRONG FIT
- Company Size: 8/10 (250 employees, target is 200-500)
- Industry: 10/10 (Perfect match: B2B SaaS)
- Tech Stack: 9/10 (Using 3/4 target technologies)
- Budget: 8/10 (Funded company, likely has budget)

**Intent**: 25/30 HIGH INTENT
- Requested demo (not just content download)
- Visited pricing page 3x
- Specific use case mentioned in form

**Urgency**: 20/30 MODERATE
- Timeline: "Next quarter"
- Not immediate but real need
- Current solution expires in 60 days

**Total**: 80/100 **HOT LEAD**

---

## Lead Details

**Contact**:
- Name: [First Last]
- Title: [Job Title]
- Email: [Email]
- Phone: [Phone]
- LinkedIn: [URL]

**Company**:
- Name: [Company]
- Industry: [Industry]
- Size: [X] employees
- Location: [City, State]
- Website: [URL]
- Funding: [Series X, $Y raised]

**Engagement History**:
- First touch: [Date]
- Page views: [X]
- Content downloaded: [List]
- Email opens: [X]%
- Demo request: [Date]

---

## Qualification Questions

**Must-Ask (Critical)**:
1. "What's driving you to look at [product type] right now?"
2. "What are you currently using for [use case]?"
3. "When do you need this in place?"
4. "Who else is involved in this decision?"

**Good-to-Ask (Context)**:
5. "What would success look like?"
6. "What's your budget range?"
7. "Have you looked at other options?"

**Expected Answers** (based on data):
- Likely pain: [Problem they mentioned]
- Current solution: [Competitor likely]
- Decision maker: [Probably their boss, [Title]]
- Budget: $[Estimated based on company size]

---

## Recommended Outreach

**Call Script** (within 1 hour):

Hi [Name], this is [Your Name] from [Company].

I see you requested a demo about 30 minutes ago - thanks for your interest!

Quick question before I show you around: what's prompting you to look at [product category] right now?

[Listen]

Got it. And are you currently using [competitor/manual process]?

[Listen]

Perfect. Let me show you exactly how we solve that...


**Email Template** (if no answer):

Subject: Re: Demo Request - [Company Name]

Hi [Name],

Just tried calling (missed you!) about your demo request.

Quick context before we connect:

I work with a lot of [their role] at [similar companies] who are dealing with [their likely pain].

Most common questions I get:

  1. [Question about pricing]
  2. [Question about implementation]
  3. [Question about integrations]

Happy to answer these + show you around.

When's good for a quick 15-min call?

[Your Name]


---

## Routing Logic

**Assign To**: [Rep Name]

**Why This Rep**:
- Territory: [Geographic/Industry match]
- Experience: [Has closed similar companies]
- Availability: [Available this week]
- Track record: [High win rate on similar leads]

**Briefing for Rep**:
> "Hot lead from [Company]. They're a [size] [industry] company using [current solution]. Requested demo specifically for [use case]. Score: 80/100. They mentioned [timeline]. Call within 1 hour."

---

## Lead Intelligence

**Similar Customers**:
- [Customer 1]: Similar size, closed in 30 days
- [Customer 2]: Same industry, $50K deal
- [Customer 3]: Used same tech stack

**Likely Objections**:
1. Price (budget concern)
2. Implementation time
3. Integration with [their tech]

**Competitive Intel**:
- Probably comparing to [Competitor]
- [Competitor] weakness: [What we do better]

---

## Next Steps

**Immediate (1 hour)**:
- [ ] Call lead (use script above)
- [ ] If no answer, send email
- [ ] Schedule demo for [Date]

**Short-term (24 hours)**:
- [ ] Send calendar invite with prep questions
- [ ] Research company deeper
- [ ] Prepare custom demo
- [ ] Identify decision maker on LinkedIn

**Follow-up**:
- [ ] Demo completed
- [ ] Proposal sent
- [ ] Create opportunity in CRM

Remember: Speed to lead matters - calling within 5 minutes = 10x better conversion than 30 minutes!

© OneWave-AI, MIT. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file

Files

Just SKILL.md in inbound-lead-qualifier of OneWave-AI/claude-skills.

Open the folder on GitHubat commit fc5b785

Compare with similar skills

Inbound Lead Qualifier next to the 5 skills that share the most tags, products or categories with it. Stars are the repository's; “used in” counts other GitHub owners with a copy.

Inbound Lead Qualifier compared with similar skills
SkillStarsUsed inTokensAuto-checkLicenceRepo updated
Inbound Lead Qualifier this skillOneWave-AI/claude-skills336—~1.4kAutomated safety check: PassMIT
Find Leadseracle/OpenOutreach3.2k—~4.6kAutomated safety check: PassGPL-3.0
100m Leadsgetagentseal/founder-playbook729—~2.3kAutomated safety check: PassMIT
Business Contact and Social Links Finderbrowser-act/skills6.1k1 repos~1.6kAutomated safety check: PassMIT
GitHub Lead GenDucksss/codex-profiles180—~1kAutomated safety check: PassMIT
LinkedIn Ads Managementivangfalco/ads-skills279—~1.7kAutomated safety check: PassCustom licence

Similar skills

  • Find Leads

    eracle/OpenOutreach

    Find qualified B2B leads with OpenOutreach — run openoutreach find N [emails], read the CSV it prints on stdout, and hand the rows to whatever sends.

    3.2k GitHub stars~4.6k tokensUpdated yesterday
    Marketing & SEOAuto-check passed
  • 100m Leads

    getagentseal/founder-playbook

    Builds lead generation systems using Alex Hormozi's Core Four framework (warm outreach, content, cold outreach, paid ads), lead magnets, and Rule of 100.

    729 GitHub stars~2.3k tokensUpdated 4 days ago
    Marketing & SEOAuto-check passed
  • Finds a company's official website and social profiles from its name, or collects social links from a website URL, using BrowserAct templates run by a Python script.

    6.1k GitHub starsUsed in 1 repo~1.6k tokens
    Marketing & SEOAuto-check passed
  • GitHub Lead Gen

    Ducksss/codex-profiles

    A skill your agent uses when running GitHub lead generation for codex-profiles.

    180 GitHub stars~1k tokensUpdated today
    Marketing & SEOAuto-check passed
  • LinkedIn Ads Management

    ivangfalco/ads-skills

    Routes LinkedIn Ads work for B2B SaaS to the right playbook: campaign planning, performance analysis, account audits, creative, scaling and account-based campaigns.

    279 GitHub stars~1.7k tokensUpdated 2 mo ago
    Marketing & SEOAuto-check passed
  • Free Tool Strategy

    freekmurze/dotfiles

    When the user wants to plan, evaluate, or build a free tool for marketing purposes — lead generation, SEO value, or brand awareness.

    1k GitHub starsUsed in 20 repos~1.4k tokens
    Marketing & SEOAuto-check passed

More from OneWave-AI/claude-skills

All 69 skills in this repo
  • CRM Data Cleanup

    OneWave-AI/claude-skills

    Finds duplicate and junk records in a CRM CSV export with fuzzy matching, normalizes fields and writes a reviewable merge plan plus import-ready files without touching the live CRM.

    336 GitHub stars~2.5k tokensUpdated 9 days ago
    Auto-check passed
  • Design Export Repair

    OneWave-AI/claude-skills

    Repairs broken decks and PDFs exported from Claude Design or similar AI deck generators: clipped text, wrong fonts and corrupted .pptx package structure.

    336 GitHub stars~2.6k tokensUpdated 9 days ago
    Auto-check passed
  • Bi Measure Builder

    OneWave-AI/claude-skills

    Writes, explains, debugs, and optimizes BI calculations - Power BI / Fabric DAX measures and calculated columns, Tableau calculated fields (FIXED/INCLUDE/EXCLUDE LOD expressions, table…

    336 GitHub stars~2.2k tokensUpdated 9 days ago
    Auto-check passed
  • Bookkeeping Close

    OneWave-AI/claude-skills

    Categorizes transactions, reconciles bank and card statements to the ledger, works a month-end checklist and prepares a close package, without ever forcing a balance.

    336 GitHub stars~2k tokensUpdated 9 days ago
    Auto-check passed
  • CSV and Excel Merger

    OneWave-AI/claude-skills

    Combines CSV, TSV and Excel files into one verified table with pandas, by stacking or joining, mapping columns, normalizing keys and removing duplicates.

    336 GitHub stars~1.6k tokensUpdated 9 days ago
    Auto-check passed
  • Sec Filing Puller

    OneWave-AI/claude-skills

    Pulls financial statement numbers for US public companies straight from SEC EDGAR's free official XBRL APIs (companyfacts, companyconcept, frames, submissions) into a cited table.

    336 GitHub stars~2.1k tokensUpdated 9 days ago
    Auto-check passed

Categories

Questions about Inbound Lead Qualifier

What does Inbound Lead Qualifier do?

Analyze inbound leads (form fills, demo requests) and score based on ICP fit, intent, and urgency. Inbound Lead Qualifier is an agent skill from OneWave-AI/claude-skills. Analyze inbound leads (form fills, demo requests) and score based on ICP fit, intent, and urgency.

When should I use Inbound Lead Qualifier?

Inbound Lead Qualifier fits situations like: qualifying and routing inbound leads at scale; tasks that involve Lead generation.

How do I install Inbound Lead Qualifier in Claude Code?

Run `npx skills add OneWave-AI/claude-skills --skill inbound-lead-qualifier -a claude-code`. Or copy the skill folder (inbound-lead-qualifier in OneWave-AI/claude-skills) into .claude/skills/inbound-lead-qualifier in your project. Claude Code loads it when a task matches its description.

How do I install Inbound Lead Qualifier in Codex?

Run `npx skills add OneWave-AI/claude-skills --skill inbound-lead-qualifier -a codex`. Or copy the skill folder (inbound-lead-qualifier in OneWave-AI/claude-skills) into .agents/skills/inbound-lead-qualifier in your project. Codex loads it when a task matches its description.

Can I use Inbound Lead Qualifier in Cursor, Gemini CLI or GitHub Copilot?

Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add OneWave-AI/claude-skills --skill inbound-lead-qualifier -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/inbound-lead-qualifier, .gemini/skills/inbound-lead-qualifier, .github/skills/inbound-lead-qualifier and .opencode/skills/inbound-lead-qualifier in your project.

What does Inbound Lead Qualifier need to run?

SKILL.md names no scripts, command-line tools or credentials: Inbound Lead Qualifier is instructions for the agent only.

Does Inbound Lead Qualifier access the network?

SKILL.md contains no URLs. Any network use would come from the scripts or tools the agent runs. This is read from the text; nothing was executed.

Is Inbound Lead Qualifier safe to install?

Our automated static check of SKILL.md found no risky patterns, such as piping downloads into a shell, reading credential files or hidden Unicode. It is not a guarantee. Review the folder before installing.

What licence does Inbound Lead Qualifier use?

Inbound Lead Qualifier is published under the MIT licence (the repository's licence). It allows redistribution, so the full SKILL.md is shown on this page.

How many tokens does Inbound Lead Qualifier use?

About 1.4k tokens (SKILL.md is roughly 5.5k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full.

What are the alternatives to Inbound Lead Qualifier?

Skills that share tags, products or a category with Inbound Lead Qualifier: Find Leads (eracle/OpenOutreach, 3.2k stars), 100m Leads (getagentseal/founder-playbook, 729 stars), Business Contact and Social Links Finder (browser-act/skills, 6.1k stars) and GitHub Lead Gen (Ducksss/codex-profiles, 180 stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Inbound Lead Qualifier?

OneWave-AI (a GitHub organization) maintains it in OneWave-AI/claude-skills, which has 336 GitHub stars. The repository holds 69 skills in this directory. The repository was last updated on October 2, 2026.

Source: OneWave-AI/claude-skills on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.