classify-leads
Skill16 starsChanged 9 months agoMITView on GitHub
Classify leads using LLM for complex distinctions like product SaaS vs agencies. Use when user asks to classify leads, filter leads by type, or categorize businesses.
- Reads credentials
3 other projects use a version of this, 3 of them edited.
Adopted by
Most recently taken up by
- MohamedEssam0-0/claude-skillsedited, first seen Oct 11, 2026
- phuongdo/claude-skillsedited, first seen Feb 17, 2026
- nickjwells/skills-workspaceedited, first seen Feb 1, 2026
Other versions3 projects use a version of this.
Word for word · 0
None found.
Edited · 3
- nickjwells/skills-workspace★ 2893% same
- MohamedEssam0-0/claude-skills★ 093% same
- phuongdo/claude-skills★ 093% same
Wrote their own version · 0
None found.
How matches are found. Word for word: the exact same text. Edited: shares passages with this file (“99% same” means 99% of its five-word phrases also appear here; 10% or more counts). Their own version: similar meaning, or, weakest, the same name. We can’t tell which project had it first. Projects are counted among the 200 most-starred candidates, and mentions are links to the repository we found, up to 50 per site, so both counts are a floor.
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The file
We split this skill into the rules it gives an agent
2 rules. 2 are common, 0 are distinctive, and 0 are very specific to this project.
2
Common
Most of the 3 edited versions we read keep these.
0
Distinctive
This author's own choices. Worth a look.
0
Very specific
Tied to their project's names, files or tools. Probably skip.
- Common
- Distinctive
- Very specific
- Common: line 15
NOT for simple categories (dentists, realtors)
- Common: line 33
Default: includes "unclear" classifications (medium confidence)
“Common” is measured: kept by at least 6 in 10 of the 3 edited versions of this file we could read. “Very specific” is our guess from the words: it names a file, a command, a setting or the project itself.
Files
LLM Lead Classification
Goal
Classify leads using Claude for complex distinctions that keyword matching can't handle.
When to Use
- Product SaaS vs IT consulting agencies
- High-ticket vs low-ticket businesses
- Subscription vs one-time payment models
- NOT for simple categories (dentists, realtors)
Scripts
./scripts/classify_leads_llm.py- Main classification script./scripts/update_sheet.py- Update sheets./scripts/read_sheet.py- Read from sheets
Usage
python3 ./scripts/classify_leads_llm.py .tmp/leads.json \
--classification_type product_saas \
--output .tmp/classified_leads.jsonPerformance
- ~2 minutes for 3,000 leads
- ~$0.30 per 1,000 leads
- Default: includes "unclear" classifications (medium confidence)
Classification Types
product_saas: Product companies vs service/consulting- Custom types can be added
Output
JSON file with classification added to each lead record.
Schema
Inputs
| Name | Type | Required | Description |
leads_file | file_path | Yes | JSON file with lead data |
classification_type | string | Yes | Classification type (e.g., 'product_saas') |
output | file_path | No | Output JSON file path |
Outputs
| Name | Type | Description |
classified_file | file_path | JSON file with classification added to each lead |
Credentials
| Name | Source |
ANTHROPIC_API_KEY | .env |
Composable With
Skills that chain well with this one: scrape-leads, gmaps-leads, instantly-campaigns
Cost
$0.30 per 1,000 leads
Does it work?
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