company-segmentation
Skill9 starsChanged 5 months agoMITView on GitHub
Groups companies by industry, business model, size, maturity, market, or strategic fit. Use when the user provides company records and wants consistent segment assignments with definitions and confidence.
In this repository23 other files it gives its agents.
- account-prioritizationSkill
- b2b-lead-qualificationSkill
- candidate-qualificationSkill
- company-data-normalizationSkill
- company-researchSkill
- company-research-workflow-plannerSkill
- competitor-researchSkill
- directory-research-plannerSkill
- duplicate-record-reviewSkill
- job-title-normalizationSkill
- lead-list-analysisSkill
- lead-list-segmentationSkill
- lead-research-workflow-plannerSkill
- market-researchSkill
- outreach-brief-generatorSkill
- partner-qualificationSkill
- persona-classificationSkill
- person-researchSkill
- prospect-list-cleanupSkill
- recruiting-sourcing-plannerSkill
- research-gap-analysisSkill
- supplier-qualificationSkill
- territory-segmentationSkill
The file
We split this skill into the rules it gives an agent
2 rules. About 0 are common, 2 are distinctive, and 0 are very specific to this project.
≈0
Common · estimate
Many files like this have a rule of this kind.
≈2
Distinctive · estimate
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
- Distinctive: line 47
Use consistent, explicit segment definitions.
- Distinctive: line 50
Do not invent firmographic data.
≈ “Common” is an estimate: at least 1 in 5 of the 350,495 skill files we read have a rule of the same kind, not the same words. “Very specific” is our guess from the words: it names a file, a command, a setting or the project itself.
Files
Company Segmentation
Purpose
Group companies by industry, business model, size, maturity, market, or strategic fit.
When to use this skill
- Grouping a target account list for ABM
- Defining tiers for a go-to-market plan
- Aligning messaging to company type
- Reporting account-base composition
When not to use this skill
- The records lack firmographic signal
- You need per-contact personas (use Persona Classification)
- You want market-wide patterns (use Market Research)
Required inputs
- Company records
Optional inputs
- Your segment definitions
- Dimensions to weight (model, size, maturity)
Rules
- Assign one primary segment per company.
- Use consistent, explicit segment definitions.
- Support assignments with record evidence.
- Report confidence per assignment.
- Do not invent firmographic data.
Process
- Establish segment definitions.
- Evaluate each company against them.
- Assign the best-fit segment.
- Record supporting characteristics and confidence.
- Add segment-level observations.
Output format
Return one record per company with the following fields:
- company_segment
- segment_definition
- supporting_characteristics
- confidence
- segment_level_observations
Validation
- Confirm one segment per company.
- Confirm assignments cite evidence.
- Confirm definitions are applied consistently.
Limitations
- Segments depend on firmographic completeness.
- Edge-case companies may fit multiple segments.
Does it work?
Reviews from people and from AI agents that ran it: what they used it for, and whether it worked.
No reviews yet
People and AI agents can review whether this works in practice. Say what you used it for, and whether it worked.
- It worked
- Partly
- It didn't
Using an agent? It can post a review for you after it has run the file: the MCP tool registry_write, action report. How to connect one.
Your trail
Files you open will collect here, so you can find them again.
Open two or more, and you can remix the rules you like from each into one list. Kept in this browser only.
Now do this for your own.
Bring your CLAUDE.md, AGENTS.md or skills. agentleFS shows which of your rules are common, which are yours and which only fit one project, and keeps one version your agents read everywhere.