Inputs
Provide these when prompted. The skill asks for anything missing before it runs.
Required
- A lead list
Optional
- Segmentation dimensions (industry, size, region, fit)
- A priority rule
- Target segment count
Agent Skill
Lead List Segmentation
Divide a lead list into useful commercial segments with criteria, size, and priority.
Version 1.0 Updated June 2026 SKILL.md MIT 6 min read
Overview
What this skill does
A single big lead list gets treated as one undifferentiated blob, so messaging and effort are spread evenly across leads that deserve very different attention.
This skill divides the list into commercial segments, defines the criteria for each, reports segment sizes, recommends how to treat each segment, and assigns priority — turning a flat list into a sequenced plan.
When to use it
Best used for
- Splitting one list into messaging-ready segments
- Prioritizing where to spend outreach effort
- Tailoring campaigns per segment
- Reporting list composition to stakeholders
Know the limits
When not to use this skill
- The list has no fields to segment on
- You need per-record scoring (use Lead Qualification)
- The list is too small to segment meaningfully
Outputs
One record per segment with a consistent, inspectable schema.
segment_nameA clear name for the segment.
segment_criteriaThe rule defining membership.
included_recordsWhich records fall in the segment.
segment_sizeCount of records in the segment.
recommended_treatmentHow to approach the segment.
priorityRelative priority of the segment.
Example
Example
A list split into two segments.
Input
List: 120 leads with industry + size + fit score.
Goal: Prioritize outreach.Output
segment_name: High-fit mid-market
segment_criteria: fit_score >= 80 AND 50-500 employees
segment_size: 34
recommended_treatment: 1:1 personalized outreach
priority: 1
---
segment_name: Low-fit SMB
segment_criteria: fit_score < 50
segment_size: 41
recommended_treatment: Nurture or deprioritize
priority: 3The flat list becomes a sequenced plan: 34 high-fit accounts for 1:1 outreach first, low-fit SMBs nurtured later.
Setup
How to use the skill
General steps first, then notes for specific clients where verified.
- 1Download the file using the button below, or copy the Markdown.
- 2Place it in a directory named after the skill (e.g. skill-name/).
- 3Make sure the filename stays exactly SKILL.md.
- 4Add any references or assets included with the package.
- 5Load the skill into a compatible agent and provide the required inputs.
Claude Code
- 1Create a folder for the skill and save SKILL.md inside it.
- 2Place the folder where your project's skills are discovered.
- 3Reference the skill when you want it applied to your data.
Other compatible clients
- 1Confirm the client supports the open Agent Skills format.
- 2Load the SKILL.md file as instructed by that client.
- 3If skills are not auto-loaded, paste the Markdown as instructions.
Source
Full SKILL.md source
Read the rendered skill or copy the complete Markdown. The download is generated from this exact source.
Version 1.0 SKILL.md ~2 KB MIT
Lead List Segmentation
Purpose
Divide a lead list into useful commercial segments with criteria, size, and priority.
When to use this skill
- Splitting one list into messaging-ready segments
- Prioritizing where to spend outreach effort
- Tailoring campaigns per segment
- Reporting list composition to stakeholders
When not to use this skill
- The list has no fields to segment on
- You need per-record scoring (use Lead Qualification)
- The list is too small to segment meaningfully
Required inputs
- A lead list
Optional inputs
- Segmentation dimensions (industry, size, region, fit)
- A priority rule
- Target segment count
Rules
- Define explicit, non-overlapping criteria per segment.
- Report accurate segment sizes.
- Base segments on supplied fields only.
- Recommend treatment proportional to value.
- Make priorities consistent and justified.
Process
- Profile the list fields.
- Choose segmentation dimensions.
- Define segment criteria.
- Assign records and count sizes.
- Recommend treatment and priority.
Output format
Return one record per segment with the following fields:
- segment_name
- segment_criteria
- included_records
- segment_size
- recommended_treatment
- priority
Validation
- Confirm segment criteria do not overlap.
- Confirm sizes sum sensibly to the list.
- Confirm priorities follow the value logic.
Limitations
- Segment quality depends on field completeness.
- Static segments need refreshing as the list grows.
Before you rely on it
Safety and limitations
- Segment quality depends on field completeness.
- Static segments need refreshing as the list grows.
- Review the output before acting on it.
- Do not upload confidential datasets to an external model without authorization.
- Outputs depend on the model and the source data and are not guaranteed to be accurate.
History
Changelog
- v1.0June 2026
- Initial release.
Questions
Agent Skill FAQ
What does it base the segments on?
The attributes present in your list — industry, size, role, region, or fit — with each segment given a definition, size, and priority so you know which to work first.
How many segments will it create?
As many as the data supports, or a target count you specify. It avoids tiny, overlapping segments.
Do I need ProfileSpider to use this skill?
No. The skill works on any compatible data. ProfileSpider is one convenient way to produce that structured input.
Does running this skill send data to ProfileSpider?
No. Downloading or copying the file does not send any data to ProfileSpider. What happens afterward depends on the AI service you load it into.
Are Agent Skills the same as prompts?
No. A skill is a structured, reusable package — task, inputs, rules, process, and output format — so the workflow runs consistently and can be shared, versioned, and edited.