Agent skill
clean-job-titles
Standardize verbose LinkedIn job titles into clean, usable formats
Filed under LinkedIn and social.
From jurjen-gtm-engineer/gtmskills · 55 skill entries · 0 · pushed 2026-10-04
What it does when it runs
Standardize verbose LinkedIn job titles into clean, usable formats
Automated analysis of the skill and the 0 files bundled beside it. A skill’s own description is written to be selected by an agent, so it describes the job and not the dependencies.
- Keys and connectors you must supply
- None found.
- Hosts it reaches
- No third-party host appears in the skill or its bundled files.
- Tool permissions it declares
- No
allowed-toolsin the frontmatter. It only issues instructions, so there is nothing to bound. - Actions present in the files
- None. Instructions only.
Install it
View source on GitHub ↗git clone --depth 1 --filter=blob:none --sparse https://github.com/jurjen-gtm-engineer/gtmskills.git /tmp/gtmskills git -C /tmp/gtmskills sparse-checkout set "skills/clean-job-titles" mkdir -p ~/.claude/skills/clean-job-titles cp -R "/tmp/gtmskills/skills/clean-job-titles/." ~/.claude/skills/clean-job-titles/
Picked up without a restart. A project skill of the same name is shadowed by your personal one. For one repository only, swap ~/.claude/skills for .claude/skills. Claude Code docs ↗
The folder is the same in every client that implements the format — 46 of them — so if yours is not above, only the destination changes.
The skill
Source on GitHub ↗Reproduced in full from jurjen-gtm-engineer/gtmskills/blob/77dc0b3112dbf6cf906dfc3d526b6f7031bf964c/skills/clean-job-titles/SKILL.md, which is licensed MIT (repository). 416 words, 7 headings.
Clean Job Titles
You are standardizing verbose or complex job titles into clean, usable formats for personalization and segmentation.
Input
User provides:
- A raw job title (often from LinkedIn)
- Optionally: multiple titles to clean in batch
Process
-
Analyze Title Components
Prompt Pattern:
For this job title: "[RAW TITLE]" Simplify to standard form by: 1. Removing geographic qualifiers (", North America", ", EMEA") 2. Removing company-specific branding ("Chief Evangelist & ...") 3. Keeping the core role and seniority level 4. Standardizing common variations -
Output Format
Original: [Verbose title] Cleaned: [Standardized title] Components: - Seniority: [C-level / VP / Director / Manager / IC] - Function: [Sales / Marketing / Engineering / etc.] - Specialty: [If applicable] Segmentation Tags: - seniority:[level] - function:[area] - decision_maker:[yes/no]
Examples
Input: "Chief Evangelist & Head of Global Thought Leadership, North America"
Output:
Original: Chief Evangelist & Head of Global Thought Leadership, North America
Cleaned: Chief Evangelist
Components:
- Seniority: C-level equivalent
- Function: Marketing / Thought Leadership
- Specialty: Evangelism, Content
Segmentation Tags:
- seniority:executive
- function:marketing
- decision_maker:yes
Input: "Senior Director of Revenue Operations and Business Systems, Enterprise"
Output:
Original: Senior Director of Revenue Operations and Business Systems, Enterprise
Cleaned: Senior Director of Revenue Operations
Components:
- Seniority: Director
- Function: Revenue Operations
- Specialty: Business Systems
Segmentation Tags:
- seniority:director
- function:revops
- decision_maker:yes
Input: "VP, Head of Sales - SMB & Mid-Market (West Region)"
Output:
Original: VP, Head of Sales - SMB & Mid-Market (West Region)
Cleaned: VP of Sales
Components:
- Seniority: VP
- Function: Sales
- Specialty: SMB/Mid-Market
Segmentation Tags:
- seniority:vp
- function:sales
- decision_maker:yes
Batch Processing
For multiple titles:
| Original | Cleaned | Seniority | Function |
|----------|---------|-----------|----------|
| [Title 1] | [Clean 1] | [Level] | [Area] |
| [Title 2] | [Clean 2] | [Level] | [Area] |
Use Cases
- Email Personalization: Use cleaned title in "Hi [Name], as a [Clean Title]..."
- Segmentation: Group by seniority or function for campaigns
- Routing: Route leads to appropriate sales rep by title
- Scoring: Add points based on seniority level
Related Skills
/role-focus- Understand what the role focuses on/ideal-customer-profiles- Match cleaned titles to ICP
Examples are illustrative. Company names, prices and numbers in them are placeholders or may be out of date, so check the live source before you rely on any detail.
Other skills for the same job
Different authors, same problem. Matched on the words in the skill name, across every library in the catalogue except this one.
- playbook-job-posting-language by growthenginenowoslawski · 739
- linkedin-job-post-to-buyer-pain-map by Varnan-Tech · 672
- clean-data by explorium-ai · 156
- find-qualified-titles by getaero-io · 64
- clean-validate by Frontal-so · 6
- job-changes by Frontal-so · 6
- playbook-job-posting-language by automatewithuday · 1
- job-posting-intent by edupegoretti · 0
Need help setting it up?
This page tells you what clean-job-titles does and what it needs. Cheetah builds the agent setup it runs inside: data, CRM, sequencing and the guardrails.
Book a call →The directory stays free. There is nothing gated behind this.