linkedin-job-post-to-buyer-pain-map
linkedin-job-post-to-buyer-pain-map is a Prospecting & lead research skill for AI agents, published by Varnan-Tech in the opendirectory repository on GitHub. Skillspace rates linkedin-job-post-to-buyer-pain-map B (81/100) and it passed the safety scan; the rating is based on static analysis only.
Takes pasted LinkedIn job posts or hiring descriptions and converts them into a structured buyer pain map with inferred pains, capability gaps, buy-vs-build signal, account priority scores, and suggested outreach angles. Use when asked to analyze hiring posts, decode job descriptions for buyer intent, build a pain map from job listings, extract GTM signals from hiring activity, or prioritize accounts based on hiring data. Trigger when a user says "analyze these job posts", "what pain does this hiring signal", "build a pain map from these listings", "decode this job description", or "score these accounts from their hiring".
- Grade
- B
- Quality
- 81 / 100
- Safety
- Passed
- GitHub stars
- 546
Unproven: rated by static analysis only, not yet compared head-to-head.
Our two independent classifiers differ on this skill's category, so treat the placement as provisional.
This rating describes the version of the repository we crawled; it may have changed since, so go by its current files.
Our review
- Architecture
- 100 / 100
- Maturity
- Structured: ships references or scripts
- Security scan
- No issues found
- License
- MIT
- Adoption
- Adopted by 0 other repositories, in 1 collections
- Scope
- Portable: works in any project. Generic method to turn job posts into a buyer pain map.
Not checked yet
- Not judged on the rubric yet (not a contender in its category)
- No blind task eval yet
- Sibling files (scripts, references) not fetched; security scan covers SKILL.md only
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