> ## Documentation Index
> Fetch the complete documentation index at: https://www.opendirectory.dev/docs/llms.txt
> Use this file to discover all available pages before exploring further.
# linkedin-job-post-to-buyer-pain-map
> Turn LinkedIn job posts into an actionable buyer pain map with signal strength, urgency, and outreach angles for each account.
**Category:** Research · **Version:** `1.0.0` · **Author:** `ajaycodesitbetter` · **Compatibility:** All targets (claude, codex, opencode, gemini, anti-gravity, openclaw, hermes)
Turn LinkedIn job posts into an actionable buyer pain map with signal strength, urgency, and outreach angles for each account.
## Install
```bash theme={null}
npx "@opendirectory.dev/skills" install linkedin-job-post-to-buyer-pain-map --target claude
```
```bash theme={null}
npx skills add Varnan-Tech/opendirectory --skill linkedin-job-post-to-buyer-pain-map
```
```bash theme={null}
/plugin marketplace add Varnan-Tech/opendirectory
/plugin install opendirectory-gtm-skills@opendirectory-marketplace
```
1. Copy `https://github.com/Varnan-Tech/opendirectory/tree/main/skills/linkedin-job-post-to-buyer-pain-map` into [download-directory.github.io](https://download-directory.github.io/) to download the ZIP.
2. Open **Claude Desktop** -> **Customize** -> **Skills** -> **+** -> **Upload a skill** and drop the folder containing `SKILL.md`.
[**Install linkedin-job-post-to-buyer-pain-map in Manus AI**](https://manus.im/import-skills?githubUrl=https%3A%2F%2Fgithub.com%2FVarnan-Tech%2Fopendirectory%2Ftree%2Fmain%2Fskills%2Flinkedin-job-post-to-buyer-pain-map\&utm_source=opendirectory)
## What It Does
* Parses 1–15 pasted job descriptions and groups them by company
* Extracts team, seniority, responsibility emphasis, requirement language, and tool/stack hints from each post
* Infers primary and secondary operational pains with cited evidence from the job text
* Scores each account on 3 dimensions: signal strength (1–10), urgency (1–10), ICP fit (1–10)
* Computes an overall priority score (10–100) using a transparent weighted formula
* Determines buy-vs-build posture and company stage from hiring language
* Generates 1–3 actionable outreach angles per account with talk-track bullets
* Produces a structured handoff object ready for `outreach-sequence-builder` consumption
## Requirements
| Requirement | Purpose | How to Set Up |
| - | - | - |
| Gemini API key | Signal analysis, scoring, and pain inference | aistudio.google.com → Get API key |
## Setup
```bash theme={null}
cp .env.example .env
```
Fill in `GEMINI_API_KEY` (required).
No other dependencies. The skill runs entirely through agent instructions and Gemini API calls.
## How to Use
Analyze a single job post:
```
"Analyze this job post for buyer pain. My product is [X]. ICP: [Y]. Here's the post: [paste job description]"
```
Batch analysis of multiple posts:
```
"Build a pain map from these 5 job posts. Product: [X]. ICP: [Y]. Posts: [paste all posts]"
```
Focus on positioning angles:
```
"Decode these hiring descriptions for positioning angles. Focus on positioning. Product: [X]. ICP: [Y]. Posts: [paste posts]"
```
Handoff to outreach:
```
"Analyze these job posts and give me a handoff I can pass to outreach-sequence-builder"
```
## Input Format
Each job post should include at minimum:
* **Company name** and **job title** (required)
* **Job description text** — the full pasted content (required)
* Location, seniority, team/function, URL (optional — inferred if missing)
Posts can be pasted as plain text, numbered lists, or structured JSON objects.
## Output
For each company analyzed, the skill produces:
1. **Summary** — headline, overall score, score breakdown with explanations, stage guess, buy-vs-build posture
2. **Buyer Pain Map** — primary and secondary pains, each with label, description, and cited evidence
3. **Outreach Angles** — 1–3 angles with narrative and talk-track bullets
4. **Handoff** — structured block for outreach-sequence-builder (account summary, key pain, personas, tone)
Reports are saved to `docs/pain-maps/` as dated markdown files.
## Scoring Model
| Dimension | Weight | Measures |
| - | - | - |
| Signal Strength | 40% | Density and specificity of relevant hiring signals |
| Urgency | 30% | Time-sensitivity indicators in the job text |
| ICP Fit | 30% | Company profile match to user's ICP description |
**Overall Score** = `round((0.4 × signal + 0.3 × urgency + 0.3 × icp_fit) × 10)` → 10–100 scale.
See `references/scoring-rubric.md` for full scoring rules and modifiers.
## Plays Well With
| Skill | How |
| - | - |
| `outreach-sequence-builder` | Feed the handoff block as input context to generate a multi-channel outreach sequence |
| `noise-to-linkedin-carousel` | Use primary pains and evidence quotes as content source material |
| `reddit-icp-monitor` | Cross-reference pain themes from job posts with Reddit discussions |
## When NOT to Use
* Need to **find** companies hiring → use `linkedin-hiring-intent-scanner` or `yc-intent-radar-skill`
* Need to **write** outreach messages → use `outreach-sequence-builder`
* Need to **monitor** platforms for signals → use `reddit-icp-monitor` or `twitter-GTM-find-skill`
* Need contact data or email enrichment → this skill does not provide that
## Project Structure
```
linkedin-job-post-to-buyer-pain-map/
├── SKILL.md
├── README.md
├── .env.example
├── cover.png
├── evals/
│ └── evals.json
└── references/
├── scoring-rubric.md
└── examples.md
```
## License
MIT
This documentation is built and hosted on [Mintlify](https://mintlify.com), a developer documentation platform.