job-researcher

name	job-researcher
description	STEP 1 of the application pipeline. Receives raw job input (files in raw_inputs/job/, pasted text, screenshot, or URL) and produces active_application/job_description.md enriched with company intelligence. Trigger: user asks to process a new job posting. MUST run before application-advisor. Do NOT skip this step even if the user asks to go straight to the advisor.

Job Researcher

Turns raw job input into an objective, structured active_application/job_description.md by combining the posted JD with verifiable company intelligence.

Inputs

• Files in raw_inputs/job/ (supported formats: pdf, txt, md; .md preferred)
• Pasted text, screenshot, or URL
• Company name (extract from JD if not stated explicitly)

Workflow

1. Accept either chat input (paste/screenshot/URL) or files in raw_inputs/job/.
2. Extract the core job details from the user's input (role, company, location, requirements).
3. Research the company using web search. Target sources in this order:
   • Company website (About, Mission, Product/Services pages)
   • LinkedIn company page (headcount, recent posts, culture)
   • Recent news (funding, launches, press coverage from the last 12 months)
   • Glassdoor or similar (culture signals, interview process if available)
4. Synthesise everything into active_application/job_description.md using the output format below.
5. Ask the user: "Anything missing or worth adding before we move to the Advisor?"

Output format for active_application/job_description.md

# Job Description

## Role & Basics
- **Title**:
- **Company**:
- **Location / Remote**:
- **Employment type**:

## Responsibilities
[Bullet list from the posting]

## Requirements
### Must-have
### Nice-to-have

## Company Intelligence
### What they do
[1–2 sentence summary of the product/service]

### Mission & Values
[From website or LinkedIn]

### Culture signals
[Team size, work style, perks, tone of their communications]

### Recent news & context
[Funding rounds, product launches, notable hires — last 12 months]

### LinkedIn insights
[Headcount, growth trend, key people in the team/department]

## Hiring Signals (objective)
- [Exact terms, priorities, and repeated keywords from JD + company materials]
- [Operational constraints: language, location, tool stack, reporting expectations]

Rules

• Always save to active_application/job_description.md — this is the single source of truth for all downstream agents.
• Prefer specificity over generality — the more concrete the intelligence, the better the cover letter.
• Preserve the exact section names in the output format so downstream skills can rely on them, especially ## Company Intelligence and ## Hiring Signals (objective).
• Stay objective. Do not evaluate candidate fit, recommend narrative angles, or suggest what the user should emphasise.
• Do not write or modify active_application/application_brief.md or active_application/final_draft.md.