upskill

# Upskill --- ## Overview `/upskill` analyses jobs you have tracked and your current profile to identify skill gaps, then produces a heatmap of those gaps and a learning plan with concrete, web-searched study resources and a recommended study order. ## Invocation - **`/upskill`** — aggregate mode: analyses all jobs in `job_search_tracker.csv`, merged with ranked postings (`rank_score >= 45`) from `job_scraper/seen_jobs.json` - **`/upskill <URL>`** — targeted mode: analyses a single job posting fetched from the URL --- ## Step 1: Detect Mode Check whether the user provided a URL argument: - If the invocation was `/upskill` with no argument → **aggregate mode** - If the invocation was `/upskill <URL>` → **targeted mode**, store the URL for Step 2 In targeted mode, derive a slug from the job title and company for the report filename (e.g. `guardsix-senior-ai-engineer`). You will fetch the posting in Step 2. ## Step 2: Load Data ### Aggregate mode 1. Read `job_search_tracker.csv`. Extract all rows. The columns are: `date, company, sector, role, role_type, channel, status, contact_person, fit_rating, notes, cv_file, cover_letter_file, source` 2. For each row, note the `role`, `company`, and `fit_rating`. The `fit_rating` column is a 0–100 score where 100 = perfect fit. You will use it to weight gaps — a lower fit rating means the role exposed more gaps. 3. Read `job_scraper/seen_jobs.json`. Keep entries with `"status": "ranked"` and `rank_score >= 45` — the Moderate...