upskilllisted

# 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 scored jobs in `data/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 `data/jobs.json`. Take every entry `/rank` has scored, i.e. every one carrying a `rank_score`. 2. For each, note `title`, `company` and `rank_score`. `rank_score` is a 0–100 score where 100 = perfect fit. You will use it to weight gaps — a lower score means the role exposed more gaps. Where `rank_dimensions` is present it splits that score into `technical`, `experience`, `behavioral` and `career`, so a gap can be attributed rather than guessed at. 3. Read `.claude/skills/job-application-assistant/01-candidate-profile.md` to get the candidate's current skills and experience. 4. Check `upskill/` for th