feat: add /rank command to triage scraped jobs into a ranked shortlist (#43)

/scrape finds and dedupes postings; /apply evaluates one at a time in
depth. Nothing connects the two ends: after a scrape returns 20 jobs, the
user eyeballs a table to decide where to spend /apply effort. /rank is the
bridge: batch-score every new posting against the fit framework and return
a ranked shortlist.

How it works:

- Selects jobs with status "new" from job_scraper/seen_jobs.json (--all
  re-ranks everything unapplied; a focus argument filters), excluding
  anything already in job_search_tracker.csv
- Dispatches parallel general-purpose agents (~5 jobs each) that WebFetch
  each posting and score the five dimensions from 04-job-evaluation.md.
  The rubric (skill match areas, career goals, deal-breakers) is passed
  inline per the same token-efficiency rules /apply uses; agents score
  only from actually fetched content and mark dead postings expired,
  never guessing from a title
- Triage depth by design: posting text vs. profile only - no company
  research, no salary lookups. /apply's Step 1 evaluation stays
  authoritative and always re-runs on handoff
- Aggregates with the framework's 30/25/15/30 weighting and verdict
  bands; location deal-breakers veto regardless of score; deadlines
  within 7 days get urgency flags and win ties
- Updates seen_jobs.json additively (status "ranked"/"expired" plus
  rank_score/rank_verdict/rank_date) so /scrape dedup keeps working;
  the tracker is read-only. Re-running is idempotent

Integration: job-scraper SKILL.md documents the new status values and
suggests /rank after large scrape batches; README (commands list, file
tree, quick-start step 4).

.claude/skills/job-scraper/SKILL.md

@@ -75,7 +75,7 @@ For each new job, do a rapid fit check (NOT the full evaluation from `04-job-eva
       "url": "...",
       "first_seen": "YYYY-MM-DD",
       "fit": "high/medium/low",
-      "status": "new/skipped/evaluated"
+      "status": "new/skipped/evaluated/ranked/expired"
     }
   }
 }
@@ -107,6 +107,8 @@ After presenting, ask:
 
 If the user picks a number, invoke the **job-application-assistant** skill workflow (fit evaluation first, then CV + cover letter if approved).
 
+If the run found many new jobs (roughly 8+), also suggest `/rank` - it batch-scores all new postings against the full fit framework and returns a ranked shortlist, which beats eyeballing a long table. (`/rank` sets the `ranked` and `expired` status values in `seen_jobs.json`; treat both as already-seen for dedup purposes.)
+
 ### Step 6: Update Tracker (Optional)
 
 If the user decides to apply to any job, add a row to `job_search_tracker.csv`.