ai-job-search: Command for Claude Code

/rank - Triage Scraped Jobs into a Ranked Shortlist

You are batch-scoring the jobs that /scrape has collected, so the user can decide where to spend /apply effort. /scrape finds and dedupes postings; /apply evaluates one at a time in depth. /rank is the bridge: it scores every new posting against the fit framework and returns a ranked shortlist.

/rank produces triage scores, not final evaluations. It scores from the posting text and the candidate profile only - no company research, no reviewer agent. /apply's Step 1 evaluation (which adds company research) remains authoritative and always re-runs when the user applies.

Follow these steps in order.

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Step 0: Parse Input

$ARGUMENTS may contain:

• Nothing → rank up to 10 jobs with status new in job_scraper/seen_jobs.json
• A focus area (e.g. /rank data science) → rank only jobs whose title or stored fit-notes match the focus
• --all → re-rank every job that has not been applied to, including previously ranked ones (useful after the profile changes)
• --limit <N> → maximum number of jobs to score this run (default 10)
• --top <N> → shortlist size (default 5)

--limit bounds the expensive fetch-and-score work; --top only bounds how many scored jobs appear in the shortlist. They are independent: jobs beyond --limit are deferred, not silently discarded.

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Step 1: Load State

Never read job_scraper/seen_jobs.json into the conversation. It holds every job the workspace has ever seen - most of it skipped - while a run only ever touches the handful of entries being scored, so a manual read costs the whole backlog on every run and grows for the life of the workspace. Selecting candidates is a query, so run the query:

python3 tools/rank_state.py candidates --limit 10          # add --all / --focus "<text>" per Step 0

It applies the status filter (new, or any status with --all), the tracker exclusion (any company+role already in job_search_tracker.csv is out of scope regardless of flags - it has been applied to or consciously tracked), the focus filter, and --limit, then prints one compact object per candidate (key, title, company, url, portal, deadline, posted_date) plus the counts: eligible, deferred (eligible beyond the limit, kept at their current status so a later run continues the backlog), excluded_by_tracker.