| name | job-status |
| description | Batch-update application statuses (Rejected / Interview / Offer / Withdrawn / …) in both the local CSV and the Google Sheet, with a before/after diff and confirmation gate. Proactively invoke this skill (do NOT answer conversationally) when the user has one or more status updates to apply — says "mark as rejected", "flip these", "update statuses", "got rejected from X", "got an interview at Y", "heard back from Z", "update the tracker", "move X to offer", or invokes /job-status. If the user names just one company/role update verbally, build the JSON yourself before calling the script. |
| argument-hint | <updates.json> (JSON file with array of {sheet_row, company, role, location, status, note}) |
| allowed-tools | ["Bash","Read","Write"] |
Job Status
Wraps scripts/tracker-status-update.py. Shows a diff of what will change, asks for approval, then applies.
Repo location
Same as /job-apply: $AI_JOB_AGENT_ROOT → ~/.claude/skills/ai-job-agent/ → REPO_PATH marker file → ~/ai-job-agent/.
Input JSON format
Each item in the array:
{
"sheet_row": 42,
"company": "Acme Corp",
"role": "Software Intern",
"location": "Remote",
"status": "Rejected",
"note": "Auto-rejection email received 2026-04-22"
}
sheet_row is required for the Google Sheet update (1-indexed, matching the sheet's row number — row 1 is the header, so data starts at row 2).company + role (+ optional location) are used to match the local CSV row.status is free-text, but the sheet filter typically expects: Applied, Interview, Offer, Rejected, Withdrawn.note appends to existing notes; skipped if empty or already present.
Workflow
1. Load and validate
Read $ARGUMENTS (path to JSON file). Parse. If invalid JSON or missing required fields, stop with an error message listing which rows are malformed.
2. Fetch current state
Render a before/after table showing what will change. For the sheet side, the script itself fetches rows internally — you can surface what the user supplied and let the script fill in the rest:
| # | Sheet row | Company | Role | Status → new | Note appended |
|---|
| 1 | 42 | Acme Corp | Software Intern | 📄 applied → ❌ Rejected | "Auto-rejection email received 2026-04-22" |
| 2 | 58 | Beta Inc | EE Intern | 📬 submitted → 💼 Interview | "Phone screen scheduled for Thu" |
Apply the same emoji mapping as /job-track (📄 applied · 📬 submitted · 💼 interview · 🎯 offer · ❌ rejected · 🚫 blocked · 🚪 withdrawn). Unknown statuses get no emoji.
If you want the current statuses for real, read them from the local CSV (cheap, no network) — the user can spot obvious mistakes before the sheet mutation.
3. Confirm
Ask: "Apply these N updates to Google Sheet + local CSV? (y/n)"
Stop if no.
4. Run
cd "$AI_JOB_AGENT_ROOT"
python3 scripts/tracker-status-update.py "$JSON_PATH"
Parse the script's JSON output:
{
"sheet_rows_updated": [42, 58, 101],
"local_rows_changed": 2
}
5. Render result
| Field | Value |
|---|
| Sheet rows updated | N |
| Local CSV rows changed | N |
| Sheet rows | 42, 58, 101 |
| Local tracker | $LOCAL_TRACKER |
6. Flag mismatches
If sheet_rows_updated count ≠ input count: the script doesn't apply updates missing sheet_row. Flag those.
If local_rows_changed < input count: some updates didn't match a local CSV row (fuzzy match is company+role+location, case-insensitive, exact). List the unmatched so the user can add them manually or correct the JSON.
Prerequisites
gcloud auth application-default loginSPREADSHEET_ID and SHEET_NAME env vars set (or edited in the script)- Local tracker at
$LOCAL_TRACKER (defaults to application-tracker.csv)
