Getting it into your agent
It runs from inside its repository, so the clone comes first — what it calls does not travel with the file alone.
git clone --depth 1 https://github.com/AkbarDevop/ai-job-agentnpx agentmods add skills/akbardevop/ai-job-agent/job-trackWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/skills/akbardevop/ai-job-agent/job-track)<a href="https://agentmods.dev/skills/akbardevop/ai-job-agent/job-track"><img src="https://agentmods.dev/badge/skills/akbardevop/ai-job-agent/job-track/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/akbardevop/ai-job-agent/job-track"><img src="https://agentmods.dev/badge/skills/akbardevop/ai-job-agent/job-track.svg" alt="Reviewed on agentmods" width="80" height="20"></a>What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00103 | $0.00796 |
| Opus 5.5 | $0.00041 | $0.00318 |
| Sonnet 5.5 | $0.00021 | $0.00159 |
| Haiku 4.5 | $0.00010 | $0.00080 |
Grade A, and why
job-track scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 1mo ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
How it starts
The opening of the file, as written. The whole thing — 88 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Job Track
Reads the local CSV tracker and renders it as a markdown table grouped by status. Optionally pushes new rows to the configured Google Sheet.
Repo location
Same resolution as /job-apply: $AI_JOB_AGENT_ROOT → ~/.claude/skills/ai-job-agent/ → REPO_PATH marker file → ~/ai-job-agent/.
Tracker location
$LOCAL_TRACKER env var, else $AI_JOB_AGENT_ROOT/application-tracker.csv.
Workflow
1. Read the CSV
Columns (per templates/tracker.template.csv):
date, company, role, status, location, source, applied_by, url, notes, contact, compensation, days_since, key
If the file doesn't exist, tell the user to run bash setup.sh (which creates it from the template) and stop.
2. Summary table (counts by status)
| Status | Count |
|---|---|
| 📄 applied | N |
| 📬 submitted | N |
| 💼 interview | N |
| 🎯 offer | N |
| ❌ rejected | N |
| 🚫 blocked | N |
| 🚪 withdrawn | N |
| total | N |
Use whatever statuses are actually present in the CSV — don't hardcode the list. Apply this emoji mapping for known statuses (case-insensitive match); unknown statuses get no emoji. If a status is missing from the CSV entirely, don't include that row.
3. Recent activity table (last 10 rows by date)
| Date | Company | Role | Status | Platform | URL |
|---|
Truncate URL to domain only (e.g., linkedin.com/jobs/view/…) to keep the table readable.
4. If argument is sync
Check SPREADSHEET_ID is set (env var or not YOUR_SHEET_ID in the script). If missing, tell the user to either export the env var or edit scripts/google-sheet-sync.py, then stop.
Otherwise run:
cd "$AI_JOB_AGENT_ROOT"
python3 scripts/google-sheet-sync.py "$LOCAL_TRACKER"
Parse the JSON output (it returns updatedRange, updatedRows, etc.) and render a single-row result table:
| Field | Value |
|---|---|
| Sheet | $SPREADSHEET_ID / $SHEET_NAME |
| Rows appended | N |
| Range updated | e.g. 'Job Tracker'!A47:M51 |
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 1mo ago First seen · 88 lines · 103 tokens per session scan A 9b0f6bef4013
job-track is a skill published in the GitHub repository AkbarDevop/ai-job-agent (67 stars, last pushed 6mo ago), licensed MIT. It adds 103 tokens to every session and 796 once invoked, about $0.0004 per session on Opus 5.5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.
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