datachain-jobs

You are now loaded with the datachain-jobs skill. Maintain a jobs analytics file at `dc-knowledge/jobs/index.md`. Follow the 3-step flow below exactly. --- ## Step 1 — Check Staleness ``` python3 {skill_dir}/scripts/jobs.py --plan ``` - If `"studio_available": false` → report the `error` message and stop. - If `"up_to_date": true` → skip to Step 3. - If `"up_to_date": false` → continue to Step 2. --- ## Step 2 — Fetch & Write ``` python3 {skill_dir}/scripts/jobs.py --fetch [--days N] [--limit N] [--enrich] ``` - Use `--days N` from the user's request if stated (e.g. "last 7 days" → `--days 7`). Default: `--days 30`. - Add `--enrich` only when the question requires duration, workers, or cluster data AND `enriched: false` in an existing index — tell the user it makes one API call per terminal job. - If the script fails → report the error and stop. Write `dc-knowledge/jobs/index.md` using EXACTLY this format: ```markdown --- generated: <generated from script output> days_covered: <days_covered> total_jobs: <filtered_count> failed_count: <failed_count> complete_count: <complete_count> running_count: <running_count> other_count: <other_count> enriched: <true|false> duration_note: "Wall-clock duration (submit→finish). Null when enriched=false or job still running." truncated: <true|false> --- ## Clusters | Name | Cloud | Max Workers | Default | |------|-------|-------------|---------| | <name> | <cloud_provider> | <max_workers> | <yes if is_default else no> | ## Jobs ...