Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx skills add glebis/claude-skills --skill job-babysittergit clone --depth 1 https://github.com/glebis/claude-skillsWrote 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/glebis/claude-skills/job-babysitter)<a href="https://agentmods.dev/skills/glebis/claude-skills/job-babysitter"><img src="https://agentmods.dev/badge/skills/glebis/claude-skills/job-babysitter/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/glebis/claude-skills/job-babysitter"><img src="https://agentmods.dev/badge/skills/glebis/claude-skills/job-babysitter.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector warn
SkillSpector: 1 finding, up to medium
These are SkillSpector’s own severities. On a checked sample its high-severity flags on skills were ~96% false positives — a documented command, a public API, a “never do X” rule — so we show them as a caution to read, not a verdict. Why →
- medium Excessive Agency · line 80 Skill enables autonomous high-impact decisions without human-in-the-loop verification. Critical operations (destructive commands, financial transactions, data deletion) should require explicit user confirmation.Fix: Add human-in-the-loop confirmation for destructive, irreversible, or high-impact operations. Never auto-execute commands that modify files, send data, or alter system state.
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 | $0.00147 | $0.01358 |
| Opus 5 | $0.00073 | $0.00679 |
| Sonnet 5 | $0.00029 | $0.00272 |
| Haiku 4.5 | $0.00015 | $0.00136 |
Grade A, and why
job-babysitter 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 8d 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 — 107 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Job Babysitter
Purpose
Stop manually polling long-running background jobs. Instead of dozens-to-hundreds of
ls -lh / ps checks while guessing at completion, start one background watcher that
detects the terminal state via plateau heuristics, then routes a verdict — done,
needs-attention, or blocked — with the exact next command.
A night-shift nurse for background jobs: it checks vitals on a schedule and escalates only when something is actually wrong.
When to use
Use when a job will run long enough that babysitting it by hand wastes attention:
- Media encodes / transcodes (ffmpeg, video-transcribe, audio extraction)
- Embedding or vector-DB builds (qmd embed, index builds)
- Batch agent / LLM pipelines run in the background
- Browser / scrape daemons (real-browser, agent-browser) prone to hanging
Do NOT use for jobs that finish in seconds, or where a single Bash call already
returns the result.
Core principle: stay thin, lean on the harness
This skill orchestrates Claude Code's own primitives — do not reimplement them:
- Start the watcher with
run_in_background: true. When it exits, the harness re-invokes the agent automatically — no manual polling loop needed. - The watcher (
scripts/watch_job.py) owns the deterministic part: poll with backoff, detect plateau, distinguish done from stuck, emit a verdict JSON. - The skill's value is the per-job-type heuristics, the safe-recovery playbook,
and notification routing — all in
references/playbook.md.
Workflow
1. Identify the job's signals
Determine what can be watched, in order of reliability:
- PID — the process ID (most reliable completion signal). Get it from the job's
launch,
pgrep, orps. - Output file — a file that grows as the job progresses (e.g. ffmpeg target).
- Log file — a log that gets appended (e.g. an embed progress log).
Read references/playbook.md § "Completion heuristics by job type" to pick flags for
the specific job type (ffmpeg, embed, batch, browser).
What ships with it
2 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
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.
- 8d ago First seen · 107 lines · 147 tokens per session scan A be45a1ed8c1c
job-babysitter is a skill published in the GitHub repository glebis/claude-skills (375 stars, last pushed 10d ago), licensed MIT. It adds 147 tokens to every session and 1,358 once invoked, about $0.0007 per session on Opus 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 2026-09-03.
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