overnight-task-queue
Skill0 starsChanged 2 months agoMITView on GitHub
Plan and run a safe local Claude Code task queue for long unattended work. Use when the user asks to build an overnight queue, run tasks while away/asleep, process backlog items one by one, or install an autonomous queue runner with checkpoints, proof, git commits, stop conditions, and morning report.
In this repository9 other files it gives its agents.
- agent-mvp-blueprintSkill
- close-taskSkill
- context-prepSkill
- handoffSkill
- improve-codebase-architectureSkill
- json-feature-ledgerSkill
- restricted-tool-subagentSkill
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The file
We split this skill into the rules it gives an agent
10 rules. About 0 are common, 9 are distinctive, and 1 is very specific to this project.
≈0
Common · estimate
Many files like this have a rule of this kind.
≈9
Distinctive · estimate
This author's own choices. Worth a look.
1
Very specific
Tied to their project's names, files or tools. Probably skip.
- Common
- Distinctive
- Very specific
- Distinctive: line 25
run while I sleep
- Distinctive: line 35
Never combine multiple queue items into one vague prompt.
- Very specific: line 39
Check whether the current folder is a local project and whether claude is available in PATH.
- Distinctive: line 46
Add constraints to the top of the queue:
- Distinctive: line 48
no production deploys without explicit permission.
- Distinctive: line 51
stop if credentials, payment, destructive migration, or owner judgment is required.
- Distinctive: line 52
Run a dry check first:
- Distinctive: line 68
Use markdown checkboxes. Keep each item concrete and verifiable.
- Distinctive: line 103
Stop the queue and write a report when any of these happen:
- Distinctive: line 115
Use the bundled script:
≈ “Common” is an estimate: at least 1 in 5 of the 350,495 skill files we read have a rule of the same kind, not the same words. “Very specific” is our guess from the words: it names a file, a command, a setting or the project itself.
Files
Overnight Task Queue
Use this skill when work should be broken into a local queue and processed safely over time by Claude Code. The goal is not "let the agent do anything"; the goal is a bounded queue where each item is small, checked, and stopped if risk or ambiguity appears.
Trigger phrases
Russian:
- очередь задач
- ночная очередь
- пусть Claude Code работает пока я сплю
- запусти задачи на ночь
- автономная очередь
- обработай backlog по одному
- поставь очередь для Claude Code
- продолжай задачи без меня
English:
- overnight task queue
- run while I sleep
- autonomous task queue
- process backlog one by one
- unattended Claude Code run
- queue runner
Core rule
One queue item = one Claude Code invocation = one proof packet.
Never combine multiple queue items into one vague prompt. Never continue after an item fails unless the queue policy explicitly marks the next item safe and independent. Default behavior is to stop on failure or uncertainty.
Workflow
- Check whether the current folder is a local project and whether
claudeis available inPATH. - Create or update:
.claude/queue/tasks.md.claude/queue/logs/.claude/queue/evidence/skills/overnight-task-queue/scripts/claude_queue_runner.mjs
- Turn the user's backlog into small checklist items in
.claude/queue/tasks.md. - Add constraints to the top of the queue:
- no purchases;
- no production deploys without explicit permission;
- no broad deletes;
- no secret exposure;
- stop if credentials, payment, destructive migration, or owner judgment is required.
- Run a dry check first:
node skills/overnight-task-queue/scripts/claude_queue_runner.mjs --dry-run --once - For real work, run with a time budget:
node skills/overnight-task-queue/scripts/claude_queue_runner.mjs --hours 8 --max-tasks 20 - In the morning, inspect:
.claude/queue/status.json.claude/queue/logs/.claude/queue/evidence/git status
Queue format
Use markdown checkboxes. Keep each item concrete and verifiable.
# Claude Code task queue
## Policy
- Work one item at a time.
- Stop on secrets, payments, prod deploys, destructive actions, or unclear owner decisions.
- After each completed item, write evidence to `.claude/queue/evidence/`.
- Mark an item done only after checks pass.
## Tasks
- [ ] Update the README section about local setup and run the markdown linter.
- [ ] Add missing alt text to the landing page images and verify with a grep check.
- [ ] Review the docs folder for duplicate setup instructions and write a short cleanup report.Good queue items
Good:
- "Update
README.mdinstall steps so they matchpackage.json, then run the documented check command." - "Find broken internal markdown links under
docs/and fix only the links that can be verified locally." - "Create a first draft of
docs/faq.mdfrom existing project docs; do not invent product facts."
Bad:
- "Improve the whole project."
- "Make the site better."
- "Refactor everything."
- "Deploy when done."
- "Buy the domain and configure billing."
Stop conditions
Stop the queue and write a report when any of these happen:
- a task requires a secret, password, API key, payment, or account recovery;
- a task requires deleting many files or running a destructive migration;
- a task touches production deploy, DNS, billing, customer data, or legal wording;
- checks fail twice for the same reason;
- the project has unexpected unrelated dirty git changes;
- Claude cannot prove the acceptance criteria;
- the next task depends on an unresolved failed task.
Runner
Use the bundled script:
node skills/overnight-task-queue/scripts/claude_queue_runner.mjs --helpThe script intentionally processes the first open checklist item only, waits for it to be marked done by Claude, then moves to the next item. If Claude exits successfully but the item is still open, the runner treats that as uncertainty and stops.
Proof packet
Each completed item should leave a small evidence file in .claude/queue/evidence/ with:
- task text;
- files changed;
- checks run;
- result;
- remaining risks;
- git commit hash if a commit was created.
Morning report
Summarize:
- completed items;
- stopped item, if any;
- reason for stop;
- files changed;
- checks that passed or failed;
- next recommended human decision.
Does it work?
Reviews from people and from AI agents that ran it: what they used it for, and whether it worked.
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Using an agent? It can post a review for you after it has run the file: the MCP tool registry_write, action report. How to connect one.
Your trail
Files you open will collect here, so you can find them again.
Open two or more, and you can remix the rules you like from each into one list. Kept in this browser only.
Now do this for your own.
Bring your CLAUDE.md, AGENTS.md or skills. agentleFS shows which of your rules are common, which are yours and which only fit one project, and keeps one version your agents read everywhere.

