science-daemon-ops
Skill1 starsChanged 40 days agoNo licenceView on GitHub
Diagnose and maintain a self-hosted Claude Science daemon on the user's own machine — the app process itself, not the science it runs. Use this whenever the user reports that the app is crashing, restarting or relaunching itself, hanging, feeling slow, losing its session, showing "session expired", refusing connections, or emitting repeated `channel N: open failed: connect failed: Connection refused` lines from ssh; also for routine upkeep — daemon health, resident-memory growth, database bloat or VACUUM, orphaned workspace directories, un-adopted data warnings, and correct SSH port forwarding for remote access. Trigger it even when the user never says "daemon" and even when they are sure the app crashed: most reported crashes are graceful self-update restarts, and this skill tells those apart from real faults using the daemon's own logs. Not for analysis work done inside the app, and not for remote cluster or SLURM job failures (that is remote-compute-ssh).
- Reads credentials
In this repository23 other files it gives its agents.
- bio-diagramSkill
- claim-gateSkill
- cli-subagentsSkill
- cluster-autoscoutSkill
- cluster-rulesSkill
- codex-offloadSkill
- deslopSkill
- doc-build-gateSkill
- experiment-preflight-singlecellSkill
- experiment-preflightSkill
- fail-loud-pipelinesSkill
- gwas-analysisSkill
- job-watchSkill
- lab-notebookSkill
- paper-outlineSkill
- phase-delegationSkill
- reproducibleSkill
- rigor-reviewSkill
- run-status-boardSkill
- session-handoffSkill
- standing-instructionsSkill
- variant-annotationSkill
- variant-callingSkill
The file
We split this skill into the rules it gives an agent
5 rules. About 0 are common, 2 are distinctive, and 3 are very specific to this project.
≈0
Common · estimate
Many files like this have a rule of this kind.
≈2
Distinctive · estimate
This author's own choices. Worth a look.
3
Very specific
Tied to their project's names, files or tools. Probably skip.
No licence file, so all rights are reserved — read it at the source. We count its rules but don't quote them. Read them on GitHub.
≈ “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.
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.

