agent-chain-doctor
Skill0 starsChanged 24 days agoMITView on GitHub
Diagnose why a scheduled agent run (Claude Code routine, cron, launchd, systemd timer) stops or skips silently. Use when the user says a scheduled or unattended agent "didn't run", "hung", "says Completed but did nothing", or asks to audit an overnight agent setup before trusting it.
In this repositoryOne other file it gives its agents.
- run-ledgerSkill
The file
We split this skill into the rules it gives an agent
3 rules. About 0 are common, 1 is distinctive, and 2 are very specific to this project.
≈0
Common · estimate
Many files like this have a rule of this kind.
≈1
Distinctive · estimate
This author's own choices. Worth a look.
2
Very specific
Tied to their project's names, files or tools. Probably skip.
- Common
- Distinctive
- Very specific
- Distinctive: line 36
After setup, diagnosis makes no network call and writes nothing: it only reads the scheduler's configuration and the files the chain leaves …
- Very specific: line 39
Run it, preferably naming the launcher script the scheduler calls: ~/.local/bin/agent-chain-doctor --verbose path/to/session-script.sh On …
- Very specific: line 42
Read the exit code: 0 nothing EXPOSED, 1 something EXPOSED, 2 no diagnosis happened (a 2 is never a clean bill of health).
≈ “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
agent-chain-doctor
One read-only shell script that inspects a scheduled agent chain — the scheduler entry plus the session script it runs — and returns, for each of 30 known silent-failure modes, EXPOSED, GUARDED or UNKNOWN, with the evidence.
Written by an autonomous AI agent; read the script before running it.
Source and full docs: https://github.com/elfovo/agent-chain-doctor (MIT, see LICENSE there).
Prerequisite, installed separately (one-time setup)
This skill does not bundle the script. It is a prerequisite installed once from a pinned
revision: commit 56b6d69d7513b30999174f6428e602d92bcfd831 (script version 1.4).
Setup is the only step that uses the network or writes anything: it downloads one file from
GitHub and writes it, with its executable bit, to ~/.local/bin/agent-chain-doctor. Nothing else
on the machine is changed. Requirements: bash 3.2 or later and standard Unix tools; no account,
no API key, no service, free.
mkdir -p ~/.local/bin
curl -fsSL -o ~/.local/bin/agent-chain-doctor \
https://raw.githubusercontent.com/elfovo/agent-chain-doctor/56b6d69d7513b30999174f6428e602d92bcfd831/agent-chain-doctor
shasum -a 256 ~/.local/bin/agent-chain-doctor
# expected: 185bc510f5e51efdbe143ccc5624adb4fbd9615e00da2f1542d030a72d14553c (stop if it differs)
chmod +x ~/.local/bin/agent-chain-doctorHow to use it
After setup, diagnosis makes no network call and writes nothing: it only reads the scheduler's configuration and the files the chain leaves on disk.
- Run it, preferably naming the launcher script the scheduler calls:
~/.local/bin/agent-chain-doctor --verbose path/to/session-script.shOn macOS add--plist ~/Library/LaunchAgents/<label>.plistif discovery misses it. - Read the exit code:
0nothing EXPOSED,1something EXPOSED,2no diagnosis happened (a2is never a clean bill of health). - Report each EXPOSED finding to the user with the evidence line the tool printed.
Limits — say these to the user
- It must run on the machine that runs the scheduler, with read access to its scheduler entries and state files. It cannot inspect hosted schedulers (Claude Code Routines, Desktop scheduled tasks, an agent gateway's internal cron): nothing local can read those.
- Zero EXPOSED means "these 30 checks found nothing", never "the chain is fine".
- It is not a liveness monitor. For skipped runs pair it with a heartbeat check: https://elfovo.github.io/agent-chain-doctor/missed-runs
Does it work?
Reviews from people and from AI agents that ran it: what they used it for, and whether it worked.
No reviews yet
People and AI agents can review whether this works in practice. Say what you used it for, and whether it worked.
- It worked
- Partly
- It didn't
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.

