andon
Skill11 starsChanged 2 months agoMITView on GitHub
Make software health, failure, degradation, and recovery visible through useful observability and diagnostics. Use when adding logs, metrics, traces, health checks, alerts, incident signals, or operational feedback.
In this repository13 other files it gives its agents.
- genchi-genbutsuSkill
- hanseiSkill
- jidokaSkill
- kaizenSkill
- kansoSkill
- kataSkill
- kodawariSkill
- monozukuri-blueprintSkill
- monozukuri-coreSkill
- monozukuri-routerSkill
- nemawashiSkill
- poka-yokeSkill
- shukkaSkill
The file
We split this skill into the rules it gives an agent
10 rules. About 0 are common, 8 are distinctive, and 2 are very specific to this project.
≈0
Common · estimate
Many files like this have a rule of this kind.
≈8
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 28
when and where it happened.
- Distinctive: line 43
Use structured logs for event context, metrics for rates and saturation, traces for distributed causality, and health checks for readiness …
- Distinctive: line 73
Do not log secrets, credentials, tokens, or unnecessary personal data.
- Distinctive: line 74
Do not add dashboards or alerts without an operational question and owner.
- Distinctive: line 75
Do not use logs to compensate for missing correctness checks.
- Distinctive: line 76
Do not treat a green health check as proof that user behavior is correct.
- Distinctive: line 77
Do not make the system noisy enough that meaningful failures disappear.
- Very specific: line 81
Document the signals, meanings, owners, redaction rules, and response path.
- Very specific: line 82
Use jidoka for the underlying defect, kodawari for review, shukka for release checks, or hansei when observability failed during an …
- Distinctive: line 85
If a referenced skill is not installed, apply its named lens inline instead of trying to invoke it.
≈ “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
Andon
Andon is a visible signal that makes a problem impossible to ignore. In software, observability should help a person detect, understand, and recover from meaningful behavior. This is a Japanese-inspired engineering metaphor, not a demand to instrument every line.
Use this skill when
- a feature or service changes important behavior;
- an incident was difficult to diagnose;
- failures are silent, ambiguous, or discovered too late;
- adding logs, metrics, traces, health checks, dashboards, or alerts;
- designing retries, degradation, recovery, or operational ownership; or
- a release needs signals that prove it is healthy.
Outcome
Produce an observability plan or implementation that answers:
- what happened;
- who or what was affected;
- when and where it happened;
- how severe it is;
- what the operator or user should do next; and
- whether the system recovered.
Workflow
1. Identify decisions and failure modes
List the behavior that needs observation, the failure or degradation modes, the people who respond, and the decisions the signals must support. Start with actionable questions, not a preferred telemetry product.
2. Choose the smallest useful signals
Use structured logs for event context, metrics for rates and saturation, traces for distributed causality, and health checks for readiness or liveness. Choose only signals that help detect, diagnose, operate, or improve the system.
3. Preserve context safely
Include correlation identifiers, stable dimensions, error categories, timing, and relevant state. Redact secrets and personal data. Avoid high-cardinality, duplicated, or noisy signals that hide the useful signal or create unsafe cost.
4. Make recovery visible
Represent failure, retry, degradation, fallback, recovery, and permanent error as distinguishable states. Health checks must reflect the dependency and readiness semantics that operators actually need.
5. Exercise the signals
Trigger representative success and failure paths. Confirm that signals appear with enough context during the failure they are meant to explain and that alerts have an owner and a meaningful action.
Evidence standard
An observability change is useful only when a person can use it to make a decision. Verify the signal in the relevant runtime or test environment and state what remains unverified.
Boundaries
- Do not log secrets, credentials, tokens, or unnecessary personal data.
- Do not add dashboards or alerts without an operational question and owner.
- Do not use logs to compensate for missing correctness checks.
- Do not treat a green health check as proof that user behavior is correct.
- Do not make the system noisy enough that meaningful failures disappear.
Handoff
Document the signals, meanings, owners, redaction rules, and response path.
Use jidoka for the underlying defect, kodawari for review, shukka for
release checks, or hansei when observability failed during an incident.
If a referenced skill is not installed, apply its named lens inline instead of trying to invoke it.
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.

