Install
$ agentstack add skill-hsienw-ai-agent-engineering-playbook-agent-observability-fault-tolerance ✓ scanned · ✓ verified, works with Claude Code, Cursor, and more.
Security review
✓ PassedNo issues found. Passed automated security review. · v0.1.0 How review works →
- ✓ Prompt-injection patterns
- ✓ Secret / credential exfiltration
- ✓ Dangerous shell & filesystem operations
- ✓ Untrusted network calls
- ✓ Known-malicious package signatures
What it can access
- ✓ Network access No
- ✓ Filesystem access No
- ✓ Shell / process execution No
- ✓ Environment & secrets No
- ✓ Dynamic code execution No
From automated source analysis of v0.1.0. “Used” means the capability is present in the source — more access means more to trust, not that it’s unsafe.
Verified badge
Passed review? Show it. Paste this badge into your README, it links to the public security report.
Reliability & compatibility
Declared compatibility
Compatibility is declared by the source manifest. End-to-end runtime verification is coming, see below.
We're building live execution health for every listing: tool-call success rate, median latency, uptime, and last-checked timestamps, measured, not self-reported. It isn't live yet, so we don't show numbers we can't stand behind.
How agent discovery & health will work →About
Agent Observability and Fault Tolerance
Skill Interface
- Name: agent-observability-fault-tolerance.
- Description: Design and review agent runtime observability and model or provider fault tolerance for metrics, traces, cost tracking, audit alignment, runtime events, fallback, repair, refusal handling, timeouts, and execution tree diagnostics.
- Parameters: Task and step lifecycle, model and tool calls, retry and fallback policy, trace identifiers, metric names, cost fields, redaction policy, terminal states, and verification scenarios.
- Instructions: Use this skill when runtime behavior must be observable across success, retry, fallback, refusal, timeout, and terminal paths. Add bounded metrics, preserve trace continuity, classify failures, redact sensitive data, and test telemetry for each recovery path.
An agent runtime should make work visible across task, step, model, tool, retry, and terminal paths. Fault tolerance should be explicit and observable.
Signals
Capture metrics and traces across:
- Task lifecycle.
- Step lifecycle.
- Tool calls.
- Model calls.
- Retry attempts.
- Structured output repair.
- Fallback provider selection.
- Human approval or refusal.
- Compensation.
- Terminal state.
Metrics
Track:
- Task success rate.
- Task completion latency.
- Step failure rate.
- Retry recovery rate.
- Resume success rate.
- Idempotency hit rate.
- Duplicate side-effect prevention rate.
- Tool success, timeout, and latency.
- Permission denial rate.
- Compensation success rate.
- Model fallback rate.
- Structured output repair success rate.
- Cost per successful task.
Trace Shape
Use a trace hierarchy that follows the actual execution chain:
request
agent task
graph node
model call
tool call
retry attempt
repair attempt
Include stable identifiers when available: request id, task id, step id, run id, thread id, graph id, node name, tool call id, provider, model category, duration, retry count, terminal status, and error code.
Fault Tolerance
- Provider temporary failure: retry within budget, then fallback if policy
allows.
- Provider timeout: retry with backoff, then fallback or return timeout result.
- Structured output parse error: attempt bounded repair.
- Structured output validation error: repair with a precise validation hint.
- Refusal or policy denial: do not retry blindly; return a structured refusal
signal.
- Tool timeout or upstream failure: classify and apply retry policy.
Safety Rules
- Do not log credentials, raw authorization headers, private payloads, full
prompts, full conversations, or unredacted personal data.
- Do not hide fallback, repair, retry, or degraded execution from telemetry.
- Do not conflate provider failure, validation failure, refusal, and timeout
into one generic error.
Verification
Test provider outage, timeout, structured parse failure, validation failure, refusal, retry exhaustion, fallback success, cost accounting, trace continuity, metric emission, and redaction.
Source & license
This open-source skill is cataloged on AgentStack and links to its original source — we do not rehost the code.
- Author: HsienW
- Source: HsienW/ai-agent-engineering-playbook
- License: MIT
Install and usage instructions live in the source repository linked above.
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Versions
- v0.1.0 Imported from the upstream source.