penguiflow-observability

penguiflow-observability is an Observability & incident response skill for AI agents, published by hurtener in the penguiflow repository on GitHub. Skillspace rates penguiflow-observability C (74/100) and it passed the safety scan; the rating is based on static analysis only.

Add structured observability to a PenguiFlow runtime — turn on JSON logging with `configure_logging(structured=True)`, attach `log_flow_events` middleware to capture `FlowEvent` lifecycle (`node_start`/`node_success`/`node_error`/`node_timeout`/`node_retry`/`node_failed`/`deadline_skip`/`trace_cancel_*`), derive counters/histograms/gauges via `FlowEvent.metric_samples()`/`tag_values()` while obeying cardinality rules (never tag by `trace_id`), wire `FlowError`/`FlowErrorCode` for traceable failures, and export topology with `flow_to_mermaid`/`flow_to_dot`. Use when a user says "add observability", "logging", "metrics", "alerts", "trace this flow", "visualize", or asks how to monitor a production worker fleet.

Grade
C
Quality
74 / 100
Safety
Passed
GitHub stars
26

Unproven: rated by static analysis only, not yet compared head-to-head.

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View source on GitHubhurtener/penguiflow

Our review

Architecture
100 / 100
Maturity
Structured: ships references or scripts
Security scan
No issues found
License
MIT
Adoption
Adopted by 0 other repositories, in 0 collections

Not checked yet

  • Not judged on the rubric yet (not a contender in its category)
  • No blind task eval yet
  • Scope (portable / vendor / repo-internal) not assessed; only the top of each category is read for scope
  • Sibling files (scripts, references) not fetched; security scan covers SKILL.md only

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