Feature flag risk assessor
Skill sisodiabhumca/agent-skills/skills/feature-flag-risk-assessor
Production-Ready Agent Skills : product analytics, growth experiments, CRM, research synthesis, postmortems, data contracts, SaaS spend, compliance, architecture maps, and LLM eval and many more.
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Vendor-neutral skill to assess risk in feature-flag configurations (stale flags, kill-switch coverage, conflicting rules) and produce actionable recommendations.
SKILL.md
1.4 KB, as published. Nobody here has run it
When to invoke
- You have a feature-flag export (JSON) and want to identify operational and release risks.
- You want to standardize flag hygiene checks during releases.
Inputs needed
--inputpath to a JSON file containing feature flags.- Expected shape:
{ "flags": [ {"key": "...", "created_at": "YYYY-MM-DD", "updated_at": "YYYY-MM-DD", "enabled": true/false, "rules": [...] } ] }
- Expected shape:
Workflow
- Validate the flag schema and required fields.
- Compute risk signals:
- stale flags (no updates beyond threshold)
- enabled flags older than threshold
- flags without a documented owner
- rule conflicts (duplicate segments with different rollouts)
- missing kill-switch (no global off / override rule)
- Emit a JSON report with per-flag risk score and suggested actions.
Output format
- JSON written to
--output:summary: counts by risk typeflags: per-flag findings +risk_score(0-100)
Guardrails
- Do not attempt to evaluate user targeting deterministically; only analyze configuration structure.
- Prefer explainable heuristics over opaque scoring.
Reference code
feature_flag_risk_assessor.pyimplements a heuristic risk analyzer (stdlib-only).