mirror of https://github.com/alirezarezvani/claude-skills.git synced 2026-08-28 04:24:58 +00:00

History

Claude 028dc13b35 feat(tooling): JSON-output sample gate (G9) + --sample fixtures (#654 ) Implements issue #654 Option A (embedded-sample convention) plus the verification harness the issue asked for: - scripts/smoke_json_output.py — new advisory gate (G9) that discovers every tool whose --help advertises JSON output, runs <tool> --sample <json-flag>, and asserts the stdout parses as JSON. Tools advertising JSON without --sample are reported as 'uncovered' (a backlog, not a failure) so the gate can be adopted incrementally; --strict flips that to a hard failure once coverage is high. Wired into ci-quality-gate.yml alongside G8. - Added --sample embedded fixtures to the 5 tools named in #654: error_budget_calculator, slo_review, blast_radius_calculator, audit_log_analyzer, api_linter. Their required args are now optional when --sample is passed; missing-arg behavior is unchanged otherwise. - Fixed 4 tools the new gate surfaced (prompt_rater, coach_tip_classifier, cheat_code_filter, redaction_linter): their --sample path printed human text and ignored --json; it now honors the JSON flag. - Synced the 3 dual-published standalone copies (slo-architect x2, chaos-engineering) so the drift guard stays green. Gate now reports 16 tools covered, 16 verified, 0 failures. https://claude.ai/code/session_01CUWsrUNZP9jpxvAwq67UiT		2026-06-11 15:29:39 +00:00
..
.claude-plugin	chore(versioning,docs): normalize stale versions to 2.9.0 + refresh counts	2026-05-27 05:22:59 +00:00
skills/chaos-engineering	feat(tooling): JSON-output sample gate (G9) + --sample fixtures (#654 )	2026-06-11 15:29:39 +00:00
README.md	feat(skills): ship chaos-engineering (Phase 3 — resilience testing discipline)	2026-05-09 21:24:16 +00:00

README.md

Chaos Engineering

End-to-end discipline for chaos experiments — design, run, learn — without becoming an outage.

What's inside

3 stdlib Python tools — experiment designer, blast-radius calculator, postmortem generator
4 reference docs — principles, experiment design, attack taxonomy, tooling landscape
2 templates — experiment plan, postmortem
/chaos-experiment slash command — interactive design wizard

Install

# Via Claude Code marketplace
/plugin install chaos-engineering

# Or clone the repo
git clone https://github.com/alirezarezvani/claude-skills.git
cd claude-skills/engineering/chaos-engineering

Quick start

SKILL=engineering/chaos-engineering/skills/chaos-engineering

# 1. Design an experiment
python "$SKILL/scripts/experiment_designer.py" \
  --target checkout-svc \
  --hypothesis "p99 < 500ms when payment slows" \
  --attack latency --magnitude "+200ms" \
  --abort-if "p99 > 1000ms OR error_rate > +1pp"

# 2. Calculate blast radius
python "$SKILL/scripts/blast_radius_calculator.py" \
  --traffic-share 0.05 --user-pop 1000000 \
  --duration-min 15

# 3. Generate postmortem after running
python "$SKILL/scripts/experiment_postmortem.py" \
  --plan plan.json --result-log results.txt

Key principles

Build a hypothesis around steady-state behavior — measurable, falsifiable
Vary real-world events — realistic failures only, not astronomy-grade
Run experiments in production — staging never has prod failure modes
Automate experiments to run continuously — single experiment = press release; continuous = engineering
Define abort criteria up front — chaos without abort = outage

The 7 attack types

Attack	Tests	Magnitude examples
Latency	Timeouts, retries, circuit breakers	+200ms, +2s
Error	Error handling, fallback paths	1%, 50%, 100%
Resource	Saturation, autoscaling, OOM	80% CPU, 90% memory, fill /var
Network partition	Consensus, leader election, failover	drop 100% to peer X
Dependency failure	Graceful degradation	timeout 100% to dep X
Time skew	Clocks, TTLs, retry backoff	+5min, +1day
Infrastructure	Auto-recovery, replica maintenance	kill 1 of N

Composition with other skills

Skill	Composition
`feature-flags-architect`	Kill switches there are abort triggers here
`kubernetes-operator`	Operators are common chaos targets
`incident-response`	Chaos that escalates becomes an incident

Skill structure

chaos-engineering/
├── README.md
├── .claude-plugin/plugin.json
└── skills/chaos-engineering/
    ├── SKILL.md
    ├── scripts/
    │   ├── experiment_designer.py
    │   ├── blast_radius_calculator.py
    │   └── experiment_postmortem.py
    ├── references/
    │   ├── chaos_principles.md
    │   ├── experiment_design.md
    │   ├── attack_taxonomy.md
    │   └── tooling_landscape.md
    └── assets/
        ├── experiment_template.md
        └── postmortem_template.md

Verifiable success

A team using this skill should achieve:

100% of chaos experiments have written hypothesis, abort criteria, blast-radius calc
Blast radius for any single experiment ≤10% of monthly error budget
Mean time between chaos experiments <14 days (continuous, not one-off)
Each experiment produces ≥1 follow-up action that gets shipped
No chaos experiment escalates to a customer-impacting incident in trailing 90 days

License

MIT — see repo root LICENSE.