You are in AUTONOMOUS MODE. Do NOT ask questions. Do NOT pause for confirmation. Execute every phase below in sequence, making decisions based on what you find.

============================================================ PHASE 0 — INPUT

$ARGUMENTS may contain:

A specific sub-area to focus on: ci, docker, k8s, monitoring, terraform, secrets, cdn, dns
--report-only — produce the readiness report without generating or modifying files
--fix — attempt to fix all identified gaps by chaining sub-skills
A target environment: aws, gcp, azure, fly, vercel
If no arguments, default to --report-only

============================================================ PHASE 1 — INFRASTRUCTURE DISCOVERY

Scan the entire project root for existing infrastructure artifacts:

CI/CD: .github/workflows/, .gitlab-ci.yml, Jenkinsfile, .circleci/, bitbucket-pipelines.yml
Containers: Dockerfile, docker-compose.yml, docker-compose.*.yml, .dockerignore
Kubernetes: k8s/, kubernetes/, helm/, charts/, any *.yaml with apiVersion: apps/
IaC: terraform/, *.tf, pulumi/, Pulumi.yaml, cdk/, cloudformation/
Monitoring: prometheus.yml, grafana/, datadog.yaml, .newrelic.yml, alertmanager.yml
Secrets: .env, .env.*, vault/, secrets/, hardcoded API keys or tokens in source
CDN: cdn/, Cloudflare config (wrangler.toml), CloudFront references in Terraform
DNS: DNS records in Terraform, Cloudflare zone configs, Route53 references

Also detect the application stack:

Language: Check package.json, go.mod, Cargo.toml, requirements.txt, pyproject.toml, Gemfile, pubspec.yaml, pom.xml, build.gradle
Framework: Next.js, Fastify, Express, Django, Flask, FastAPI, Gin, Actix, Rails, Spring Boot, Flutter
Database: Prisma schema, SQLAlchemy models, GORM, ActiveRecord, TypeORM

Store all findings in memory for scoring.

============================================================ PHASE 2 — READINESS SCORING

Score each area on a 0-100 scale using the rubric below. Be precise — partial credit is valid (e.g., 35 or 65).

Area	0	25	50	75	100
CI/CD	Nothing	Basic lint/test	PR checks + deploy	+ caching + matrix	+ security scan + preview deploys
Containers	Nothing	Dockerfile exists	+ multi-stage	+ compose + healthcheck	+ non-root + .dockerignore + optimized layers
Kubernetes	Nothing	Basic deployment	+ service + ingress	+ HPA + probes	+ PDB + resource limits + Helm
IaC	Nothing	Single resource	Modular structure	+ remote state + envs	+ cost tags + proper naming + outputs
Monitoring	Nothing	Basic logging	Metrics endpoint	+ dashboards + alerts	+ SLOs + distributed tracing
Secrets	Hardcoded values	.env files	Secrets manager	+ rotation	+ CI integration + audit trail
CDN	Nothing	Static hosting	CDN configured	+ caching rules	+ edge functions + invalidation
DNS	Nothing	Manual records	IaC-managed	+ SSL + subdomains	+ email DNS + health routing

Calculate an overall Deployment Readiness Score as the weighted average:

CI/CD: 25%
Containers: 20%
Monitoring: 15%
IaC: 15%
Secrets: 10%
Kubernetes: 5% (0-weight if app is serverless/edge)
CDN: 5%
DNS: 5%

============================================================ PHASE 3 — GAP ANALYSIS

For each area scoring below 50, generate a specific remediation plan:

What is missing (concrete, not vague)
Which sub-skill can fix it (reference: deploy/github-actions, deploy/docker, deploy/k8s, deploy/monitoring, deploy/terraform, deploy/secrets, deploy/cdn, deploy/dns)
Estimated effort: quick (<5 min), moderate (5-15 min), significant (15+ min)
Priority based on:
- Critical: No CI/CD, secrets in source code, no containerization for production app
- High: No monitoring, no IaC for cloud resources, no health checks
- Medium: Missing caching, no preview deploys, basic Kubernetes without HPA
- Low: No CDN, no email DNS, no edge functions

============================================================ PHASE 4 — REMEDIATION (if --fix)

If --fix was passed, execute remediations in priority order:

Critical items first — fix secrets exposure, add basic CI/CD
High items next — add Dockerfile, monitoring, IaC
Medium items — optimize CI caching, add HPA, preview deploys
Low items — CDN, DNS, edge functions

For each remediation:

Read the sub-skill's approach and apply it inline (do not shell out)
After each fix, re-score that area and record the before/after delta
Stop if cumulative changes exceed 20 new files (to avoid overwhelming a single PR)

============================================================ PHASE 5 — OUTPUT

Generate a deployment readiness report. Print to stdout AND write to DEPLOY_READINESS.md in the project root.

## Deployment Readiness Report

**Project**: {detected project name}
**Stack**: {language} / {framework} / {database}
**Date**: {current date}
**Overall Score**: {score}/100

### Area Scores

| Area | Score | Status | Key Finding |
|------|-------|--------|-------------|
| CI/CD | XX | PASS/WARN/FAIL | {one-line summary} |
| Containers | XX | PASS/WARN/FAIL | {one-line summary} |
| Kubernetes | XX | PASS/WARN/FAIL | {one-line summary} |
| IaC | XX | PASS/WARN/FAIL | {one-line summary} |
| Monitoring | XX | PASS/WARN/FAIL | {one-line summary} |
| Secrets | XX | PASS/WARN/FAIL | {one-line summary} |
| CDN | XX | PASS/WARN/FAIL | {one-line summary} |
| DNS | XX | PASS/WARN/FAIL | {one-line summary} |

### Critical Gaps
{list of critical and high priority gaps with sub-skill references}

### Recommended Actions
{ordered list of remediations — each with sub-skill name, estimated effort, and expected score improvement}

### Changes Made (if --fix)
{list of files created/modified with before/after scores}

Use PASS for scores >= 75, WARN for 50-74, FAIL for < 50.

============================================================ SELF-HEALING VALIDATION (max 2 iterations)

After completing deployment/infrastructure changes, validate:

Verify all generated files are syntactically valid (YAML, JSON, HCL, Dockerfile).
Run validation commands if available (terraform validate, docker build --check, kubectl dry-run).
Verify no secrets, credentials, or sensitive values are hardcoded.
If validation fails, diagnose and fix the specific syntax or config error.
Repeat up to 2 iterations.

IF STILL FAILING after 2 iterations:

Document what failed and the exact error
Include partial output if available

============================================================ NEXT STEPS

After generating the report, suggest:

Which sub-skill to run first if gaps exist (with the exact command)
Whether the project is ready for production deployment
Any architectural concerns (e.g., no database backups, no rate limiting, no disaster recovery)

============================================================ SELF-EVOLUTION TELEMETRY

After producing output, record execution metadata for the /evolve pipeline.

Check if a project memory directory exists:

Look for the project path in ~/.claude/projects/
If found, append to skill-telemetry.md in that memory directory

Entry format:

### /devops — {{YYYY-MM-DD}}
- Outcome: {{SUCCESS | PARTIAL | FAILED}}
- Self-healed: {{yes — what was healed | no}}
- Iterations used: {{N}} / {{N max}}
- Bottleneck: {{phase that struggled or "none"}}
- Suggestion: {{one-line improvement idea for /evolve, or "none"}}

Only log if the memory directory exists. Skip silently if not found. Keep entries concise — /evolve will parse these for skill improvement signals.

============================================================ DO NOT

Do NOT delete existing infrastructure files — only add or modify
Do NOT commit changes — leave them staged for review
Do NOT expose secrets in the report output
Do NOT assume a cloud provider — detect or use $ARGUMENTS
Do NOT generate Kubernetes manifests for projects that are clearly serverless/edge
Do NOT modify application source code — only infrastructure files
Do NOT install CLI tools or dependencies — work with what is available

devops

SKILL.mddeploy/devops/SKILL.md