This skill should be used when the user asks to "check accessibility", "audit WCAG compliance", "scan HTML for a11y issues", "check color contrast", or "find accessibility violations in web pages".
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
Orchestrate end-to-end release pipelines. Use when running pre-release validation, generating changelogs, bumping semantic versions, scoring deployment readiness, or gating releases with secret scanning and GO/NO-GO checks.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
설치 방법 보기설치하기 전에 에이전트에게 전달되는 지시 내용을 확인할 수 있습니다.
The agent runs pre-flight validation, generates changelogs from conventional commits, auto-bumps semantic versions, and scores deployment readiness with a GO/CONDITIONAL/NO-GO decision.
package.json, pyproject.toml, Cargo.toml, etc.; pre-release tags (--pre alpha|beta|rc).@author attribution.Before orchestrating the release, confirm these inputs. If any is unknown or vague, ASK — do not assume:
--from/--to)Stop rule: ask only the 2-3 that most change the output. If the user says "just draft it," proceed and list your assumptions at the top of the artifact.
| Tool | Purpose | Command |
|---|---|---|
preflight_checker.py | Run 7 pre-release checks (sync, conflicts, secrets, commits, deps) | python scripts/preflight_checker.py --repo . --base main --json |
changelog_generator.py | Generate Keep a Changelog markdown from a ref range | python scripts/changelog_generator.py --repo . --from v1.2.0 --to HEAD --output CHANGELOG.md |
version_bumper.py | Auto-detect next semver from commits; write version files | python scripts/version_bumper.py --repo . --dry-run --json |
release_readiness_scorer.py | Score readiness 0-100 with GO/CONDITIONAL/NO-GO decision | python scripts/release_readiness_scorer.py --input release_data.json --json |
All tools support --json for machine output. Exit code 0 = pass, 1 = fail (CI-friendly).
Load the reference that matches the task — keep this file lean and pull detail on demand:
This skill covers: pre-flight validation, semantic version bumping, changelog generation, deployment-readiness scoring, and gating releases with GO/NO-GO decisions for git + conventional-commits projects.
This skill does NOT cover: the actual deploy/orchestration execution (handled by senior-devops / devops-workflow-engineer), test authoring (senior-qa), or deep security scanning beyond secret pattern-matching (senior-secops).
| Skill | Integration |
|---|---|
senior-devops | Pipeline stages consume pre-flight and readiness JSON as gates |
senior-qa | Test results feed Tests category (25% weight) |
senior-secops | Secret scan and CVE counts feed Security category (15%) |
code-reviewer | Code quality metrics feed Code Quality category (20%) |
devops-workflow-engineer | Workflow YAML calls tools as pipeline steps |
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This skill should be used when the user asks to "check accessibility", "audit WCAG compliance", "scan HTML for a11y issues", "check color contrast", or "find accessibility violations in web pages".
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
Design and analyze A/B tests: sample size, test duration, and statistical significance for conversion experiments. Use when setting up an A/B test, calculating sample size, designing an experiment, or analyzing results.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
Design and run statistically rigorous A/B tests and experiments. Use when planning experiments, calculating sample sizes, designing test variants, selecting metrics, analyzing results, or when someone says "let's test that."
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
Sales execution across pipeline, discovery, demos, negotiation, and closing. Use when qualifying opportunities, running MEDDIC discovery, building account plans, handling objections, structuring proposals, or forecasting pipeline.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
Design ad creative across Google, Meta, LinkedIn, Twitter/X, and TikTok with platform format specs, headline formulas, and A/B testing. Use when writing ad copy, generating headline variations, creating ad sets, or validating creative.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
Answer Engine Optimization (AEO): optimize content to be cited by LLMs (ChatGPT, Claude, Perplexity, Gemini) in their answers. Use when designing content for LLM citation, auditing citability, or structuring Q&A schema.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.