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ai-augmented-sdlc

AI-assisted development governance — Copilot custom agents, MCP servers, change control, audit trail — per Hack23 ISMS AI Policy

ソース情報

リポジトリ
Hack23/game
ソースの最終更新活動
2026年4月17日 14:05
検出された SKILL.md の言語
英語
スター
13
フォーク
5

インストール方法

デフォルトでは、最初にソースを確認する Prompt が選択されています。直接コマンドに切り替えるか、ローカルコピーをダウンロードすることもできます。

ソースファイルを確認

インストールを決める前に、SKILL.md と SkillsMP に表示されている付属ファイルをお読みください。

SKILL.md を表示中

SKILL.md
ソースの指示 · 読み取り専用プレビュー
name
ai-augmented-sdlc
description
AI-assisted development governance — Copilot custom agents, MCP servers, change control, audit trail — per Hack23 ISMS AI Policy
license
MIT
# AI-Augmented SDLC Skill ## Context Applies whenever GitHub Copilot, custom agents, MCP servers, or any LLM-based tool participates in a code, docs, or configuration change. Codifies the requirements from: - [Information Security Policy — AI-First Operations Governance](https://github.com/Hack23/ISMS-PUBLIC/blob/main/Information_Security_Policy.md) - [Secure Development Policy — AI-Augmented Development Controls](https://github.com/Hack23/ISMS-PUBLIC/blob/main/Secure_Development_Policy.md) - [AI Policy](https://github.com/Hack23/ISMS-PUBLIC/blob/main/AI_Policy.md) - [Change Management](https://github.com/Hack23/ISMS-PUBLIC/blob/main/Change_Management.md) ## Rules 1. **AI outputs are proposals, not authority** — every AI-generated change needs human review before merge 2. **No autonomous deployment** — AI may not bypass CI gates, branch protection, signing, or approvals 3. **Human accountability** — the merging human owns the change regardless of AI assistance 4. **Document AI assistance** — PR descriptions note the agent/skill used (e.g., "assisted by Copilot `frontend-specialist`") 5. **Security gates unchanged or tightened** — AI may never weaken linting, CodeQL, tests, or branch protection 6. **Least-privilege tooling** — each agent uses tools appropriate to its role; widening is a governed change 7. **Curator-agent changes are Normal Changes** — edits to `.github/agents/*.md`, `.github/skills/*/SKILL.md`, `.github/copilot-mcp*.json`, and `.github/workflows/copilot-setup-steps.yml` require CEO or security-owner approval 8. **MCP governance** — MCP server config uses `secrets.COPILOT_MCP_GITHUB_PERSONAL_ACCESS_TOKEN` (never hard-coded tokens) and is reviewed like other security-sensitive code 9. **Audit trail** — every agent action is captured in PRs, commits, CI runs, and issue history 10. **Risk assessment for capability expansion** — new MCP servers, new integrations, broader tool scopes need a documented risk note 11. **Policy-cited commits** — security-relevant AI-generated changes cite the applicable ISMS policy 12. **No secret leakage through prompts** — never paste credentials, tokens, PII, or production data into prompts or shared memory 13. **Avoid data-dependency leaks** — do not accept AI output that fabricates API signatures, options, URLs, or dependencies ## Agent Tiers (per ISP §AI-First Operations) | Tier | Purpose | |---|---| | **Curator-agent** | Maintains agent + MCP + workflow configuration | | **Task agents** | Product analysis, issue creation, ISMS mapping | | **Specialist agents** | Domain-specific implementation (game / UI / test / security / docs) | ## Copilot Coding-Agent Tool Catalogue | Tool | Purpose | |---|---| | `assign_copilot_to_issue(owner, repo, issue_number, [base_ref], [custom_instructions])` | Start autonomous implementation on an issue | | `create_pull_request_with_copilot(owner, repo, title, body, [base_ref], [custom_agent])` | Create a PR where Copilot implements changes | | `get_copilot_job_status(owner, repo, id)` | Track agent job progress / completion | ### `base_ref` use cases | Scenario | `base_ref` | |---|---| | Feature branch | `feature/new-auth` | | Stacked PR | `copilot/issue-123` | | Release branch | `release/v2.0` | ### `custom_instructions` template ```text - Follow existing patterns in src/components/ - Add tests (≥ 80 % coverage, ≥ 95 % on security paths) - Cite ISMS: Secure Development Policy §Phase 3 in the PR body - Do not add new dependencies without `npm audit` + license check ``` ## Review Checklist for AI-Assisted Changes - [ ] PR description documents the agent/skill used - [ ] Diff reviewed for fabricated imports, APIs, URLs - [ ] No hardcoded secrets, tokens, or PII introduced - [ ] No weakening of validation, encoding, auth, or authorization - [ ] No new network calls or `eval`/`Function` usage without justification - [ ] Tests added; coverage thresholds met - [ ] ISMS policy cited where applicable - [ ] Dependencies audited + licensed; SBOM still valid - [ ] CodeQL / Scorecard / Dependabot remain green ## Change Management for Agent / MCP / Workflow Edits 1. Open an issue describing the capability and risk 2. Draft the change on a dedicated branch 3. Reviewer verifies: least-privilege, secret wiring, policy citations, audit trail 4. CEO or designated security owner approves 5. Merge behind branch protection; monitor agent behavior after merge ## Anti-Patterns - ❌ Merging an AI PR without reading the diff - ❌ Disabling a failing security test to make CI green - ❌ Adding a new dependency the agent "said was fine" - ❌ Pasting secrets or production data into a prompt or agent memory - ❌ Silently widening a tool scope (e.g., `tools: ["*"]` for a specialist who previously had a narrow set) without review ## Remember AI accelerates delivery; **humans** remain accountable for security, quality, and compliance. Every change passes the same gates regardless of authorship. Policy citations, audit trail, and least-privilege are non-negotiable.
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