Agile-V/agentic_agile_v

記録された最新のソース活動: 2026年7月8日 18:43

SkillsMP カタログ更新: 2026年10月29日 18:30

収集済み skills: 5

GitHub スター: 7
GitHub フォーク: 3

AI アシスタントでインストール

このプロンプトをコピーして、使用中の AI アシスタントに送ってください。

Follow https://skillsmp.com/skill-install/prompt.md to install Agent Skills from https://github.com/Agile-V/agentic_agile_v.

リポジトリの README

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# Agentic Agile-V Infrastructure This repository scaffold operationalizes the paper framework **Agentic Agile-V: From Vibe Coding to Verified Engineering in Software and Hardware Development**. The goal is simple: > Conversation discovers intent. Structured artifacts control implementation. Evidence controls acceptance. The scaffold gives teams a practical way to run AI agents inside a disciplined engineering process without turning development into uncontrolled "vibe coding". ## What is included - `AGENTS.md`: repository-level rules for coding agents. - `templates/`: feature, bug, hardware/firmware, test, review, and evidence templates. - `docs/`: process documentation for Agile-V, SCOPE-V, testing, hardware, and evidence gates. - `schemas/`: JSON schemas for task briefs, evidence bundles, system graph, impact map, and traceability. - `scripts/`: local validation and task bootstrap tools. - `.github/`: PR template, issue templates, and CI workflow for evidence gates. - `examples/`: sample feature, bug, and hardware task packages. - `src/agilev/`: Python runtime library — graph adapter, impact analysis, traceability. - `tests/`: Unit tests for the Python runtime library. ## Recommended workflow 1. Start with a conversation to discover intent. 2. Convert the conversation into a structured task brief. 3. Classify risk level from L0 to L4. 4. Ask the agent to inspect the repository and produce a plan. 5. Approve the plan for non-trivial changes. 6. Implement in small slices. 7. Generate or update tests. 8. Produce an evidence bundle. 9. Run validation gates. 10. Merge only after human review and risk-appropriate evidence. ## Quick start Create a new task package: ```bash python scripts/new_task.py --type feature --id AAV-001 --title "Add device status endpoint" ``` Validate all evidence bundles: ```bash python scripts/validate_evidence.py --root evidence ``` Validate one bundle: ```bash python scripts/validate_evidence.py --bundle evidence/examples/feature/evidence_bundle.json ``` ## Risk levels | Level | Typical scope | Required evidence | |---|---|---| | L0 | Docs, comments, trivial internal cleanup | Brief, plan, reviewer note | | L1 | Low-risk internal code | Tests or test rationale, lint/static check | | L2 | Normal production feature or bug fix | Unit/integration tests, CI, reviewer gate | | L3 | Security, customer-visible, data, APIs, persistent state | Regression tests, security/privacy check, rollback path, approval | | L4 | Safety, hardware/firmware, regulated, money movement, critical infrastructure | Independent verification, HIL/simulation/formal evidence, traceability matrix, approval | ## OpenHands Integration **NEW:** Agentic Agile-V now integrates with [OpenHands](https://github.com/All-Hands-AI/OpenHands) as an execution backend. OpenHands provides autonomous code implementation while Agile-V maintains control through: - **Skills** that teach OpenHands about Agile-V rules - **Hooks** that enforce evidence gates and scope control - **Policies** that define risk-based requirements ### Quick Start ```bash # Initialize OpenHands integration agilev openhands init # Validate setup agilev openhands doctor # Create a task agilev new --title "Add retry handling" --risk L2 # Run OpenHands (skills and hooks activate automatically) # ... # Validate the session agilev openhands validate --task AAV-0001 ``` ### Documentation - [Quick Start Guide](OPENHANDS_QUICKSTART.md) - Get started in 10 minutes - [Implementation Summary](OPENHANDS_INTEGRATION_SUMMARY.md) - Technical details - [Integration Guide](docs/integrations/openhands.md) - Full documentation - [ADR-0001](docs/adr/ADR-0001-openhands-execution-backend.md) - Architecture decision ### Key Features - ✅ Task brief enforcement (no implementation without brief) - ✅ Dangerous command blocking (rm -rf /, etc.) - ✅ Scope validation (warn on out-of-scope changes) - ✅ Tool usage logging (audit trail) - ✅ Evidence validation (block completion until evidence passes) - ✅ Risk-based policies (L0-L4 requirements) **Status:** MVP complete (Phases 0-4 of 12) --- ## Understand Anything Integration Agile V can consume an [Understand Anything](https://github.com/Lum1104/Understand-Anything) knowledge graph to add system context, impact analysis, graph traceability, and regression-test selection to the Agile-V lifecycle. ```bash # Install the runtime library pip install -e .[dev] # Run tests make test ``` See `docs/understand-anything-integration.md` for full usage documentation. The companion skill documentation is in `agile_v_skills/integrations/understand-anything/`. ## OpenWiki Integration Agile-V treats [OpenWiki](https://github.com/langchain-ai/openwiki)-generated documentation (`openwiki/`) as a validated, evidence-linked knowledge layer rather than optional reading material. ```bash # Scaffold required pages + manifest agilev wiki init # (optional) also invoke the real `openwiki` CLI agilev wiki init --run-openwiki # Validate structure and freshness agilev wiki validate # Record a knowledge_snapshot in a task's evidence bundle agilev wiki snapshot --task AAV-0001 ``` See `docs/integrations/openwiki.md` for the full integration design, required page structure, CI workflows, and backlog. ## Principle Do not let an agent implement from a long chat history. Let it implement from a reviewed, versioned brief.

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