initial: pi-setup workspace with skill + extension plan
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# Domain Evolution Bootstrap
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Use this reference when `/evolve` is asked to reshape AgentOps skills, CLI,
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hooks, docs, tests, beads, or knowledge as one software-factory system.
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## Product Frame
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AgentOps is the SDLC control plane and context compiler for LLM agents. The
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narrow waist is:
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- BDD/Gherkin for observable intent;
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- DDD for shared names and bounded contexts;
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- Hexagonal architecture for ports and adapters;
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- TDD for local proof of done;
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- XP for small vertical slices;
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- CI, SRE, ADRs, and provenance for repeated trust and memory.
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Do not treat a skill, hook, or command as valuable by itself. It is valuable
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only when it advances the factory loop: intent, boundary, proof, evidence, and
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compounding context.
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## Bootstrap Sequence
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1. Read current direction from `PRODUCT.md`, `GOALS.md`,
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`docs/cdlc.md`, and `docs/architecture/operating-loop.md`.
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2. Validate the durable control artifacts:
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```bash
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bash scripts/check-agentops-domain-evolution-plan.sh
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```
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3. Select one domain and one vertical slice from:
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- `docs/reference/agentops-domain-evolution-bdd.md`
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- `docs/reference/agentops-skill-domain-map.md`
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- `docs/reference/agentops-hexagonal-architecture-map.md`
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- `docs/reference/agentops-domain-evolution-plan.md`
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4. Use `skill-builder` and `skill-auditor` for skill changes. Use
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`skills/skill-auditor/scripts/score_agentops_skill.py` to choose the
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smallest score-improving patch.
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5. Keep CLI and hook changes behind typed ports or existing validation scripts.
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6. Run focused validation before selecting the next slice.
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## Hard Rules
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- No broad rewrite before a Gherkin row, domain, and first proof are named.
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- No third-party content copying; use clean-room structural observations only.
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- No shipped skill deletion until replacement workflow and validation evidence
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exist.
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- No shell-only read path when a typed port already exists.
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- No unattended run from a dirty canonical root or stale installed `ao` binary.
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