ai-pipeline

name	ai-pipeline
description	Orchestrate the repo-aligned AI engineering pipeline (plan → decisions → eval → improve → cleanup → verify → archive) with explicit approval gates. TRIGGER when user asks to run the full pipeline or go from idea to delivery; DO NOT TRIGGER for small tasks or when user invokes a specific phase.

AI Pipeline — Repo-Aligned Orchestration

Orchestrate the full “idea → delivery” pipeline while staying strictly compatible with this repository’s workflow gates and artifact conventions.

Hard Compatibility Rules

• Follow CLAUDE.md lifecycle gates and agents (including Approval Gate and Archive/WAL).
• All runtime artifacts MUST be written under .claude/runs/task-briefs/<YYYY-MM-DD>_<slug>_*.
• No external state directories, no implicit git/CI automation.
• No infinite loops. Any iterative improvement requires explicit user approval to continue.
• Only delegate to available agent types (e.g., search) and provide self-contained context.

When to Use

• User asks to “run the pipeline / full pipeline”
• Work spans multiple phases: planning + decision records + evaluation + implementation + cleanup + verification

Do not use when the user requests a single phase explicitly (e.g., “just write the plan”).

Pipeline (Repo Lifecycle Mapping)

0. Intake: input-classifier — classify and normalize the raw input before anything else. Emits [Intake] block with Intent/Profile/Scenario/AC-Candidates. Skip only for explicit @shortcuts or single-phase invocations.
1. Design: brainstorming (when creative) → impl-plan or blueprint
2. Decisions: architecture-decision-records
3. Evaluation: eval-harness (define pass/fail and verification commands)
4. Approval Gate: if risk is MEDIUM/HIGH, stop after spec and wait for approval
5. Implement: implement the plan in-scope only
6. Improve (optional): self-improve (bounded iterations, user-approved) 6.1 External Research (conditional): if self-improve score has plateaued for 2+ iterations, invoke external-research to find new approaches before continuing. External research can only be invoked once per plateau.
7. Cleanup: ai-slop-cleaner (regression-safe)
8. Verify: ac-verify (single pass) or ultraqa (bounded cycles)
9. Archive: write WAL fragments + archive the task_brief
10. Remember (optional): invoke remember skill to extract lessons learned into long-term memory. Use when the task surfaced non-obvious project constraints, anti-patterns, or validated approaches.

Orchestration Steps

Step 0 — Intake + Scope

Run input-classifier on the raw input. Use its [Intake] block as the seed for Steps 1–2.

Capture:

• Objective (what changes, what must not)
• File boundary (explicit in-scope paths)
• Acceptance criteria (what evidence means “done”) — from [Intake].AC-Candidates if available

Step 1 — Create Task Artifacts

Create:

• <slug>_task_brief.md
• <slug>_current_task.md

Step 2 — Run Phases in Order

• Plan → Decisions → Eval → (Approval Gate) → Implement → Verify → Archive

Step 3 — Iteration Policy (if not met)

If acceptance criteria are not met:

• Produce a short delta analysis (what failed, why)
• Propose one next iteration (plan change or fix)
• Ask the user to approve another iteration (no silent looping)

Related Skills

• eval-harness: MUST precede self-improve; defines the objective baseline
• self-improve: bounded improvement loop requiring eval-harness baseline
• remember: optional post-archive knowledge preservation
• external-research: plateau-breaker for stalled self-improve cycles