ln-1000-pipeline-orchestrator

name	ln-1000-pipeline-orchestrator
description	Drives a Story through full pipeline (tasks, validation, execution, quality). Use when executing a Story end-to-end from kanban board.
disable-model-invocation	true
license	MIT

Paths: File paths (references/, ../ln-*) are relative to this skill directory.

Type: L1 Orchestrator Category: 1000 Pipeline

Pipeline Orchestrator

Drives a selected Story through the full pipeline (task planning -> validation -> execution -> quality gate) by invoking coordinators as Skill() calls in a single context and advancing from coordinator stage artifacts.

Purpose & Scope

• Parse kanban board and show available Stories for user selection
• Ask business questions in ONE batch before execution; make technical decisions autonomously
• Drive selected Story through 4 stages: ln-300 -> ln-310 -> ln-400 -> ln-500
• Write stage notes + checkpoints after each stage for reporting and recovery
• Handle failures, retries, rework cycles, and escalation to user
• Generate pipeline report with branch name, git stats, agent review info

Hierarchy

L0: ln-1000-pipeline-orchestrator (sequential Skill calls, single context)
  +-- Skill("ln-300") — task decomposition (internally manages stateful task-plan workers)
  +-- Skill("ln-310") — validation (internally launches configured external review agents when available)
  +-- Skill("ln-400") — execution (internally dispatches stateful task workers)
  +-- Skill("ln-500") — quality gate (internally runs artifact-first ln-510/ln-520, verdict, finalization)

Key principle: ln-1000 invokes coordinators via Skill tool. Each coordinator manages its own internal worker dispatch and emits a stage artifact. ln-1000 does NOT modify existing skills — it calls them exactly as a human operator would and treats coordinator artifacts as the primary completion signal.

Task Storage Mode

MANDATORY READ: Load references/environment_state_contract.md and references/storage_mode_detection.md

Extract: task_provider = Task Management -> Provider (linear | file).

When to Use

• One Story ready for processing — user picks which one
• Need end-to-end automation: task planning -> validation -> execution -> quality gate
• Want controlled Story processing with pipeline report

Pipeline: 4-Stage State Machine

MANDATORY READ: Load references/pipeline_states.md for transition rules and guards. MANDATORY READ: Load references/loop_health_contract.md

Backlog       --> Stage 0 (ln-300) --> Backlog      --> Stage 1 (ln-310) --> Todo
(no tasks)        create tasks         (tasks exist)      validate            |
                                                          | NO-GO             |
                                                          v                   v
                                                       [retry/ask]    Stage 2 (ln-400)
                                                                             |
                                                                             v
                                                                      To Review
                                                                             |
                                                                             v
                                                                      Stage 3 (ln-500)
                                                                       |          |
                                                                      PASS       FAIL
                                                                       |          v
                                                                      Done    To Rework -> Stage 2
                                                               (branch pushed)  (max 2 cycles)

Stage	Skill	Input Status	Output Status
0	ln-300-task-coordinator	Backlog (no tasks)	Backlog (tasks created)
1	ln-310-multi-agent-validator	Backlog (tasks exist)	Todo
2	ln-400-story-executor	Todo / To Rework	To Review
3	ln-500-story-quality-gate	To Review	Done / To Rework

Workflow

Phase 0: Recovery Check

PIPELINE="{skill_repo}/ln-1000-pipeline-orchestrator/scripts/cli.mjs"
recovery = Bash: node $PIPELINE status

IF recovery.active == true:
  # Previous run interrupted — resume from CLI state
  1. Extract: story_id, stage, resume_action from recovery JSON
  2. Read already-written stage artifacts and runtime state
  3. Re-read kanban board -> secondary verification only
  4. IF recovery.state.worktree_dir exists: cd {recovery.state.worktree_dir}
  5. Jump to Phase 4, starting from resume_action

IF recovery.active == false:
  # Fresh start — proceed to Phase 1

Phase 1: Discovery, Kanban Parsing & Story Selection

MANDATORY READ: Load references/kanban_parser.md for parsing patterns.

1. Auto-discover docs/tasks/kanban_board.md (or Linear API via storage mode operations)
2. Extract project brief from target project's CLAUDE.md (NOT skills repo):

   project_brief = {
     name: <from H1 or first line>,
     tech: <from Development Commands / tech references>,
     type: <inferred: "CLI", "API", "web app", "library">,
     key_rules: <2-3 critical rules>
   }
   IF not found: project_brief = { name: basename(project_root), tech: "unknown" }
   

3. Parse all status sections: Backlog, Todo, In Progress, To Review, To Rework
4. Extract Story list with: ID, title, status, Epic name, task presence
5. Filter: skip Stories in Done, Postponed, Canceled
6. Detect task presence per Story:
   • Has _(tasks not created yet)_ -> no tasks -> Stage 0
   • Has task lines (4-space indent) -> tasks exist -> Stage 1+
7. Determine target stage per Story (see references/pipeline_states.md Stage-to-Status Mapping)
8. Show available Stories and ask user to pick ONE:

   Project: {project_brief.name} ({project_brief.tech})
   
   Available Stories:
   | # | Story | Status | Stage | Skill | Epic |
   |---|-------|--------|-------|-------|------|
   | 1 | PROJ-42: Auth endpoint | To Review | 3 | ln-500 | Epic: Auth |
   | 2 | PROJ-55: CRUD users | Backlog (no tasks) | 0 | ln-300 | Epic: Users |
   | 3 | PROJ-60: Dashboard | Todo | 2 | ln-400 | Epic: UI |
   
   AskUserQuestion: "Which story to process? Enter # or Story ID."
   

9. Store selected story. Extract story brief for selected story only:

   description = tracker getStory(selected_story.id).body  // provider-specific transport per tracker_provider_contract.md
   story_briefs[id] = parse <!-- ORCHESTRATOR_BRIEF_START/END --> markers
   IF no markers: story_briefs[id] = { tech: project_brief.tech, keyFiles: "unknown" }
   

Phase 2: Pre-flight Questions (ONE batch)

1. Load selected Story description (metadata only)
2. Scan for business ambiguities -- questions where:
   • Answer cannot be found in codebase, docs, or standards
   • Answer requires business/product decision (payment provider, auth flow, UI preference)
3. Collect ALL business questions into single AskUserQuestion
4. Technical questions -- resolve using project_brief:
   • Library versions: MCP Ref / Context7 (for project_brief.tech ecosystem)
   • Architecture patterns: project_brief.key_rules
   • Standards compliance: ln-310 Phase 2 handles this

Skip Phase 2 if no business questions found. Proceed directly to Phase 3.

Phase 3: Pipeline Setup

3.0 Linear Status Cache (Linear mode only)

IF storage_mode == "linear":
  statuses = list_issue_statuses(teamId=team_id)
  status_cache = {status.name: status.id FOR status IN statuses}

  REQUIRED = ["Backlog", "Todo", "In Progress", "To Review", "To Rework", "Done"]
  missing = [s for s in REQUIRED if s not in status_cache]
  IF missing: ABORT "Missing Linear statuses: {missing}. Configure workflow."

3.1 Pre-flight: Settings Verification

Verify .claude/settings.local.json in target project:

• defaultMode = "bypassPermissions" (required for Agent workers spawned by coordinators)

3.2 Worktree Isolation

MANDATORY READ: Load references/git_worktree_fallback.md

branch_check = git branch --show-current
IF branch_check matches feature/* / optimize/* / upgrade/* / modernize/*:
  worktree_dir = CWD
  project_root = CWD
  branch = branch_check
ELSE:
  story_slug = slugify(selected_story.title)
  branch = "feature/{selected_story.id}-{story_slug}"
  worktree_dir = ".hex-skills/worktrees/story-{selected_story.id}"
  project_root = CWD

  changes = git diff HEAD
  IF changes not empty:
    git diff HEAD > .hex-skills/pipeline/carry-changes.patch

  git fetch origin
  base_branch = detect per references/git_scope_detection.md §Base Branch Detection
  git worktree add -b {branch} {worktree_dir} origin/{base_branch}

  IF .hex-skills/pipeline/carry-changes.patch exists:
    git -C {worktree_dir} apply .hex-skills/pipeline/carry-changes.patch && rm .hex-skills/pipeline/carry-changes.patch
    IF apply fails: WARN user "Patch conflicts -- continuing without uncommitted changes"

  cd {worktree_dir}    # All subsequent Skill calls inherit this CWD

Coordinators self-detect feature/* on startup -> skip their own worktree creation (ln-400 Phase 1 step 5).

3.3 Initialize Pipeline State

Bash: node $PIPELINE start \
  --story {selected_story.id} \
  --title "{selected_story.title}" \
  --storage {storage_mode} \
  --project-brief '{JSON.stringify(project_brief)}' \
  --story-briefs '{JSON.stringify(story_briefs)}' \
  --business-answers '{JSON.stringify(business_answers)}' \
  --status-cache '{JSON.stringify(status_cache)}' \
  --skill-repo-path "{skill_repo}" \
  --worktree-dir "{worktree_dir}" \
  --branch-name "{branch}"

IF result.recovery == true:
  # Active run found — resume instead of fresh start
  Jump to Phase 4 using result.state

3.4 Sleep Prevention (Windows only)

IF platform == "win32":
  Bash: cp {skill_repo}/ln-1000-pipeline-orchestrator/references/scripts/hooks/prevent-sleep.ps1 .hex-skills/pipeline/prevent-sleep.ps1
  Bash: powershell -ExecutionPolicy Bypass -WindowStyle Hidden -File .hex-skills/pipeline/prevent-sleep.ps1 &
  sleep_prevention_pid = $!

Phase 4: Pipeline Execution

MANDATORY READ: Load references/phases/phase4_flow.md for ASSERT guards, stage notes, context recovery, and error handling. MANDATORY READ: Load references/checkpoint_format.md for checkpoint schema.

# --- INITIALIZATION ---
id = selected_story.id
target_stage = determine_stage(selected_story)    # pipeline_states.md / guards.mjs

# --- PROGRESS TRACKER (survives compaction) ---
TodoWrite([
  {content: "Stage 0: Task Decomposition (ln-300)", status: "pending", activeForm: "Decomposing tasks"},
  {content: "Stage 1: Validation (ln-310)", status: "pending", activeForm: "Validating story"},
  {content: "Stage 2: Execution (ln-400)", status: "pending", activeForm: "Executing tasks"},
  {content: "Stage 3: Quality Gate (ln-500)", status: "pending", activeForm: "Running quality gate"},
  {content: "Pipeline Report + Cleanup", status: "pending", activeForm: "Generating report"}
])

# --- STAGE 0: Task Decomposition ---
IF target_stage <= 0:
  Bash: node $PIPELINE advance --story {id} --to STAGE_0
  Skill(skill: "ln-300-task-coordinator", args: "{id}")
  Read Stage 0 coordinator artifact -> Bash: node $PIPELINE record-stage-summary --story {id} --payload '{...}'
  ASSERT Stage 0 artifact: status=completed, stage=0
  IF ASSERT fails: Bash: node $PIPELINE record-loop-health --story {id} --stage 0 --payload '{"error":"Stage 0 ASSERT failed","progress_detected":false}'
  Re-read kanban only as secondary assertion
  IF ASSERT fails: Bash: node $PIPELINE pause --story {id} --reason "Stage 0 artifact missing or invalid"; ESCALATE
  Write stage notes: .hex-skills/pipeline/stage_0_notes_{id}.md (Key Decisions, Artifacts)
  Bash: node $PIPELINE checkpoint --story {id} --stage 0 --plan-score {score} --tasks-remaining '{JSON tasks}' --last-action "Tasks created"

# --- STAGE 1: Validation ---
IF target_stage <= 1:
  Bash: node $PIPELINE advance --story {id} --to STAGE_1
  IF advance fails (guard rejection): handle per error.recovery
  Skill(skill: "ln-310-multi-agent-validator", args: "{id}")
  Read Stage 1 coordinator artifact -> Bash: node $PIPELINE record-stage-summary --story {id} --payload '{...}'
  ASSERT artifact verdict = GO and readiness_score >= 5
  IF NO-GO:
    Bash: node $PIPELINE advance --story {id} --to STAGE_1    # retry (guard auto-increments validation_retries)
    IF advance fails: Bash: node $PIPELINE pause --story {id} --reason "Validation retry exhausted"; ESCALATE
    Skill(skill: "ln-310-multi-agent-validator", args: "{id}")    # retry
    Read retry Stage 1 artifact -> Bash: node $PIPELINE record-stage-summary --story {id} --payload '{...}'
  IF same ASSERT failure repeats without new Stage 1 artifact/checkpoint/status evidence:
    Bash: node $PIPELINE record-loop-health --story {id} --stage 1 --payload '{"error":"Stage 1 ASSERT failed","progress_detected":false}'
    IF result.pause.pause == true: ESCALATE using result.state.paused_reason
  Re-read kanban only as secondary assertion
  IF still NOT Todo: Bash: node $PIPELINE pause --story {id} --reason "Validation artifact or status invalid"; ESCALATE
  Extract agents_info from Stage 1 artifact metadata or review runtime state
  Write stage notes: .hex-skills/pipeline/stage_1_notes_{id}.md (Verdict, Agent Review, Key Decisions)
  Bash: node $PIPELINE checkpoint --story {id} --stage 1 --verdict {verdict} --readiness {score} --agents-info "{agents}" --last-action "Validated"

# --- COMPACTION RECOVERY (replaces old COMPACTION GUARD) ---
# If context compacted and vars lost: Bash: node $PIPELINE status --story {id}
# Extract resume_action from JSON -> continue from there. No manual JSON reads needed.

# --- STAGE 2+3 LOOP (rework cycle, managed by CLI guards) ---
WHILE true:

  # STAGE 2: Execution
  IF target_stage <= 2 OR (status shows rework cycle):
    Bash: node $PIPELINE advance --story {id} --to STAGE_2
    IF advance fails: Bash: node $PIPELINE pause --story {id} --reason "{error}"; ESCALATE; BREAK
    Skill(skill: "ln-400-story-executor", args: "{id}")
    Read Stage 2 coordinator artifact -> Bash: node $PIPELINE record-stage-summary --story {id} --payload '{...}'
    ASSERT artifact story_status = To Review
    IF ASSERT fails: Bash: node $PIPELINE record-loop-health --story {id} --stage 2 --payload '{"error":"Stage 2 ASSERT failed","progress_detected":false}'
    Re-read kanban only as secondary assertion
    IF ASSERT fails: Bash: node $PIPELINE pause --story {id} --reason "Stage 2 artifact missing or invalid"; ESCALATE; BREAK
    git_stats = parse `git diff --stat origin/{base_branch}..HEAD`
    Write stage notes: .hex-skills/pipeline/stage_2_notes_{id}.md (Key Decisions, Git commits)
    Bash: node $PIPELINE checkpoint --story {id} --stage 2 --tasks-completed '{JSON done}' --git-stats '{JSON stats}' --last-action "Implementation complete"

  # STAGE 3: Quality Gate (IMPOSSIBLE TO SKIP — next line after Stage 2)
  Bash: node $PIPELINE advance --story {id} --to STAGE_3
  Skill(skill: "ln-500-story-quality-gate", args: "{id}")
  Read Stage 3 coordinator artifact -> Bash: node $PIPELINE record-stage-summary --story {id} --payload '{...}'
  IF repeated identical quality FAIL has no new artifact/task/code delta:
    Bash: node $PIPELINE record-loop-health --story {id} --stage 3 --payload '{"error":"Stage 3 repeated quality FAIL","progress_detected":false}'
    IF result.pause.pause == true: ESCALATE using result.state.paused_reason
  Extract quality verdict, score, agents_info from Stage 3 artifact
  Re-read kanban only as secondary assertion
  Write stage notes: .hex-skills/pipeline/stage_3_notes_{id}.md (Verdict, Score, Agent Review, Branch)
  Bash: node $PIPELINE checkpoint --story {id} --stage 3 --verdict {verdict} --quality-score {score} --agents-info "{agents}" --last-action "Quality gate: {verdict}"

  IF Story status = Done:
    Bash: node $PIPELINE advance --story {id} --to DONE
    BREAK

  IF Story status = To Rework:
    Read Stage 3 artifact `metadata.rework_hint` for blocking_categories and suggested_focus
    Bash: node $PIPELINE advance --story {id} --to STAGE_2    # guard auto-increments quality_cycles
    IF advance fails (quality_cycles >= 2):
      Bash: node $PIPELINE pause --story {id} --reason "Quality gate failed 2 times"
      ESCALATE: "Quality gate failed after max cycles. Manual review needed."
      BREAK
    # Pass rework focus to ln-400:
    Skill(skill: "ln-400-story-executor", args: "{id} --rework-focus {blocking_categories}")
    CONTINUE

  Bash: node $PIPELINE pause --story {id} --reason "Unexpected Stage 3 outcome"
  ESCALATE: "Story ended Stage 3 in unexpected status. Manual review needed."
  BREAK

### Stop Conditions (Quality Cycle)

| Condition | Action |
|-----------|--------|
| All tasks Done + Story = Done | STOP — Story completed successfully |
| `quality_cycles >= 2` | STOP — ESCALATE: "Quality gate failed after max cycles. Manual review needed." |
| Validation retry fails (NO-GO after retry) | STOP — ESCALATE: ask user for direction |
| Stage 2 precondition fails | STOP — ESCALATE: "Stage 2 incomplete, manual intervention needed" |
| Same stage ASSERT failure repeats without new evidence | STOP — runtime `record-loop-health` pauses with actionable reason |

### Phase 5: Cleanup & Report

0. Signal pipeline complete

pre_cleanup_status = Bash: node $PIPELINE status --story {id} IF pre_cleanup_status.state.phase != "DONE": Bash: node $PIPELINE advance --story {id} --to DONE

1. Self-verify against Definition of Done

status = Bash: node $PIPELINE status --story {id} final_state = status.state.phase OR "DONE" verification = { story_selected: status.state.story_id == id story_processed: final_state IN ("DONE", "PAUSED") } IF ANY verification == false: WARN user with details

2. Read stage notes

stage_notes = {} FOR N IN 0..3: IF .hex-skills/pipeline/stage_{N}notes{id}.md exists: stage_notes[N] = read file content ELSE: stage_notes[N] = "(no notes captured)"

3. Extract branch info

branch_name = git branch --show-current git_stats_final = git diff --stat origin/{base_branch}..HEAD (if not already captured)

4. Finalize pipeline report

durations = {N: stage_timestamps.stage_{N}end - stage_timestamps.stage{N}_start FOR N IN 0..3 IF both timestamps exist}

Write docs/tasks/reports/pipeline-{date}.md:

Pipeline Report -- {date}

Story: {id} -- {title} Branch: {branch_name} Final State: {final_state} Duration: {now() - pipeline_start_time}

Task Planning (ln-300)

Tasks	Plan Score	Duration
{N} created	{score}/4	{durations[0]}

{stage_notes[0]}

Validation (ln-310)

Verdict	Readiness	Agent Review	Duration
{verdict}	{score}/10	{agents_info}	{durations[1]}

{stage_notes[1]}

Implementation (ln-400)

Status	Files	Lines	Duration
{result}	{files_changed}	+{added}/-{deleted}	{durations[2]}

{stage_notes[2]}

Quality Gate (ln-500)

Verdict	Score	Agent Review	Rework	Duration
{verdict}	{score}/100	{agents_info}	{quality_cycles}	{durations[3]}

{stage_notes[3]}

Pipeline Metrics

Wall-clock	Rework cycles	Validation retries
{total_duration}	{quality_cycles}	{validation_retries}

5. Show pipeline summary to user

Pipeline Complete:

Story	Branch	Planning	Validation	Implementation	Quality Gate	State
{id}	{branch}	{stage0}	{stage1}	{stage2}	{stage3}	{final_state}

Report saved: docs/tasks/reports/pipeline-{date}.md

6. Worktree cleanup

cd {project_root} IF final_state == "PAUSED" AND worktree_dir exists AND worktree_dir != project_root: git -C {worktree_dir} add -A git -C {worktree_dir} commit -m "WIP: {id} pipeline paused" --allow-empty git -C {worktree_dir} push -u origin {branch} git worktree remove {worktree_dir} --force Display: "Partial work saved to branch {branch} (remote). Worktree cleaned." IF final_state == "DONE" AND worktree_dir exists AND worktree_dir != project_root:

ln-500 committed + pushed in Phase 7. Clean worktree only.

git worktree remove {worktree_dir} --force

7. Stop sleep prevention (Windows)

IF sleep_prevention_pid: kill $sleep_prevention_pid 2>/dev/null || true

8. Remove pipeline state files

Delete .hex-skills/pipeline/ directory

9. Report results location to user

## Coordinator Artifacts as Orchestration Truth

- **Read coordinator artifact first** after each stage completion. Never treat prose output as completion truth
- Re-read board after each stage only as a secondary assertion for expected status transitions
- Coordinators (ln-300/310/400/500) update Linear/kanban via their own logic. Lead verifies the artifact first, then checks board consistency
- **Update algorithm:** Follow `references/kanban_update_algorithm.md` for Epic grouping and indentation

## Error Handling

| Situation | Detection | Action |
|-----------|----------|--------|
| ln-300 task creation fails | Skill returns error | Escalate to user: "Cannot create tasks for Story {id}" |
| ln-310 NO-GO (Score <5) | Stage 1 artifact verdict != GO | Retry once. If still NO-GO -> ask user |
| Task in To Rework 3+ times | ln-400 reports rework loop | Escalate: "Task X reworked 3 times, need input" |
| ln-500 FAIL | Stage 3 artifact verdict = FAIL | Fix tasks auto-created by ln-500. Stage 2 re-entry. Max 2 quality cycles |
| Skill call error | Exception from Skill() | `node $PIPELINE status` -> re-invoke same Skill (runtime + artifacts handle resume) |
| Context compression | PostCompact hook or manual detection | `node $PIPELINE status` -> extract resume_action -> continue |

## Worker Invocation (MANDATORY)

**Host Skill Invocation:** `Skill(skill: "...", args: "...")` is mandatory delegation.
- Claude: call the Skill tool exactly as shown.
- Codex: if no Skill tool exists, locate the named skill in available skills, read its `SKILL.md`, treat `args` as `$ARGUMENTS`, execute that skill workflow, then return here with its result/artifact.
- Do not inline worker logic or mark the worker complete without executing the target skill.

| Stage | Skill | Invocation |
|-------|-------|------------|
| 0 | ln-300-task-coordinator | `Skill(skill: "ln-300-task-coordinator", args: "{id}")` |
| 1 | ln-310-multi-agent-validator | `Skill(skill: "ln-310-multi-agent-validator", args: "{id}")` |
| 2 | ln-400-story-executor | `Skill(skill: "ln-400-story-executor", args: "{id}")` |
| 3 | ln-500-story-quality-gate | `Skill(skill: "ln-500-story-quality-gate", args: "{id}")` |

## TodoWrite format (mandatory)

```text
- Phase 1: Resolve Story and business context (pending)
- Phase 2: Ask targeted business questions only if needed (pending)
- Phase 3: Setup pipeline runtime and worktree state (pending)
- Phase 4: Execute stage 0 -> 3 sequentially with ASSERT guards (pending)
- Phase 5: Write report, clean worktree, and finalize runtime state (pending)
- Phase 6: Run pipeline meta-analysis (pending)

TodoWrite format (mandatory):

{content: "Stage N: {name} (ln-NNN)", status: "pending", activeForm: "{verb}ing"}

Critical Rules

1. Single Story processing. User selects which Story to process
2. Coordinators via Skill. Lead invokes ln-300/ln-310/ln-400/ln-500 via Skill tool. Each coordinator manages its own internal worker dispatch (Agent/Skill)
3. Skills as-is. Never modify or bypass existing skill logic
4. Artifact-first verification. After EVERY Skill call, read coordinator artifact first and re-read kanban only as secondary assertion. Lead never caches stage truth in chat state
5. Quality cycle limit. Max 2 quality FAILs per Story (original + 1 rework). After 2nd FAIL, escalate to user
6. Worktree lifecycle. ln-1000 creates worktree in Phase 3.4. Branch finalization (commit, push) by ln-500. Worktree cleanup by ln-1000 in Phase 5 (lead is in worktree, so ln-500 skips cleanup)
7. Stage notes. Lead writes .hex-skills/pipeline/stage_N_notes_{id}.md after each stage for Pipeline Report
8. Checkpoints. CLI scripts write run-scoped runtime state under .hex-skills/pipeline/runtime/runs/{run_id}/ via node $PIPELINE checkpoint after each stage

Known Issues

Symptom	Likely Cause	Self-Recovery
Lead outputs generic text after long run	Context compression destroyed state vars	node $PIPELINE status -> extract resume_action -> continue from there
ln-400 stuck on same task	Task in rework loop	ln-400 handles internally; escalates after 3 reworks

Anti-Patterns

• Skipping quality gate after execution (Stage 3 is the next line after Stage 2 -- impossible to skip)
• Treating kanban state as the primary completion signal instead of coordinator artifacts
• Running mypy/ruff/pytest directly instead of letting coordinators handle it
• Processing multiple stories without user selection
• Creating worktrees outside Phase 3.4 (coordinators self-detect feature/*)
• Modifying coordinator internal dispatch (ln-400's Agent/Skill pattern is correct as-is)

Plan Mode Support

When invoked in Plan Mode, show available Stories and ask user which one to plan for:

1. Parse kanban board (Phase 1 steps 1-7)
2. Show available Stories table
3. AskUserQuestion: "Which story to plan for? Enter # or Story ID."
4. Execute Phase 2 (pre-flight questions) if business ambiguities found
5. Resolve skill_repo_path -- absolute path to skills repo root
6. Show execution plan for selected Story
7. Write plan to plan file (using format below), call ExitPlanMode

Plan Output Format:

## Pipeline Plan for {date}

> **BEFORE EXECUTING -- MANDATORY READ:** Load `{skill_repo_path}/ln-1000-pipeline-orchestrator/SKILL.md` (full file).
> After reading SKILL.md, start from Phase 3 (Pipeline Setup) using the context below.

**Story:** {ID}: {Title}
**Current Status:** {status}
**Target Stage:** {N} ({skill_name})
**Storage Mode:** {file|linear}
**Project Brief:** {name} ({tech})
**Business Answers:** {answers from Phase 2, or "none"}
**Skill Repo Path:** {skill_repo_path}

### Execution Sequence
1. Read full SKILL.md + references (Phase 3 prerequisites)
2. Setup worktree + initialize CLI-managed pipeline state (Phase 3)
3. Execute stages sequentially via Skill() calls (Phase 4)
4. Generate pipeline report (Phase 5)
5. Cleanup worktree + state files (Phase 5)

Definition of Done (self-verified in Phase 5)

• User selected Story (state.story_id is set)
• Business questions resolved (stored OR skip)
• Story processed to terminal state (state.phase IN ("DONE", "PAUSED"))
• Per-stage ASSERT verifications passed (artifact first, kanban secondary)
• Stage notes written for each completed stage
• Pipeline report generated (file exists at docs/tasks/reports/)
• Pipeline summary shown to user
• Worktree cleaned up (Phase 5 step 6)
• Meta-Analysis run (Phase 6)

Phase 6: Meta-Analysis

MANDATORY READ: Load and references/phases/phase6_meta_analysis.md

Skill type: execution-orchestrator. When requested, run after Phase 5. Pipeline-specific implementation (recovery map, trend tracking, assumption audit, report format) in phase6_meta_analysis.md.

Reference Files

Phase 4-6 Procedures (Progressive Disclosure)

• Pipeline flow: references/phases/phase4_flow.md (ASSERT guards, stage notes, context recovery, error handling)
• Meta-analysis: references/phases/phase6_meta_analysis.md (Recovery map, trend tracking, report format)

Core Infrastructure

• MANDATORY READ: Load references/git_worktree_fallback.md
• MANDATORY READ: Load references/research_tool_fallback.md
• Pipeline states: references/pipeline_states.md
• Checkpoint format: references/checkpoint_format.md
• Kanban parsing: references/kanban_parser.md
• Kanban update algorithm: references/kanban_update_algorithm.md
• Settings template: references/templates/settings_template.json
• Sleep prevention: references/scripts/hooks/prevent-sleep.ps1
• Environment state: references/environment_state_contract.md
• Storage mode operations: references/storage_mode_detection.md
• Auto-discovery patterns: references/auto_discovery_pattern.md

Delegated Skills

• ../ln-300-task-coordinator/SKILL.md
• ../ln-310-multi-agent-validator/SKILL.md
• ../ln-400-story-executor/SKILL.md
• ../ln-500-story-quality-gate/SKILL.md

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Version: 3.0.0 Last Updated: 2026-03-19