| 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.
- Auto-discover
docs/tasks/kanban_board.md (or Linear API via storage mode operations)
- 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" }
- Parse all status sections: Backlog, Todo, In Progress, To Review, To Rework
- Extract Story list with: ID, title, status, Epic name, task presence
- Filter: skip Stories in Done, Postponed, Canceled
- Detect task presence per Story:
- Has
_(tasks not created yet)_ -> no tasks -> Stage 0
- Has task lines (4-space indent) -> tasks exist -> Stage 1+
- Determine target stage per Story (see
references/pipeline_states.md Stage-to-Status Mapping)
- 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."
- 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)
- Load selected Story description (metadata only)
- 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)
- Collect ALL business questions into single AskUserQuestion
- 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
- Single Story processing. User selects which Story to process
- 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)
- Skills as-is. Never modify or bypass existing skill logic
- 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
- Quality cycle limit. Max 2 quality FAILs per Story (original + 1 rework). After 2nd FAIL, escalate to user
- 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)
- Stage notes. Lead writes
.hex-skills/pipeline/stage_N_notes_{id}.md after each stage for Pipeline Report
- 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:
- Parse kanban board (Phase 1 steps 1-7)
- Show available Stories table
- AskUserQuestion: "Which story to plan for? Enter # or Story ID."
- Execute Phase 2 (pre-flight questions) if business ambiguities found
- Resolve
skill_repo_path -- absolute path to skills repo root
- Show execution plan for selected Story
- 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)
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
Version: 3.0.0
Last Updated: 2026-03-19
