loop-planner
Evaluate-Loop Step 1: PLAN. Use this agent when starting a new track or feature to create a detailed execution plan. Reads spec.md, loads project context, and produces a phased plan.md with specific tasks, acceptance criteria, and dependencies. Triggered by: 'plan feature', 'create plan', 'start track', '/conductor implement' (planning phase).
Packaged view
This page reorganizes the original catalog entry around fit, installability, and workflow context first. The original raw source lives below.
Install command
npx @skill-hub/cli install ibrahim-3d-conductor-orchestrator-superpowers-loop-planner
Repository
Skill path: skills/loop-planner
Evaluate-Loop Step 1: PLAN. Use this agent when starting a new track or feature to create a detailed execution plan. Reads spec.md, loads project context, and produces a phased plan.md with specific tasks, acceptance criteria, and dependencies. Triggered by: 'plan feature', 'create plan', 'start track', '/conductor implement' (planning phase).
Open repositoryBest for
Primary workflow: Research & Ops.
Technical facets: Full Stack.
Target audience: everyone.
License: Unknown.
Original source
Catalog source: SkillHub Club.
Repository owner: Ibrahim-3d.
This is still a mirrored public skill entry. Review the repository before installing into production workflows.
What it helps with
- Install loop-planner into Claude Code, Codex CLI, Gemini CLI, or OpenCode workflows
- Review https://github.com/Ibrahim-3d/conductor-orchestrator-superpowers before adding loop-planner to shared team environments
- Use loop-planner for development workflows
Works across
Favorites: 0.
Sub-skills: 0.
Aggregator: No.
Original source / Raw SKILL.md
---
name: loop-planner
description: "Evaluate-Loop Step 1: PLAN. Use this agent when starting a new track or feature to create a detailed execution plan. Reads spec.md, loads project context, and produces a phased plan.md with specific tasks, acceptance criteria, and dependencies. Triggered by: 'plan feature', 'create plan', 'start track', '/conductor implement' (planning phase)."
---
# Loop Planner Agent — Step 1: PLAN
Creates detailed, scoped execution plans for tracks. This is Step 1 of the Evaluate-Loop.
## Inputs Required
1. Track `spec.md` — what needs to be built
2. `conductor/tracks.md` — what's already been done (to avoid overlap)
3. Track `plan.md` (if exists) — check for prior progress
## Workflow
### 1. Load Context
read_file in order:
1. `conductor/tracks.md` — completed tracks and their deliverables
2. Track's `spec.md` — requirements for this track
3. Track's `plan.md` (if exists) — check what's already `[x]` done
4. `conductor/product.md` — product scope reference
5. `conductor/tech-stack.md` — technical constraints
### 2. Identify Scope Boundaries
Before writing any plan:
- List what `spec.md` asks for (deliverables)
- List what's already done in other tracks (from `tracks.md`)
- Identify overlap — anything in spec that was already delivered elsewhere
- Flag overlap items as "SKIP — already done in [TRACK-ID]"
### 3. Create Phased Plan with DAG
write_file `plan.md` with this structure (now includes dependency DAG for parallel execution):
```markdown
# [Track Name] — Execution Plan
## Context
- **Track**: [ID]
- **Spec**: [one-line summary]
- **Dependencies**: [list prerequisite tracks]
- **Overlap Check**: [tracks checked, conflicts found/none]
- **Execution Mode**: PARALLEL | SEQUENTIAL
## Dependency Graph
<!-- YAML DAG for parallel execution -->
```yaml
dag:
nodes:
- id: "1.1"
name: "Task name"
type: "code" # code | ui | integration | test | docs | config
files: ["src/path/to/file.ts"]
depends_on: []
estimated_duration: "30m"
phase: 1
- id: "1.2"
name: "Another task"
type: "code"
files: ["src/another/file.ts"]
depends_on: []
phase: 1
- id: "1.3"
name: "Depends on 1.1 and 1.2"
type: "code"
files: ["src/path/to/file.ts"]
depends_on: ["1.1", "1.2"]
phase: 1
parallel_groups:
- id: "pg-1"
tasks: ["1.1", "1.2"]
conflict_free: true
- id: "pg-2"
tasks: ["1.3", "1.4"]
conflict_free: false
shared_resources: ["src/path/to/file.ts"]
coordination_strategy: "file_lock"
```
## Phase 1: [Phase Name]
### Tasks
- [ ] Task 1.1: [Specific action] <!-- deps: none, parallel: pg-1 -->
- **Type**: code
- **Acceptance**: [How to verify this is done]
- **Files**: [Expected files to create/modify]
- [ ] Task 1.2: [Specific action] <!-- deps: none, parallel: pg-1 -->
- **Type**: code
- **Acceptance**: [How to verify]
- **Files**: [Expected files]
- [ ] Task 1.3: [Depends on above] <!-- deps: 1.1, 1.2 -->
- **Type**: code
- **Acceptance**: [How to verify]
- **Files**: [Expected files]
## Phase 2: [Phase Name]
...
## Discovered Work
<!-- Add items here during execution if scope expansion is needed -->
```
### 3.1 DAG Generation Algorithm
When creating the plan, build the dependency graph:
```python
def generate_dag(tasks: list) -> dict:
"""
Generate DAG from task list.
1. Create nodes for each task
2. Analyze dependencies (explicit + file-based)
3. Identify parallel groups (tasks at same level with no conflicts)
4. Detect shared resources
"""
nodes = []
for task in tasks:
nodes.append({
"id": task['id'],
"name": task['name'],
"type": determine_task_type(task),
"files": task.get('files', []),
"depends_on": task.get('depends_on', []),
"estimated_duration": estimate_duration(task),
"phase": task['phase']
})
# Build adjacency list
dependents = defaultdict(list)
for node in nodes:
for dep in node['depends_on']:
dependents[dep].append(node['id'])
# Compute topological levels
levels = compute_topological_levels(nodes)
# Group tasks by level for parallel execution
parallel_groups = []
for level_num, level_tasks in enumerate(levels):
if len(level_tasks) >= 2:
# Analyze file conflicts
file_usage = defaultdict(list)
for task_id in level_tasks:
task = next(n for n in nodes if n['id'] == task_id)
for f in task.get('files', []):
file_usage[f].append(task_id)
# Find conflict-free groups
shared_files = {f: tasks for f, tasks in file_usage.items() if len(tasks) > 1}
if not shared_files:
parallel_groups.append({
"id": f"pg-{level_num + 1}",
"tasks": level_tasks,
"conflict_free": True
})
else:
parallel_groups.append({
"id": f"pg-{level_num + 1}",
"tasks": level_tasks,
"conflict_free": False,
"shared_resources": list(shared_files.keys()),
"coordination_strategy": "file_lock"
})
return {
"nodes": nodes,
"parallel_groups": parallel_groups
}
```
### 3.2 Task Type Detection
Automatically detect task type from description and files:
| Indicators | Type |
|------------|------|
| `src/components/`, `.tsx`, `ui`, `component` | `ui` |
| `api/`, `integration`, `supabase`, `stripe` | `integration` |
| `.test.ts`, `test`, `coverage` | `test` |
| `.md`, `docs`, `documentation` | `docs` |
| `config`, `.json`, `.env` | `config` |
| Default | `code` |
### 3.3 Parallel Group Identification
Tasks can run in parallel if:
1. No dependency relationship (neither depends on the other)
2. At the same topological level
3. Either:
- No shared files (conflict_free: true)
- Shared files with coordination strategy (conflict_free: false)
### 4. Plan Quality Checklist
Before finalizing, verify:
| Check | Question |
|-------|----------|
| Scoped | Does every task trace back to a `spec.md` requirement? |
| No Overlap | Does any task duplicate work from completed tracks? |
| Testable | Does every task have clear acceptance criteria? |
| Ordered | Are tasks sequenced by dependency? |
| Sized | Can each task be completed in a single session? |
### 5. Output
Save the plan to the track's `plan.md` and report:
```
## Plan Created
**Track**: [track-id]
**Phases**: [count]
**Tasks**: [total count]
**Dependencies**: [list]
**Ready for**: Step 2 (Evaluate Plan) → hand off to loop-plan-evaluator
```
## Metadata Checkpoint Updates
The planner MUST update the track's `metadata.json` at key points:
### On Start
```json
{
"loop_state": {
"current_step": "PLAN",
"step_status": "IN_PROGRESS",
"step_started_at": "[ISO timestamp]",
"checkpoints": {
"PLAN": {
"status": "IN_PROGRESS",
"started_at": "[ISO timestamp]",
"agent": "loop-planner"
}
}
}
}
```
### On Completion
```json
{
"loop_state": {
"current_step": "EVALUATE_PLAN",
"step_status": "NOT_STARTED",
"checkpoints": {
"PLAN": {
"status": "PASSED",
"started_at": "[start timestamp]",
"completed_at": "[ISO timestamp]",
"agent": "loop-planner",
"commit_sha": "[if plan was committed]",
"plan_version": 1
},
"EVALUATE_PLAN": {
"status": "NOT_STARTED"
}
}
}
}
```
### Update Protocol
1. read_file current `metadata.json`
2. Update `loop_state.checkpoints.PLAN` fields
3. Advance `current_step` to `EVALUATE_PLAN`
4. write_file back to `metadata.json`
If `metadata.json` doesn't exist or is v1 format, create v2 structure with default values.
## Handoff
After creating the plan, the **Conductor** should dispatch the **loop-plan-evaluator** agent to verify the plan before execution begins.