/large-plan
Scaffold and execute folder-based multi-phase plans with async agent collaboration. Use when planning large features, multi-PR workflows, or coordinating parallel agent work across phases. NOT for: single-file changes, simple bugs, quick tasks.
$ golems-cli skills install large-planUpdated 2 weeks ago
Invoke as: /large-plan (single segment).
Source: ~/Gits/golems/skills/golem-powers/large-plan/ (symlinked at ~/.claude/commands/large-plan).
Scaffold folder-based plans with phase folders, execute them through the branch-PR-review cycle, and coordinate async agent collaboration.
Quick Actions
| What you want to do | Workflow |
|---|---|
| Create a new plan from a description | workflows/scaffold.md |
| Execute the next phase in a plan | workflows/execute-phase.md |
| Start async collab on a phase | workflows/collab.md |
Available Scripts
| Script | Purpose | Usage |
|---|---|---|
scripts/scaffold-plan.sh | Create folder-based plan structure | bash scripts/scaffold-plan.sh <plan-dir> <plan-name> <phase-count> |
Core Concept
Large plans are folder-based: one folder per phase, each containing a README.md (steps) and findings.md (shared knowledge). A main README.md acts as the index with a progress table and routing.
plan-dir/
README.md # Index: progress table, routing, execution rules
collab.md # Created when parallel phases exist (see below)
phase-1-name/
README.md # Steps for this phase
findings.md # Shared knowledge room (agents write here)
phase-2-name/
README.md
findings.md
...
Execution Decision: Sequential vs Parallel
EVERY plan must decide this at scaffold time. Analyze the dependency graph:
Phases with NO cross-dependencies → Parallel (collab.md + multiple agents)
Phases that depend on each other → Sequential (execute-phase, one at a time)
Mixed → Rounds (parallel within round, sequential between rounds)
Decision tree:
- Draw the dependency graph from phase
Depends Onfields - Group independent phases into rounds (phases in the same round can run in parallel)
- If ANY round has 2+ phases → create
collab.mdat plan root - Add
## Execution Strategyto the main README.md showing rounds and parallelism
Example:
Full SKILL.md source — includes LLM directives, anti-patterns, and technical instructions stripped from the Overview tab.
Invoke as: /large-plan (single segment).
Source: ~/Gits/golems/skills/golem-powers/large-plan/ (symlinked at ~/.claude/commands/large-plan).
Scaffold folder-based plans with phase folders, execute them through the branch-PR-review cycle, and coordinate async agent collaboration.
Quick Actions
| What you want to do | Workflow |
|---|---|
| Create a new plan from a description | workflows/scaffold.md |
| Execute the next phase in a plan | workflows/execute-phase.md |
| Start async collab on a phase | workflows/collab.md |
Available Scripts
| Script | Purpose | Usage |
|---|---|---|
scripts/scaffold-plan.sh | Create folder-based plan structure | bash scripts/scaffold-plan.sh <plan-dir> <plan-name> <phase-count> |
Core Concept
Large plans are folder-based: one folder per phase, each containing a README.md (steps) and findings.md (shared knowledge). A main README.md acts as the index with a progress table and routing.
plan-dir/
README.md # Index: progress table, routing, execution rules
collab.md # Created when parallel phases exist (see below)
phase-1-name/
README.md # Steps for this phase
findings.md # Shared knowledge room (agents write here)
phase-2-name/
README.md
findings.md
...
Execution Decision: Sequential vs Parallel
EVERY plan must decide this at scaffold time. Analyze the dependency graph:
Phases with NO cross-dependencies → Parallel (collab.md + multiple agents)
Phases that depend on each other → Sequential (execute-phase, one at a time)
Mixed → Rounds (parallel within round, sequential between rounds)
Decision tree:
- Draw the dependency graph from phase
Depends Onfields - Group independent phases into rounds (phases in the same round can run in parallel)
- If ANY round has 2+ phases → create
collab.mdat plan root - Add
## Execution Strategyto the main README.md showing rounds and parallelism
Example:
## Execution Strategy
| Round | Phases | Mode | Agents |
|-------|--------|------|--------|
| 1 | Phase 1, Phase 2 | **parallel** (collab) | brainClaude, golemsClaude |
| 2 | Phase 3 (depends on 1+2) | sequential | mainClaude |
| 3 | Phase 4, Phase 5 | **parallel** (collab) | brainClaude, golemsClaude |When a round has parallel phases, the orchestrator:
- Creates/updates
collab.mdusing the collab protocol - Spawns one agent per phase (Task tool or CLI agents)
- Each agent's kickoff prompt includes the collab.md path
- Orchestrator monitors collab.md and advances rounds when all phases are done
Plan Lifecycle
Scaffold plan → Analyze dependencies → Group into rounds
|
┌───────────────────────────┘
▼
Round has 1 phase? → Execute sequentially (execute-phase)
Round has 2+ phases? → Create collab.md, spawn agents in parallel
|
▼
All round phases done → Advance to next round → Repeat
Branch Lifecycle (per phase)
master -> feature/phase-N-name -> implement -> commit -> push -> PR
^ |
|__ merge <-- approve <-- fix <-- review (CodeRabbit + Cursor Bugbot + DeepSource)
Phase Template
Each phase README follows this template:
# Phase N: Name
> [Back to main plan](../README.md)
## Goal
One sentence describing what this phase achieves.
## Round
Round M (parallel with Phase X, Phase Y) OR Round M (sequential).
## Tools
- **Research:** [gemini|cursor|codex] — what to research
- **Code:** [cursor|haiku|sonnet] — what to implement
- **MCPs:** [list relevant MCP servers]
## Steps
1. Step one
2. Step two
3. ...
## Depends On
- Phase X (for Y reason)
## Status
- [ ] Step one
- [ ] Step twoFindings Template
Each phase findings.md is the shared collaboration room:
# Phase N Findings
## Decisions
- [timestamp] Decision: ...
## Research
- [timestamp] Agent: Found that ...
## Task Board
| Task | Owner | Status |
|------|-------|--------|
| Research X | gemini | done |
| Implement Y | cursor | in progress |Parallel Execution (Collab Protocol)
When a round has 2+ independent phases, use the full collab protocol defined in workflows/collab.md.
The orchestrator MUST:
- Create
collab.mdat plan root using the template from the collab workflow - Fill in all mandatory sections (Goal, Agents, Task Board, Constraints, Gates)
- Spawn agents with collab path in their kickoff prompt
- Monitor collab.md and advance rounds when all agents report
done
Key rule: If the human has to tell you to update the collab file, the collab has failed. Agents must self-coordinate.
Complexity tiers (from collab workflow):
- Lightweight (~40 lines): 2 agents, fully independent work
- Standard (~100 lines): 2-3 agents, some dependencies
- Complex (~200 lines): 3+ agents, multi-repo, round-based
See workflows/collab.md for the full protocol, mandatory sections, update gates, message format, and anti-patterns.
Integration with Other Skills (Building Blocks)
MANDATORY for every phase:
| Skill | When | Why |
|---|---|---|
/pr-loop | Every phase completion | The FULL loop — branch through MERGED. Not optional. |
/superpowers:test-driven-development | All implementation | Red-green-refactor. No code without failing test first. |
/superpowers:verification-before-completion | Before claiming "done" | Evidence before assertions. Always. |
/never-fabricate | Before reporting results | Read() files before summarizing them. |
Optional per phase:
| Skill | When to use |
|---|---|
/critique-waves | Verify phase output with parallel agents |
/test-plan | Generate test plans per phase |
/prd | Create PRDs from phase specs |
/commit | CodeRabbit review + atomic commit (step 5 of pr-loop) |
/create-pr | Create PR (step 7 of pr-loop) |
PR Review Cycle (per phase)
After push, automated reviewers comment. Classify each:
| Type | Action |
|---|---|
| Real bug | FIX immediately |
| Style preference | Fix if genuinely better |
| Over-engineering | SKIP |
| Out of context | Comment explaining why |
Repeat push-fix cycle until no real bugs remain.
Platform Features vs Universal Fallbacks
Claude Code features are listed first. If running on Codex or Cursor, use the universal fallback. Full adapter docs: adapters/
| Feature | Claude Code | Universal Fallback |
|---|---|---|
| Parallel phase agents | Agent(isolation="worktree", run_in_background=true) | Spawn CLI agents manually: cd <wt> && codex --full-auto "phase N" |
| Phase worktree isolation | Agent(isolation="worktree") — auto-creates + cleans up | git worktree add -b feature/phase-N ../<dir> master |
| Collab file monitoring | CronCreate or /loop 5m | nohup bash -c 'while true; do grep done collab.md; sleep 300; done' & |
| Cron cleanup (plan done) | CronDelete(<id>) — mandatory | kill <bg-monitor-pid> |
| Plan mode (spec first) | EnterPlanMode → ExitPlanMode | Write plan to docs.local/plan/<name>/README.md manually |
| Memory persistence | brain_store() / brain_search() via BrainLayer | Append to <plan-dir>/findings.md |
| Session resume | claude --resume | Not available — pass <plan-dir>/README.md in next session's context |
| Background phase execution | Agent(run_in_background=true) | nohup codex --full-auto "..." > phase.log 2>&1 & |
Quality Gates (before marking phase done)
| Gate | Check |
|---|---|
| Typed right | No any, proper interfaces |
| Documented | JSDoc on exports, CLAUDE.md updated if needed |
| DRY | No duplicated logic |
| Tests pass | bun test / npm test green |
| Build passes | No compile errors |
Best Pass Rate
100%
Opus 4.6
Assertions
11
3 models tested
Avg Cost / Run
$0.1998
across models
Fastest (p50)
2.7s
Sonnet 4.6
Behavior Evals
Phase 2 baseline — skill quality on ClaudeBehavior Baseline
| Assertion | Opus 4.6 | Sonnet 4.6 | Haiku 4.5 | Consensus |
|---|---|---|---|---|
| scaffolds-folder-structure | 3/3 | |||
| includes-phase-dependencies | 3/3 | |||
| pr-loop-per-phase | 3/3 | |||
| includes-quality-gates | 3/3 | |||
| references-tdd | 3/3 | |||
| refuses-to-skip-quality-gate | 2/3 | |||
| suggests-scope-reduction | 3/3 | |||
| maintains-pr-loop | 3/3 | |||
| spawns-parallel-agents | 3/3 | |||
| uses-collab-files | 2/3 | |||
| defines-merge-strategy | 3/3 |
Token Usage
Cost per Run
| Model | Input Tokens | Output Tokens | Cost / Run | Cost / 1K Runs |
|---|---|---|---|---|
| Opus 4.6 | 6,921 | 5,421 | $0.5104 | $510.40 |
| Sonnet 4.6 | 5,135 | 4,777 | $0.0871 | $87.10 |
| Haiku 4.5 | 1,708 | 1,254 | $0.0020 | $2.00 |
Response Time (p50)
Response Time (p95)
| Model | p50 | p95 | Overhead |
|---|---|---|---|
| Opus 4.6 | 7.8s | 14.8s | +90% |
| Sonnet 4.6 | 2.7s | 4.2s | +55% |
| Haiku 4.5 | 2.9s | 4.9s | +67% |
Last evaluated: 2026-03-12 · Data is generated from skill assertions (real cross-model benchmarks coming soon)
Changelog entries are derived from eval runs and skill version updates. Full cascading changelog (Phase 4D) coming soon.
Best Pass Rate
100%
Assertions
11
Models Tested
3
Evals Run
3
- +Initial release to Golems skill library
- +11 assertions across 3 eval scenarios
- +3 workflows included: scaffold, collab, execute-phase