deep-plan

name	deep-plan
description	Research-validated planning — research → plan → verify cycle for high-confidence implementation plans
scope	core
context	fork
version	1.0.0
user-invocable	true
argument-hint	<topic-or-issue>
teams-compatible	true

Deep Plan Skill

Research-validated planning that eliminates the gap between research assumptions and actual code. Orchestrates a 3-phase cycle: Discovery Research → Reality-Check Planning → Plan Verification.

Teams-compatible — works both from the main conversation (R010) and inside Agent Teams members. When used in Teams, the member directly executes the 3-phase workflow without Skill tool invocation.

Usage

/deep-plan <topic-or-issue>
/deep-plan "implement caching layer for API responses"
/deep-plan #325 new authentication system
/deep-plan Rust async runtime migration

Problem Solved

Research-only analysis (like /research) produces findings based on assumptions about the codebase. These assumptions often diverge from reality:

Assumption	Reality	Impact
"Feature X is missing"	Already implemented	Wasted effort on duplicate work
"Pattern Y is needed"	Partially exists	Over-engineering existing code
"Library Z is required"	Already a dependency	Unnecessary integration effort

/deep-plan solves this by cross-referencing research findings against actual code before committing to a plan.

Architecture — 3 Phases

Phase 1: Discovery Research

Invoke the /research skill internally for comprehensive topic analysis.

Phase 1: Discovery Research
├── Skill(research, args="<topic>")
├── 10-team parallel analysis (3 batches × 4/4/2)
├── Cross-verification loop (opus + codex)
├── ADOPT / ADAPT / AVOID taxonomy
└── Output: research report (artifact)

Execution:

• Orchestrator mode: Delegates to /research skill via Skill(research, args="<topic>").
• Teams mode: Executes the research workflow inline (see Teams Mode section). The member spawns research teams directly as sub-agents.

The executor waits for completion before proceeding to Phase 2.

Output: Full research report with ADOPT/ADAPT/AVOID taxonomy.

Phase 2: Reality-Check Planning

Ground-truth the research findings against the actual codebase.

Phase 2: Reality-Check Planning
├── EnterPlanMode
├── Explore agents (up to 3 parallel)
│   ├── Explore 1: Verify ADOPT items exist/don't exist
│   ├── Explore 2: Check ADAPT items for current state
│   └── Explore 3: Validate AVOID alternatives
├── Gap analysis table
├── Refined plan (real gaps only)
└── ExitPlanMode → user approval

Steps:

1. Enter Plan Mode: EnterPlanMode to activate planning context

2. Codebase Exploration: Spawn up to 3 Explore agents in parallel to verify research assumptions:

   • Each ADOPT item: Does it already exist? Partially implemented?
   • Each ADAPT item: What is the current state to adapt from?
   • Each AVOID item: Are the alternatives already available?

3. Gap Analysis: Build a reconciliation table:

   | Research Finding | Actual Code State | Gap Type | Action |
   |-----------------|-------------------|----------|--------|
   | "No caching"    | Redis client exists | Overestimate | Remove from plan |
   | "Need auth middleware" | No auth layer | Real gap | Keep in plan |
   | "Migrate to v3" | Already on v3.1 | Overestimate | Remove from plan |
   | "Add rate limiting" | Basic limiter exists | Partial gap | Adapt existing |
   

4. Refined Plan: Write implementation plan containing ONLY real gaps:

   • Remove overestimates (already implemented)
   • Adjust partial gaps (adapt, don't rebuild)
   • Prioritize real gaps by impact

5. User Approval: ExitPlanMode presents the refined plan for user review

Phase 3: Plan Verification Research

Validate the refined plan with focused research before implementation begins.

Phase 3: Plan Verification Research
├── 3-team focused verification
│   ├── T1: Technical feasibility
│   ├── T2: Conflict/duplication check
│   └── T3: Test strategy & risk
├── Verdict: PASS or REVISE
├── PASS → implementation advisory
└── REVISE → return to Phase 2

Teams (3 parallel, NOT full 10-team):

Team	Focus	Verifies
T1	Technical feasibility	Can the plan be implemented with current stack/deps?
T2	Conflict & duplication	Does the plan conflict with in-flight work or duplicate existing code?
T3	Test strategy & risk	Is the plan testable? What are the failure modes?

Invocation: Phase 3 teams are spawned directly as parallel agents (NOT via Skill(research)). The orchestrator creates 3 focused agents, each with a specific verification mandate derived from the Phase 2 plan.

Model selection: sonnet for teams, opus for synthesis.

Verdict:

• PASS: Plan is verified. Display implementation advisory.
• REVISE: Issues found. Return to Phase 2 with feedback for plan refinement.
• REVISE limit: After 2 REVISE cycles, escalate to user for manual judgment.

Workflow Diagram

User: /deep-plan "topic"
  │
  ├─ Phase 1: Discovery Research
  │   ├─ Skill(research, args="topic")
  │   ├─ 10-team analysis → ADOPT/ADAPT/AVOID
  │   └─ Output: research artifact
  │
  ├─ Phase 2: Reality-Check Planning
  │   ├─ EnterPlanMode
  │   ├─ Explore agents (up to 3 parallel)
  │   ├─ Gap analysis: research vs actual code
  │   ├─ Refined plan (real gaps only)
  │   └─ ExitPlanMode → user approval
  │
  └─ Phase 3: Plan Verification
      ├─ 3-team focused research
      ├─ Verdict: PASS or REVISE
      ├─ PASS → implementation advisory
      └─ REVISE → loop back to Phase 2 (max 2 cycles)

Differentiation

Skill	Scope	Code Verification	Phases
/research	Analysis only	None — assumption-based	1
Plan mode	Planning only	Yes — code exploration	1
/structured-dev-cycle	Full implementation	Yes — stage-by-stage	6
/deep-plan	Analysis + Planning + Verification	3-pass cross-verification	3

/deep-plan fills the gap between research (which lacks code grounding) and implementation (which lacks upfront analysis). It produces a verified plan ready for execution.

Display Format

Before execution:

[Deep Plan] {topic}
├── Phase 1: Discovery Research (10 teams, 3 batches)
├── Phase 2: Reality-Check Planning (up to 3 Explore agents)
└── Phase 3: Plan Verification (3 focused teams)

Estimated phases: 3 | Models: sonnet → opus
Execute? [Y/n]

Phase transitions:

[Deep Plan] Phase 1/3 — Discovery Research
├── Research skill active...
└── Awaiting 10-team results

[Deep Plan] Phase 2/3 — Reality-Check Planning
├── Gap analysis: 6 ADOPT items → 2 real gaps, 4 overestimates
└── Refined plan: 5 action items (down from 12)

[Deep Plan] Phase 3/3 — Plan Verification
├── T1 (feasibility): ✓ PASS
├── T2 (conflicts): ✓ PASS
├── T3 (test/risk): ✓ PASS
└── Verdict: PASS — ready for implementation

Post-Completion Advisory

After PASS verdict:

[Advisory] Verified plan ready for implementation.
├── For complex implementations (10+ files): /structured-dev-cycle
├── For parallel task execution: superpowers:subagent-driven-development
└── For simple tasks (< 3 files): proceed directly

Execution Rules

Rule	Detail
Phase 1	Full /research skill invocation (10 teams)
Phase 2	Max 3 parallel Explore agents (R009)
Phase 3	Max 3 parallel verification teams (R009)
Orchestrator only	Main conversation manages all phases (R010)
Intent display	Show phase plan before execution (R015)
Ecomode	Auto-activate for team result aggregation (R013)
REVISE limit	Max 2 cycles before user escalation

Agent Teams (R018)

When Agent Teams is enabled, Phase 1 and Phase 3 parallel teams SHOULD use Agent Teams instead of individual Agent tool calls:

Phase	Without Agent Teams	With Agent Teams
Phase 1	Delegates to /research (handles internally)	Delegates to /research (handles internally)
Phase 2	Up to 3 Explore agents via Agent tool	Up to 3 Explore agents via Agent tool (below threshold)
Phase 3	3 agents via Agent tool	3 agents — at threshold, prefer Agent Teams for coordination

Phase 1 delegation to /research means Agent Teams decisions are handled by the research skill itself. Phase 3's 3-team verification is at the Agent Teams threshold (3+ agents) and benefits from peer messaging for cross-verification.

Model Selection

Phase	Component	Model	Rationale
Phase 1	Research teams	sonnet	Delegated to /research skill
Phase 1	Verification	opus	Delegated to /research skill
Phase 2	Explore agents	haiku	Fast codebase search
Phase 2	Gap analysis	opus	Complex reconciliation reasoning
Phase 3	Verification teams	sonnet	Balanced analysis
Phase 3	Synthesis/verdict	opus	Final judgment

Cost Estimate

Phase	Approximate Cost	Driver
Phase 1	High	Full 10-team /research invocation
Phase 2	Low-Medium	Up to 3 Explore agents (haiku) + 1 opus synthesis
Phase 3	Medium	3 sonnet verification teams + 1 opus synthesis
Total	High	Dominated by Phase 1 research cost

/deep-plan is designed for high-stakes decisions where plan quality justifies the cost. For quick planning, use EnterPlanMode directly.

Integration

Component	Integration
/research	Phase 1 full invocation (via Skill tool or inline in Teams mode) + Phase 3 reduced invocation pattern
EnterPlanMode/ExitPlanMode	Phase 2 plan creation and user approval
Explore agents	Phase 2 codebase verification (up to 3 parallel)
R009	Phase 1 (10 teams batched), Phase 2 (3 Explore), Phase 3 (3 teams)
R010	Orchestrator manages all 3 phases; teams are subagents
R013	Ecomode for team result aggregation
R015	Phase transition intent display
result-aggregation	Phase 1 and 3 result formatting
superpowers:subagent-driven-development	Post-PASS implementation advisory (external plugin)

Fallback Behavior

Scenario	Fallback
Phase 1 /research fails	Manual analysis, then proceed to Phase 2
Phase 2 EnterPlanMode unavailable	Perform analysis without plan mode context
Phase 3 REVISE ≥ 2 times	Escalate to user for manual judgment
Explore agent failure	Reduce parallel count, retry with remaining
Partial team failure	Synthesize from available results, note gaps

Teams Mode

When running inside an Agent Teams member (not via Skill tool), the deep-plan workflow operates identically but with these adaptations:

How It Works

The orchestrator reads this SKILL.md and includes the deep-plan instructions directly in the Teams member's prompt. The member then:

1. Phase 1: Executes research workflow inline (not via Skill(research)) — spawns 10 research teams as sub-agents
2. Phase 2: Uses EnterPlanMode/ExitPlanMode and Explore agents normally
3. Phase 3: Spawns 3 verification teams as sub-agents
4. Delivers final verified plan via SendMessage to team lead

Prompt Embedding Pattern

# When spawning a Teams member for deep-plan:
Agent(
  name: "planner-1",
  team_name: "my-team",
  prompt: """
  You are a deep-plan agent. Follow the deep-plan skill workflow below:
  {contents of deep-plan/SKILL.md}

  Also follow this research workflow for Phase 1:
  {contents of research/SKILL.md}

  Topic: {user's planning topic}
  Deliver verified plan via SendMessage to team lead when complete.
  """
)

Differences from Orchestrator Mode

Aspect	Orchestrator Mode	Teams Mode
Invocation	Skill(deep-plan)	Prompt embedding
Phase 1 research	Skill(research)	Inline execution
Result delivery	Return to main conversation	SendMessage to team lead
Plan approval	User via ExitPlanMode	Team lead via SendMessage
Context isolation	Previously used context: fork	Standard context (no fork)

Why No context: fork

context: fork was removed to enable Teams compatibility. Fork blocks sub-agent spawning, which is essential for Phase 1 (10 research teams) and Phase 3 (3 verification teams). Without fork, deep-plan operates in the standard context, which is required for both orchestrator and Teams usage.

Artifact Persistence

Phase 1 research artifact is persisted by the /research skill.

Phase 3 verification report is persisted by the final synthesis agent:

.claude/outputs/sessions/{YYYY-MM-DD}/deep-plan-{HHmmss}.md

With metadata header:

---
skill: deep-plan
date: {ISO-8601 with timezone}
query: "{original user query}"
phases_completed: 3
verdict: PASS|REVISE
---