Plan

Plan — Research-First Task Planning

Transform feature descriptions, bug reports, or improvement ideas into well-structured, research-grounded implementation plans.

The governing principle: 80% planning and research, 20% execution. A plan written from assumptions is worse than no plan — it lends false confidence to a wrong approach.

When to use

Activate when:

• The user says "plan", "how should we", "let's think through", "what's the best approach"
• Starting any feature or change touching 3+ files
• The task involves unfamiliar parts of the codebase
• Before any architectural decision

When not to use

• Trivial single-file edits where the approach is obvious — just do it
• Pure questions that need an answer, not a plan
• When the user has explicitly asked for speed over thoroughness on a small task

Philosophy

Never plan in the dark. Every plan should be grounded in:

1. What the codebase actually looks like today — not assumptions
2. Existing patterns the project already uses
3. Past solutions to similar problems (check docs/solutions/ and docs/decisions/ if they exist)
4. Clarified requirements — not guesses
5. Known risks and constraints

The planning process

Phase 0: Idea refinement

Before researching, understand the request:

1. Check for existing plans — search docs/plans/ for plans related to this feature. If one exists, present it and ask: continue from it, update it, or start fresh?
2. Check for past solutions — search docs/solutions/, docs/decisions/, or any project memory layer for previously solved similar problems.
3. Classify the request — feature, bug fix, refactor, or improvement?
4. Gauge risk — does this touch security, payments, auth, or external APIs? High-risk topics warrant external research in Phase 1.5.

If the request is vague, ask 1-2 refinement questions before launching research.

Phase 1: Parallel research

Launch these research tracks in parallel using the Agent tool — they are independent and should not run sequentially. Tailor each prompt to the specific task.

Track A: Codebase exploration

Spawn a sub-agent to map the current state:

• Files that will be affected by this change (with paths)
• Existing patterns for similar functionality (with examples)
• Related code, tests, types, and utilities
• Technical debt in the affected areas

Have the agent return file paths and code excerpts for every finding, so the plan can reference real locations rather than guesses.

Track B: Learnings research

Spawn a second sub-agent (or search directly) to look through docs/solutions/, docs/decisions/, and any documented best-practices for:

• Previously solved similar problems
• Past decisions that constrain or inform this work
• Patterns documented as project conventions
• Known gotchas in the affected areas

Track C: Dependency check (when relevant)

For tasks involving external libraries, APIs, or integrations:

• Check current versions in package.json (or the project's manifest)
• Look for existing usage patterns in the codebase
• Identify potential conflicts or breaking changes

Optional: offload exploration to a second CLI model. If you have a second coding CLI available (e.g. an OpenAI Codex CLI, a Gemini/Antigravity CLI, or any agent that can read the repo), you can delegate Track A or Track B to it to preserve the orchestrator's context window for synthesis. Pass it the task description plus the directories to explore, capture its findings to a temp file, then read and spot-check 2-3 cited paths (delegated models hallucinate paths) before folding the findings into the plan. This is a pure optimization — the core skill works entirely with the parallel sub-agents above.

Phase 1.5: External research decision (conditional)

After local research completes, decide if external research is warranted:

Phase 2: Ask clarifying questions

Before producing any plan, ask clarifying questions with AskUserQuestion. Good candidates:

• Scope — "Should this also handle [edge case]?"
• Priority — "What matters most: speed, robustness, or simplicity?"
• Constraints — "Any requirements I should know about that aren't in the codebase?"
• Approach — when multiple valid approaches exist, present them with tradeoffs

Only ask questions that would meaningfully change the plan. Skip if the task is already clear.

Phase 3: Choose detail level

Match plan depth to task complexity:

Minimal (quick tasks, 3-5 files): problem statement · steps with file paths · success criteria.

Standard (typical features, 5-15 files): context from research · problem statement · proposed approach with rationale · step-by-step plan · technical considerations · acceptance criteria · risks and mitigations.

Comprehensive (large features, architectural changes, 15+ files): executive summary · detailed problem analysis · solution design with phases · alternatives considered (and why rejected) · technical specs · schema/migration plan · API contract changes · risk mitigations · testing strategy · extensibility notes.

Phase 4: Write the plan

Create the plan at docs/plans/YYYY-MM-DD-<type>-<descriptive-name>-plan.md:

# [Plan Title]

**Type:** feat | fix | refactor | chore | docs
**Date:** YYYY-MM-DD
**Status:** draft | approved | in-progress | completed

## Context
What we learned from research (key findings only, not a data dump).
Reference specific files and patterns discovered.

## Problem Statement
What needs to change and why.

## Proposed Approach
The chosen strategy and rationale (1-3 sentences).

## Implementation Steps

### Step 1: [Description]
- **Files:** `path/to/file.ts`
- **Changes:** What specifically changes
- **Depends on:** (nothing | Step N)

### Step 2: [Description]
...

## Risks & Mitigations
| Risk | Impact | Mitigation |
|------|--------|------------|
| [Risk] | [Impact] | [How we handle it] |

## Success Criteria
- [ ] What "done" looks like
- [ ] How we verify it works

## Out of Scope
Things we're deliberately NOT doing (and why).

## Research Notes
Key findings from the research phase. Reference `docs/solutions/` entries if relevant.

Valid filename examples:

• 2026-02-15-feat-export-pipeline-plan.md
• 2026-02-15-fix-auth-redirect-plan.md
• 2026-02-15-refactor-data-layer-plan.md

Then create a TodoWrite task list from the implementation steps for real-time tracking.

Phase 5: Present and get approval

Present the plan summary, then offer next steps:

1. Approve and start working — hand off to implementation
2. Adjust the plan — modify scope, approach, or steps
3. Deepen research — investigate specific areas further before committing
4. Shelve for later — keep the plan in docs/plans/ for future reference

Do NOT start coding until the user approves the plan.

Plan quality checklist

Before presenting, verify:

• Every step references specific files/locations discovered during research
• The approach follows existing codebase patterns (don't invent new ones without reason)
• Dependencies between steps are clear (what must happen before what)
• Success criteria are testable, not vague
• Nothing is assumed — anything uncertain was asked in Phase 2
• Past solutions have been checked for relevant patterns
• The plan file exists in docs/plans/ with correct naming

Anti-patterns

• Planning without research. Don't produce a plan from assumptions. Always explore first.
• Over-planning. A plan for a 3-step task should be 3 steps, not 15. Match plan complexity to task complexity.
• Ignoring existing patterns. If the codebase already does something similar, follow that pattern.
• Asking obvious questions. Don't ask "Should I write tests?" if the codebase already tests similar features — just include them.
• Vague steps. "Implement the feature" is not a step. "Add generateExport to lib/export.ts following the pattern in lib/share.ts" is a step.
• Ignoring past solutions. Always check for prior art before planning. Someone may have already solved this.

Known gotchas

• Delegated exploration hallucinates paths. If you offload Track A/B to a second CLI model, always spot-check cited file paths against the real repo before trusting them.
• Plans go stale mid-implementation. Plans are living documents. If you discover something during implementation that invalidates the plan, stop, update the plan, and re-confirm with the user.
• Conflicting patterns in research. If research surfaces two competing patterns, present both with tradeoffs and let the user decide. Record the decision so the next plan doesn't relitigate it.

Integration with other skills

• After approval — hand off to your implementation flow, or proceed directly for simpler tasks.
• After completion — capture what went well or poorly into your project's memory/solutions layer, so the next plan benefits.
• Companion — pair with an evaluate-plan pass to catch requirements the first draft silently dropped.