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mola-plan

Used for all planning operations.

Skill by 418-teapot

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Works with Claude Code, Claude apps, Codex, Cursor, Gemini CLI, GitHub Copilot, VS Code, OpenCode, Goose, Windsurf. Read the repository before you give any tool access to your data.

npx agentmarket install skill/418-teapot-mola-plan

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About

Used for all planning operations. Automatically adjusts interview depth based on task clarity — clear tasks get fast-track decomposition, fuzzy requirements trigger research-and-adopt defaults, and architecture-class tasks get deep decision-tree grilling with scenario stress testing. Produces structured plan files (and design specs for architecture tasks). Load this skill whenever the request involves requirement clarification, task decomposition, design decisions, or implementation planning.

Use cases: design, testing, research, productivity

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Permissions

What this skill can do and what it asks for, from its SKILL.md. Checked Oct 25, 2026.

Tools
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Install scripts
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Network hosts it talks to 1

  • codeload.github.com · found in install command

Files it touches

  • ~/.claude/skills/mola-plan

What's inside

Skill name
mola-plan
Description
Used for all planning operations. Automatically adjusts interview depth based on task clarity — clear tasks get fast-track decomposition, fuzzy requirements trigger research-and-adopt defaults, and architecture-class tasks get deep decision-tree grilling with scenario stress testing. Produces structured plan files (and design specs for architecture tasks). Load this skill whenever the request involves requirement clarification, task decomposition, design decisions, or implementation planning.
License
MIT
Instructions
196 lines in SKILL.md · view on GitHub

Files (5)

  • SKILL.md
  • intent-clear.md · references/
  • intent-unclear.md · references/
  • plan-template.md · templates/
  • spec-template.md · templates/

SKILL.md (first lines)

# Planning — from ground-check to approved plan

Produces a structured plan file decomposing work into sequenced, verifiable tasks.
For Architecture-class tasks, also produces a design spec before the plan.

## Anti-Patterns

- **"This Is Too Simple To Need A Spec"** — The most expensive mistakes come from unexamined assumptions on "simple" changes. A spec is 1-2 pages, not 50. Spec the simple things; save the expensive surprises for later.
- **Skipping ground before classify** — Ground reveals what is actually involved. Classify without ground is guessing. Always explore first.
- **Beginning implementation** — NEVER begin implementation (even "quick scaffolding" or "just a skeleton"). Outputs are plan files (+ optional spec for Architecture).
- **Skipping approval gates** — Present brief → wait for OK → write. Every section, every artifact.
- **Asking what the codebase can answer** — Explore first. User time is more expensive than search time.

## Workflow

Complete all 6 phases in order.

### Phase 1 - Ground Check

Explore the codebase to validate the problem exists and understand what is involved.
Run these in parallel when independent.

1. **Search** — affected files, entry points, call sites, dependency graph
2. **Pattern discovery** — existing implementations to reference, established conventions
3. **Context gathering** — codebase docs (`AGENTS.md`, README), external documentation, prior plans in `.zoo/plans/`

**Scope assessment:** If the work spans 2+ independent subsystems, stop and request decomposition: "Request decomposition needed: this spans [subsystems] which should be planned independently." Otherwise confirm scope coherent and proceed.

**Output of Ground:** A mental model answering four questions:
- Where do changes go? (files, modules, entry points)
- What exists already? (patterns to follow, tests to update)
- What is the scope? (how many files, how many modules, cross-boundary?)
- What is unknown? (gaps that need classification and user questions)

Do NOT interview the user during Ground. Note questions for Phase 3.

### Phase 2 - Classify

Based on Ground findings, determine the reference strategy:

| Ground signals | References to load |
|---|---|
| Files + approach + boundaries all clear, simple | `references/intent-clear.md` |
| Standard task, intent fuzzy, defaults needed | `references/intent-unclear.md` |
| Architecture-class, real tradeoffs, scope ambiguity | `grill` skill |
| ON THE FENCE | default to `grill` skill |

State the classification once: "Classification: [Clear|Unclear|Architecture]. Loading references: [...]."

**Graceful upgrade:** If mid-flow you realize the task is heavier than classified, load the `grill` skill. No need to restart or re-enter the Workflow. You can load the skill mid-interview and continue.

### Phase 3 - Interview

Load the classified reference(s) and execute their protocol. All three references share:

- **Two Filter discipline** for every question candidate:

  Filter 1: Can the codebase/docs answer this? → research it, don't ask. | Filter 2: Do best-practice defaults answer this? → adopt and inform, don't ask. | Genuine owner-decision → ask (≤2 per turn, recommended answer first).

- ≤2 questions per turn, multi-select when possible, recommended answer first (C3)
- Adopt defaults, inform user — do not interrogate (C4)

**intent-clear.md:** Topology lock → decision-fork questions only → clearance check.
**intent-unclear.md:** Research defaults → adopt → present assumptions ledger → minimal questions (0-2).
**grill skill:** Decision-tree traversal → depth-first branch resolution →
scenario stress testing → domain vocabulary refinement. The `grill` skill
is the single source of truth for Architecture-class interview — do not duplicate its protocol here. Load it via the skill tool.

Do NOT duplicate reference content in this SKILL. Each reference owns its protocol.

### Phase 4 - Present Design (Incremental)

After the interview resolves, present the design one section at a time. Scale each section to its complexity:

1. **Context** — what triggered this, code involved, user need
2. **Goals** — specific, measurable design objectives
3. **Key Decisions** — chosen approach with rationale
4. **Scope** — Must have + Must NOT have (explicit guardrails)
5. **Risks** — known risks and mitigations
6. **Success Criteria** — how we will know the design achieves its goals

2-3 sentences if straightforward, up to 200-300 words if nuanced. After EACH section, ask for user approval. If the user requests revision, revise that section and continue.

**Scale by classification:** Clear/Unclear → lightweight brief (Context/Approach/Scope/Risks in one pass). Architecture → section-by-section with full depth.

**Anti-patterns:**
- Dumping the whole design at once → user cannot give focused feedback
- Skipping pauses for approval → user surprise on final write
- Continuing past clear objections without resolving

### Phase 5 - Produce

#### If spec path (Architecture classification):

**Step 5a: Scaffold spec file**

Read `templates/spec-template.md` and adapt it into a spec file:

1. Derive the title from the slug (kebab-case → title case).
2. Compute today's date as `YYYYMMDD`.
3. Write the spec via the `write` tool to `.zoo/plans/<slug>-spec-<YYYYMMDD>.md`
   with this frontmatter:

   ```yaml
   ---
   title: "<Title>"
   slug: "<slug>-spec-<YYYYMMDD>"
   created: "<ISO timestamp>"
   updated: "<ISO timestamp>"
   status: awaiting-approval
   ---
   ```

   Then write the template body, replacing `{{TITLE}}` with the title and filling placeholder sections from the design interview.

**Step 5b: Fill sections** — via edit tool, fill each section per the inline placeholder guidance. Each decision entry includes: Chosen option, Alternatives considered, Scenarios tested.

**Step 5c: Self-review** — run 4 checks, fix findings inline:

From 418-teapot/ZooKeeper, MIT.

More from 418-teapot/ZooKeeper

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Last commit (this folder)
Oct 6, 2026 (22 days ago)

From GitHub (fetched Oct 24, 2026).

Details

License
MIT
First seen
Oct 24, 2026
Last checked
Oct 24, 2026

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Cite this page

mola-plan skill. Agent Mart. https://agentmart.dev/skills/418-teapot-mola-plan (last updated 2026-10-24)