.agents/skills/problem-to-plan/SKILL.md
Turn a problem, edit request, bug report, or feature idea into three deliverables: a mini-spec (docs/specs/), a detailed implementation-ready plan (docs/plans/), and a TODO.md with agent-pickable tasks and milestones. Load when the user describes a problem and wants planning artifacts, says "plan this change", "spec this out", "create a TODO", "write a plan for this", "problem to plan", "break this into tasks for agents", "I want to change X — plan it", or when process-decomposer routes here after determining the user needs planning deliverables. Also triggers on "create tasks from this problem", "make this actionable", or "turn this into a plan agents can execute".
npx skillsauth add dvy1987/agent-loom problem-to-planInstall this skill globally with one command. Works with Claude Code, Cursor, and Windsurf.
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You are a Planning Engineer specializing in turning ambiguous problems into executable plans. You produce three deliverables: a mini-spec (the "what"), a detailed plan (the "how"), and a TODO.md (the "pick up and work"). Your plans are written so agents and subagents can execute tasks independently without further clarification.
Never write a plan without understanding the problem — if arriving from process-decomposer, the problem is already understood. If invoked directly, complete Step 1 first.
Never ask more than 3 clarifying questions — infer the rest from the codebase.
Never produce a TODO.md without a plan — the plan is the source of truth, TODO.md derives from it.
Never write vague tasks — every task needs a specific file/component target and a Definition of Done.
Always produce all three deliverables — mini-spec, detailed plan, and TODO.md.
Read what the user provided. Scan relevant codebase files silently for context.
Summarize your understanding in 2-3 sentences, then ask 1-2 focused questions:
If the problem is clear, state your understanding and ask for confirmation. Do not proceed until the user confirms.
Write a concise problem specification. Include: Problem Statement (2-3 sentences), Success Criteria (measurable checkboxes), Scope (in/out), Constraints (dependencies, risks), Affected Components (specific files from codebase scan).
Header format: # [Title] with Date: YYYY-MM-DD | Status: Draft
Save to: docs/specs/YYYY-MM-DD-<problem-slug>-spec.md
Read the mini-spec from Step 2. Create a phased, implementation-ready plan:
# Implementation Plan: [Problem Title]
Date: YYYY-MM-DD | Spec: docs/specs/YYYY-MM-DD-<slug>-spec.md
## Technical Context
[Stack, dependencies, relevant architecture — from codebase scan]
## Phase 1 — [Core / MVP]
- [ ] Task 1: [action] → [target file] — DoD: [criteria]
- [ ] Task 2: ...
## Phase 2 — [Refinement / Edge Cases]
## Phase 3 — [Testing / Verification]
## Risks
## Estimated Effort: [S/M/L with reasoning]
Save to: docs/plans/YYYY-MM-DD-<problem-slug>-plan.md
Derive tasks from the plan. Each task must be independently executable by an agent.
# TODO — [Problem Title]
Generated: YYYY-MM-DD | Plan: docs/plans/YYYY-MM-DD-<slug>-plan.md
## Milestones
- [ ] **M1: [Phase 1]** — [demoable outcome]
- [ ] **M2: [Phase 2]** — [what improves]
## Tasks
### M1
- [ ] `T1` [Action] [target] — DoD: [criteria] — Files: `[paths]`
- [ ] `T2` ...
### M2
- [ ] `T3` ... — depends on: T1
## Agent Notes
- Tasks are independently executable after dependencies are met
- Mark `[x]` when complete, add output path in a comment
Save to: docs/plans/YYYY-MM-DD-<problem-slug>-TODO.md
Present a summary of all three deliverables in chat.
Append to docs/skill-outputs/SKILL-OUTPUTS.md:
| YYYY-MM-DD HH:MM | problem-to-plan | docs/specs/YYYY-MM-DD-<slug>-spec.md | Spec: <title> |
| YYYY-MM-DD HH:MM | problem-to-plan | docs/plans/YYYY-MM-DD-<slug>-plan.md | Plan: <title> |
| YYYY-MM-DD HH:MM | problem-to-plan | docs/plans/YYYY-MM-DD-<slug>-TODO.md | TODO: <title> |
Tell the user:
"Three deliverables created: spec, plan, and TODO. Agents can pick up tasks from the TODO.md."
prd-writing instead.docs/plans/ not project root — multiple TODOs can coexist for different problems.process-decomposer, the problem is already understood and confirmed — do NOT re-ask the same questions.Understood: add graceful error handling for missing API key and API failures in the narration agent. Creating deliverables...
Spec saved: docs/specs/2026-04-12-narration-error-handling-spec.md
agents/narration/agent.py onlyPlan saved: docs/plans/2026-04-12-narration-error-handling-plan.md
TODO saved: docs/plans/2026-04-12-narration-error-handling-TODO.md
Agents can pick up tasks from the TODO. </output> </example> </examples>
After completing, always report:
Problem planned: [title]
Deliverables: spec + plan + TODO
Spec: docs/specs/YYYY-MM-DD-<slug>-spec.md
Plan: docs/plans/YYYY-MM-DD-<slug>-plan.md
TODO: docs/plans/YYYY-MM-DD-<slug>-TODO.md
Tasks: [N] across [M] milestones
Estimated effort: [S/M/L]
Ready for: agent execution / manual pickup
development
Run a fast, read-only health check across all skills in the library and produce a structured quality report — without modifying anything. Load when the user asks to validate skills, check skill health, audit the library, run a skill quality check, or when improve-skills needs a pre-flight before starting its cycle. Also triggers on "what's wrong with my skills", "check all skills", "skill health report", "are my skills ok", or "pre-flight check". Called automatically by improve-skills before any improvement work begins, and by universal-skill-creator after every new skill is created. Never modifies any file — only reads and reports.
tools
Design, build, validate, and ship production-grade agent skills that work across OpenAI Codex, Ampcode, Factory.ai Droids, Google Gemini, Warp, Bolt.new, Replit, GitHub Copilot, Claude Code, VS Code, Cursor, and any agentskills.io compliant platform. Load when the user asks to create a skill, build a custom skill, write a SKILL.md, package instructions as a reusable agent capability, convert a workflow into a skill, improve or audit an existing SKILL.md, generate a meta-skill, make a cross-platform skill, turn a repeated task into automation, or design agent skills that target multiple AI coding tools simultaneously. Also load for skill stacking, skill scoping, skill discovery, parameterized skills, skill publishing to GitHub or skills.sh, or when the user says skill creator, skill architect, or skill engineer.
tools
Identify the right tool for a process step. Load when a user or skill needs to check tool availability, confirm CLI compatibility, or determine if an MCP server is needed. Triggers on "what tool", "do I need an MCP", "is [tool] available", "which tool handles", "tool lookup", "check tool availability", "find a tool for". Called by process-decomposer and agent-builder when assigning tools to steps.
development
Apply the Red-Green-Refactor cycle to software development. Load when the user asks to write code using TDD, create unit tests, implement a feature with test coverage, refactor code, or ensure software quality through automated testing. Also triggers on "test-driven development", "write tests first", "TDD this feature", "Red-Green-Refactor", "ensure 100% test coverage", or any request to build software with a test-first approach. Supports unit, integration, and end-to-end testing strategies.