plan-loop
Use when the user has a coding or engineering prompt and wants it refined into a detailed, executable plan before any code is written — the planning stage of a prompt → plan → execute → debug pipeline. It decomposes the prompt from first principles (objective, end state, environment, building blocks, tools, packages), breaks the work into PR-sized tasks each tied to a component with its files, tests, and dependencies, orders them topologically, splits each into atomic subtasks, then a separate principal-engineer agent critiques the plan for alignment, coverage, sizing, and executability; it re
npx skills add gaasher/Agent-Loop-Skills --skill plan-loop --agent claude-code
Same command for any agent — swap --agent for codex, cursor, copilot.
Weekly change comes from our own snapshots, not the repository page — it measures attention, not adoption.
# Plan Loop A **planning** loop: it turns a prompt into a plan detailed and correct enough to hand to a lower-tier model. The artifact is the plan — `plan.md` (the layout) + `tasks.json` (PR-sized tasks, each with files, tests, dependencies, and atomic subtasks). The feedback signal is two-part, like the repo's other evaluator loops: an **objective gate** (`tools/validate_plan.py` — schema shape, an acyclic dependency graph, a valid topological order, full component coverage) and a **qualitative gate** (a separate **principal engineer** agent that critiques alignment, decomposition, testability, and whether a junior could execute each task without guessing). You build the plan from first principles, validate it, critique it, and revise until the critique passes. This is the *plan* stage of a larger prompt → plan → execute → debug pipeline; it stops once the plan is ready to delegate. ## When to use Use to convert a feature/bug/refactor prompt into an executable plan grounded in a real repository — when the goal is a hand-off artifact a downstream executor (or a smaller model) can implement task-by-task. The plan is only as good as its weakest task for a literal-minded implementer,
- When to use
- Setup
- The loop
- Plan artifacts
- Ledger
- Constraints
- Roles
What does the plan-loop skill do?
Use when the user has a coding or engineering prompt and wants it refined into a detailed, executable plan before any code is written — the planning stage of a prompt → plan → execute → debug pipeline. It decomposes the prompt from first principles (objective, end state, environment, building blocks, tools, packages), breaks the work into PR-sized tasks each tied to a component with its files, tests, and dependencies, orders them topologically, splits each into atomic subtasks, then a separate principal-engineer agent critiques the plan for alignment, coverage, sizing, and executability; it re
How do I install it?
Run `npx skills add gaasher/Agent-Loop-Skills --skill plan-loop --agent claude-code` — it drops the skill into your project so the agent can pick it up. Swap the --agent value for codex, cursor or copilot if you use one of those.
Where does this skill come from?
From gaasher/Agent-Loop-Skills, a repository with 146 stars. We read it straight from the repository tree rather than a submitted listing, so what you see here is what is actually published.
Is a popular skill a good skill?
Not necessarily. Stars measure attention, not adoption — a repository can trend for a week and be abandoned. That is why we show the weekly change from our own snapshots next to the total, instead of a single flattering number.