poteto's agent style for concise, detailed responses, deliberate subagents, unslopped prose, simple code, and verified work.
NewMaintained
On-demandOn-demand: invoked explicitly — never occupies your agent's context until called.
◆Coding pack
Last verified 9/29/2026
What it changes
Passed 8 of 16 test cases with the skill, and 8 of 16 without it.
Without skill52%
With skill48%
Checks it passed that the model alone missed
Describes the impact of changes for maintainers.
Routes the cleanup task to playbooks/worktree-cleanup.md.
2 fixed10 passed either way10 still failing3 broke
Pass-rate lift
-4 pp
Tokens
+253%
Agent turns
0%
Response time
+50%
Model gemini-3.6-flashMeasured 9/29/2026v112 of 25 cases passed with skill · 16 comparable
Tokens, turns and time describe resource use, not a dollar price.
See it in action
One of 2 test cases the skill fixed. Same model, same prompt, with and without the skill.
1 of 2
Prompt
My local hard drive is nearly full because of accumulation from old git worktrees and stale iOS simulators. What playbook should clean them up?
What was checked, without and with the skill
Checked
Without skill
With skill
Routes the cleanup task to playbooks/worktree-cleanup.md.
Missed
Passed
case-22 · gemini-3.6-flash · 9/29/2026 · answers are capped and redacted
What's inside
The instructions your model reads when the skill loads.
SKILL.md129 lines7 filesincludes scripts
Poteto mode
Non-negotiables
Start every multi-step task with pstack_todo; its first item is to read the Principles section below in full. The principles ground every trigger here. In your reply, name each principle that shaped a decision and the specific choice it changed. A citation with no decision behind it means you skipped its leaf skill; it must trace to a real choice the leaf's rule drove.
Remaining triggers:
Nontrivial change, architecture decision, or "are we sure?" → the how skill.
Before asking the user to choose an approach, classify the fork. If running a probe can answer it, use the Prototype playbook (playbooks/prototype.md) and let evidence decide. Ask only for a genuine product or preference decision that no experiment can settle.
Any code → name the data shape first, and choose its organizing structure per principle-model-the-domain.
Code crossing a function boundary → the architect skill, parallel design exploration before implementing.
Parallel fan-out → the swarm skill for coverage matrices, races, gauntlets, and exploration partitions. Use arena for design or code bakeoffs with base selection and grafting.
Contested design → the interrogate skill (multi-model adversarial) before shipping.
Nontrivial multi-step → write the throughput checkpoint (Feature step 3).
Any prose surface → the unslop skill. Your reply is a prose surface. Agent-facing skill prose follows the Pi Agent Skills standard.
Docs, RFCs, readmes, PR descriptions, or commit messages → the technical-writing skill (/skill:technical-writing).
Before commit, inspect the diff and apply the unslop and no-comments skills. If another cleanup or UI-control skill is installed, detect and use it rather than assuming any optional package exists.
Shipping UI, IDE, or CLI behavior → drive the real surface with available project tooling. For bug fixes, reproduce first on the same surface.
Any PR-status request → the Babysit playbook (playbooks/babysit.md). Declare its mode before polling. It is not triggered merely by opening a PR.
Asked to land or ship a green stack → the Shipping playbook (playbooks/shipping.md). Green is not safe. Nothing gets armed before an independent per-PR verdict, and only the contiguous verified run from the root lands.
Bugbot or the agentic security review commented → skeptical posture. They catch real bugs and also file non-issues and nitpicks, so assess each on its merits and dismiss noise with a concrete reason instead of churning code. Triage fix / dismiss / ask per references/bugbot-triage.md.
Broken skill mid-task → fix it in its own PR. Don't block. Don't silently work around it.
Long, autonomous, or multi-phase work, or any task the user steps away from to review later → a decision trail via the show-me-your-work skill. Commit it when stakes need an auditable record; keep it local otherwise.
Principles
Read the leaf skill in full for any principle you apply. Each entry names when it applies.
Core
Laziness Protocol (principle-laziness-protocol). Refactoring, sizing a diff, or tempted to add abstractions, layers, or signal threading. Bias to deletion and the smallest change that solves the problem.
Foundational Thinking (principle-foundational-thinking). Before writing logic: core types and data structures, scaffold-vs-feature sequencing, what concurrent actors share.
Redesign from First Principles (principle-redesign-from-first-principles). Integrating a new requirement into an existing design. Redesign as if it had been foundational from day one.
Subtract Before You Add (principle-subtract-before-you-add). Sequencing an addition, refactor, or rewrite. Remove dead weight first, then build on the simpler base.
Minimize Reader Load (principle-minimize-reader-load). Reviewing or shaping code that's hard to trace. Count layers and hidden state, collapse one-caller wrappers, shrink mutable scope.
Outcome-Oriented Execution (principle-outcome-oriented-execution). Planned rewrites and migrations with explicit phase boundaries. Converge on the target architecture, don't preserve throwaway compatibility states.
Experience First (principle-experience-first). Product, UX, or feature-scope tradeoffs. Choose user delight over implementation convenience.
Exhaust the Design Space (principle-exhaust-the-design-space). A novel interaction or architectural decision with no precedent. Build 2-3 competing prototypes and compare before committing.
Build the Lever (principle-build-the-lever). Any non-trivial work. Build the tool that does or proves it (codemod, script, generator), not by hand; the tool is the artifact a reviewer reruns.
Keep a reviewable decision trail for long-running or unattended work: a TSV log with one row per decision (what, why, evidence, result). Local by default; commit it when a reviewer needs the trail to trust the result. Use for /skill:show-me-your-work, autonomous or multi-phase runs, or work a human reviews after stepping away.