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Follow https://skillsmp.com/skill-install/prompt.md to install Agent Skills from https://github.com/Aqua-123/pstack-for-codex.Loading the repository README…
Showing 40 of 58 collected skills.
Sketch types, signatures, and module structure before code, then stay in the loop while implementation fills in. Use for $architect, 'architect this', 'design this', or non-trivial work where jumping to code would lock in the wrong shape.
Spawn N parallel candidates at the same task, pick a base, graft the strongest parts of the losers into it. Use for $arena, 'arena this', 'throw it in the arena', or when one attempt at a non-trivial artifact would lock in the wrong shape.
Use for "automate me", "create/update/refresh my -mode skill", "turn/capture my preferences or working style into a skill", or wanting agents to follow how the user works. Drafts or revises a personal -mode skill through skill-creator and unslop, optionally…
Vet a perf measurement (limiter, tuning, limits, errors, repeatability, relevance, and whether the work happened) before you report or act on it. Use when you run a benchmark or report a speedup or regression you measured.
Generate a project-local verification skill that drives your app the way a user does — any language, framework, or platform. Use for $create-verification-skill, "make a control skill for this repo", or when a project has no scripted way to prove…
Design an auditable playbook when no narrower one fits: a large migration, an ambitious multi-part change, or work a human reviews after stepping away. Scales rigor to the task, runs a hypothesis loop, and logs decisions via show-me-your-work. Use for…
Use for "how does X work", code walkthroughs before changing something, and placement / ownership / layering questions ("where should this live", "which package owns this", "is this the right layer"). Explains subsystem architecture, runtime flow, onboarding…
Restate in your own words what you think the user's goals are and what problem they're trying to solve. Use for $in-your-own-words.
Use for "interrogate", "adversarial review", "multi-model review", "challenge this", "stress test this code", "find blind spots", or "tear this apart". Multiple LLM reviewers challenge changes from independent angles.
Catch the user up on what changed in this chat since their last message, in a few plain sentences and small visuals. Give each action item just enough context to make the call. Use for $ketchup.
Spawn Comment Sicko, fix accepted findings, and offer encodings for claimed constraints.
Guides users through pstack setup, prompting, $poteto-mode, and selection of a skill, playbook, or principle. Use only when the user explicitly invokes $poteto-help. Not for requests to do work, even ones that name pstack.
poteto's agent style for concise, detailed responses, deliberate subagents, unslopped prose, simple code, and verified work. Invoke explicitly with $poteto-mode.
Apply to any non-trivial work, not just bulk work: edits, migrations, analyses, checks. Build the tool that does it or proves it (codemod, script, generator, or a skill your subagents follow) instead of working by hand. The tool is the artifact a reviewer can…
Apply when facing a novel UI interaction or architectural decision with no precedent in the codebase. Build 2-3 competing prototypes and compare side by side before committing.
Apply before you trust, report, or act on a number you measured: a speedup, a regression, a throughput, a latency, or an eval result. Find what limits it, and rule out that it measured something other than the work you think.
Apply when debugging. Trace each symptom to its root cause and fix it there; reproduce first, ask why until you reach it, resist nil-check guards that silence crashes.
Apply when context is filling up: large outputs, long files, repeated reads, fan-out planning. Route bulk to subagents; keep summaries in the main thread, not raw payloads.
Apply when refactoring, evaluating diff size, or tempted to add abstractions, layers, or signal threading. Bias toward deletion and the smallest change that solves the problem.
Apply when reviewing or shaping code that's hard to trace. Count layers between question and answer, and hidden state in the reader's head; collapse one-caller wrappers and shrink mutable scope.
Apply when writing stateful logic, or when code branches a lot or repeats a shape assumption across files. Encode the domain in a structure instead of scattered conditionals.
Apply when tempted to ask 'should I do X?' on reversible work. Proceed, present the result, let the human course-correct after the fact; reserve confirmation for irreversible actions.
Apply when integrating a new requirement into an existing design. Redesign as if the requirement had been a foundational assumption from day one, instead of bolting it on.
Apply when sequencing an addition, refactor, or rewrite. Remove dead weight, redundant validators, and stub references first, then build on the simpler base.
Spawn three parallel review subagents over supported active-task history or a digest, surface learnings, and route each to a concrete edit on an existing skill. Use when the user says reflect.
Sharpen a task before starting: the expert approach, what the user is really after, and the right level of specification. Use for $sharpen.
Layered technical-writing standard: Diátaxis structure, Google developer style sentences, STE instruction rules, Global English syntax. Use for $technical-writing or when writing or reviewing docs, RFCs, readmes, PR descriptions, or commit messages.
Cut AI tells from any writing. Must always apply.
Use for 'why does X work this way', 'why we picked Y', design rationale, regressions, postmortems, or data-backed thresholds. Discovers available MCPs and queries each evidence category (source control, issue tracker, long-form docs, real-time chat,…
Find what a change could break somewhere else before it ships, beyond the diff, and prove the one fact it's safe because of by running real code instead of writing it up. Use for 'blast radius of X', 'what could this break', or reviewing a small diff you…
Find the mistakes agents keep repeating in this repo and make each one impossible. Try architecture first, then types, then a lint whose error names the fix, then a test, and write docs last. Prove each check fails on a real past mistake. Repeat this each…
Apply during planned rewrites and migrations with explicit phase boundaries. Converge on the target architecture; don't preserve smooth intermediate states with throwaway compatibility code.
Apply after completing a task, before declaring done. Verify against the real artifact (run the feature, read the actual value, inspect the diff), not a proxy, self-report, or 'it compiles.'
Apply to multi-step work (sweeps, migrations, runs of similar edits) and to how you stack commits and PRs. Break work into small units that each end in a verifiable state, check each before the next, and order delivery so the sequence proves itself to a…
Install, update, remove, or inspect optional Codex agent profiles for pstack, including explicit model-role configuration. Use for setup-pstack or requests to configure pstack agents and models.
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 $show-me-your-work, autonomous or…
Fan out N parallel workers, drain them, and return one report. Use for $swarm, 'swarm this', or parallel coverage, races, gauntlets, and exploration.
Use only when the user explicitly asks for TDD, a failing test, or a regression test, OR when the bug has an obvious cheap local test target. Skip when the test path is unclear, expensive, integration-heavy, or not requested.
TypeScript best practices. Use when reading or editing any .ts or .tsx file.
Use when building a local page or dashboard whose buttons send authenticated JSON to a user-owned webhook service. Do not use for unapproved public hosting, credential handling, or external automation setup.
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