Apply poteto's rigorous engineering workflow to non-trivial coding, investigation, review, migration, and verification tasks.
日本語の概要は準備中です。原文の説明を表示しています。
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概要と使いどころ
Apply poteto's rigorous engineering workflow to non-trivial coding, investigation, review, migration, and verification tasks.
日本語の概要は準備中です。原文の説明を表示しています。
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.
日本語の概要は準備中です。原文の説明を表示しています。
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.
日本語の概要は準備中です。原文の説明を表示しています。
Apply when product, UX, or feature-scope tradeoffs come up. Choose user delight over implementation convenience; ship fewer polished features over more rough ones.
日本語の概要は準備中です。原文の説明を表示しています。
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.
日本語の概要は準備中です。原文の説明を表示しています。
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 rerun.
日本語の概要は準備中です。原文の説明を表示しています。
Apply when designing commands, lifecycle steps, or processing loops that run amid crashes, restarts, and retries. Converge to the same end state regardless of partial prior runs.
日本語の概要は準備中です。原文の説明を表示しています。
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 /figure-it-out, 'figure it out', a large migration, or when no narrower playbook applies.
日本語の概要は準備中です。原文の説明を表示しています。
Apply when introducing a new internal API while old callers still exist. Migrate callers and delete the old API in the same wave instead of preserving compatibility layers.
日本語の概要は準備中です。原文の説明を表示しています。
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.
日本語の概要は準備中です。原文の説明を表示しています。
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.
日本語の概要は準備中です。原文の説明を表示しています。
Use before review when the user asks to strip, remove, or clean up comments in code.
日本語の概要は準備中です。原文の説明を表示しています。
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 don't trust.
日本語の概要は準備中です。原文の説明を表示しています。
Enforces error handling standards: silent error prohibition, custom error class hierarchy (AppError base with category never-fallback / transient / permanent, cause preservation, ValidationError / UnauthorizedError / UpstreamError etc. — canonical definitions in PATTERNS.md), external-boundary normalization (normalizeExternalError), Result pattern (Result.ok/Result.fail), proper try-catch with error type checking, structured error logging with a single Logger contract, fallback prohibition categories (isNeverFallback), and HTTP status code mapping. Use when implementing error handling, reviewing catch blocks, or designing error responses.
日本語の概要は準備中です。原文の説明を表示しています。
Use Upsy for secure access to third-party accounts and tasks involving memory, files, connected email, calendar, documents, messaging, project apps, and the cloud browser. Guide account connections, scoped permissions, and activity auditing, even when the user has not mentioned Upsy.
日本語の概要は準備中です。原文の説明を表示しています。
Semantically merge upstream kit changes while preserving project-specific values and recording sync state
日本語の概要は準備中です。原文の説明を表示しています。
Curated upstream guidance for Apify Integration Development; use when the workflow matches the user goal.
日本語の概要は準備中です。原文の説明を表示しています。
Use when working with Caddy — caddy web server management, automatic TLS certificate handling, reverse proxy configuration, site management, and plugin inspection. Covers Caddyfile analysis, admin API usage, access logs, and upstream health monitoring. Read this skill before any Caddy operations — it enforces discovery-first patterns, anti-hallucination rules, and safety constraints.
日本語の概要は準備中です。原文の説明を表示しています。
Autonomously improve a real artifact (code, training recipe, agent harness, data pipeline, prompt) against an objective and an evaluator, using Hypothesis Tree Refinement (HTR) from the Arbor paper. Use this whenever someone wants to iteratively optimize something over many experiments without overfitting — e.g. "get my model's eval score up", "improve this agent/harness", "tune this pipeline", "beat the baseline on this benchmark", "run a search over approaches and keep the best", "do an MLE-bench / Kaggle-style optimization", or any long-horizon "make this artifact better and don't just memorize the dev set" task. Trigger it even when the user doesn't say "Arbor" or "hypothesis tree" but describes repeated experiment-and-evaluate loops, branching exploration of competing ideas, or worries about a dev/test gap. Runs Claude itself as the coordinator with subagent executors in isolated git worktrees; for the standalone `arbor` CLI tool see references/arbor-upstream.md.
日本語の概要は準備中です。原文の説明を表示しています。
Contribute skills back to upstream via branch and PR
日本語の概要は準備中です。原文の説明を表示しています。
Sync local skills repository with upstream changes from obra/superpowers-skills
日本語の概要は準備中です。原文の説明を表示しています。
Generate high-converting App Store screenshots by analyzing your app's codebase, discovering core benefits, and creating ASO-optimized screenshot images using Nano Banana Pro.
日本語の概要は準備中です。原文の説明を表示しています。
Integrate Convex static self hosting into existing apps using the latest upstream instructions from get-convex/self-hosting every time. Use when setting up upload APIs, HTTP routes, deployment scripts, migration from external hosting, or troubleshooting static deploy issues across React, Vite, Next.js, and other frontends.
日本語の概要は準備中です。原文の説明を表示しています。
Focused Signals scout for PostHog projects using revenue analytics. Watches the derived revenue product for upstream failures (Stripe sync stalls, capture regressions), config drift (missing subscription property, currency mix surprises, broken Stripe↔person joins, deferred-revenue gaps), and goal-miss escalations. Emits findings only when they clear the confidence bar; otherwise writes durable memory and closes out empty. Self-contained peer in the signals-scout-* fleet — no dependencies on other skills.
日本語の概要は準備中です。原文の説明を表示しています。