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概要と使いどころ
Map test coverage to GDD critical paths, identify fixed bugs without regression tests, flag coverage drift from new features, and maintain tests/regression-suite.md. Run after implementing a bug fix or before a release gate.
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。
Investigating bugs via root cause analysis, reproduction steps, and impact assessment. Investigation-only — finds why bugs occur and where to fix them, no code. Use when a bug needs RCA before a fix.
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。
[BETA] Hands-off end-to-end branch dogfood pass with browser testing, auto-fixes, regression tests, and fix commits.
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。
Diagnosis loop for bugs and failing behavior. Use for errors, stack traces, regressions, failed tests, issue-tracker bugs, stuck investigations after failed fixes, or asks to debug/fix a bug.
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。
Implement bounded features and fixes in existing or new mini-program codebases while preserving repository rules, user-owned changes, approved behavior, assets, framework conventions, and evidence boundaries. Use when users ask to write or modify mini-program code, implement a confirmed specification or architecture, add a scoped feature, remove behavior semantically, update internal documentation required by a change, or carry out a well-defined small fix that does not require root-cause investigation. Establishes a baseline and change boundary, applies test-driven small steps, distinguishes source from generators and build artifacts, verifies the affected contract, and never reports source completion as device validation, formal acceptance, upload, or release.
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。
Implements any user intent, requirement, story, bug fix or change request by producing clean working code artifacts that follow the project's existing architecture, patterns and conventions. Use when the user wants to build, fix, tweak, refactor, add or modify any code, component or feature.
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。
Root cause analysis for bugs and unexpected behavior. Traces errors through code, uses structured reasoning, and hands off to fix when cause is found. Core of the debug↔fix mesh. When the diagnosed cause is a memory leak in a long-running process, escalates to perf for cost-impact framing (leaks drive OOM-restart → cold-start → autoscaler spend, often 20-40% bill inflation).
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。
Builds a talk as a beatdeck - a fixed 1920x1080 React stage where one click is one beat, with authored motion, presenter view, overview, and an offline self-contained build. Covers turning source material (PPTX, Keynote/PDF export, Markdown, notes) into a content audit and a scene/beat map, choosing or applying a theme, writing scene layers, automatic beats, and verifying every beat with npm run verify. Use whenever the task is creating, porting, restyling, rehearsing or fixing a presentation, talk, keynote, slide deck or conference session that should feel like a live system rather than slides, or whenever the repo contains src/beatdeck/.
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。
Your team has high autonomy — and standups are vague, weekly meetings drift into status reports, and 1:1s produce nothing but "I'm fine." This playbook fixes all three layers at once. What's inside: • Daily Standup system — 3-field format, good sample, 4 COO principles to keep it honest • Weekly Meeting — strict 25-min agenda, Scrum Master rotation, 0–10 pulse check • 1:1 Framework — 9-dimension quantified pulse, 5-group deep question bank, bilateral feedback structure • Diagnostic layer — "stuck-at" detection: info / authority / collaboration / capability / direction • FAQ for 4 common failure modes (dead standups, status-report meetings, "I'm fine" 1:1s, scaling beyond 10 people) 🇨🇳 你的团队自由度很高——但 standup 越来越糊，例会变成汇报，1:1 问不出真话。这套三层 Motivation 操作手册解决的正是这件事：standup 是信息层，例会是对齐层，1:1 是个人层。三件事做好了，motivation 不是管出来的，是长出来的。 🇯🇵 チームの自律性は高いのに、スタンドアップは曖昧で、週次ミーティングは進捗報告になり、1on1では「大丈夫です」しか返ってこない——このプレイブックは、その3層すべてを同時に解決します。 🇰🇷 팀의 자율성은 높은데 스탠드업은 두루뭉술하고, 주간 회의는 진척 보고가 되어버리고, 1:1에서는 진심을 들을 수 없다면 — 이 플레이북이 세 레이어 모두를 동시에 해결합니다. Triggers: "团队 motivation" | "standup 没人写" | "例会变成汇报" | "1:1 问不出真话" | "高自由度团队管理" | "COO 如何管人" | "team motivation" | "standup best practices" | "1on1 framework" | "weekly meeting template" | "チームモチベーション" | "팀 동기부여" | "AI startup team ops" | "remote team alignment" | "engagement下降"
🇺🇸 GitHub README Writing System — Craft a README that converts visitors to stars in <3 seconds. Proven structure from AFFiNE's 0→60K star journey: tagline engineering, first-screen law, section-by-section copywriting guide, Claude Code integration section, anti-patterns, and a pre-publish checklist. Use when you need to write or rewrite a specific README file. 🇨🇳 GitHub README 写作系统 — 打造 3 秒内把访客转化为 star 的 README。来自 AFFiNE 0→60K star 实战：tagline 工程、首屏法则、逐节文案指南、Claude Code 集成板块、反模式、发布前自检清单。需要写或改一个具体 README 文件时使用。 🇯🇵 GitHub README 作成システム — 3秒以内にビジターをスターに変えるREADMEを作る。AFFiNE 0→60Kスター実績から: タグライン設計、ファーストスクリーン法則、セクション別ライティングガイド、Claude Codeインテグレーション、アンチパターン、公開前チェックリスト。 🇰🇷 GitHub README 작성 시스템 — 3초 안에 방문자를 스타로 전환하는 README 작성법. AFFiNE 0→60K 스타 실전: 태그라인 설계, 첫 화면 법칙, 섹션별 카피라이팅 가이드, Claude Code 통합 섹션, 안티패턴, 게시 전 체크리스트. Triggers: "write README" | "README template" | "GitHub README" | "project description" | "tagline" | "open source README" | "README structure" | "README review" | "fix README" | "rewrite README" | "README写作" | "写README" | "README模板" | "项目介绍" | "开源项目文案" | "改README" | "README检查" | "README 구조" | "README 작성" | "README 검토" | "READMEの書き方" | "READMEレビュー"
Reviews pytest test code for async patterns, fixtures, parametrize, and mocking. Use when reviewing test_*.py files, checking async test functions, fixture usage, or mock patterns.
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。
Applies fixes from a prior review-llm-artifacts run, with safe/risky classification. Respects verify-llm-artifacts output when present to skip false positives.
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。
Golden-fixture contract discipline: locations, bless workflow, env vars, volatile-field scrubbing, failure-artifact triage. Use when a golden/snapshot test fails or a new golden fixture is added.
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。
Run a Meta-Harness-style optimization loop NATIVELY — automatically search over the scaffolding around a FIXED base model (memory, retrieval, context construction, prompt templates, summarization, tool-selection logic) by proposing candidate variants, scoring each on a cheap deterministic eval, and keeping a Pareto frontier of quality vs cost — using native Agent / Workflow / loop tools instead of a standalone Python harness. Use this whenever the user wants to optimize, evolve, tune, distill, or search over a harness, scaffold, prompt system, memory or retrieval policy, context-assembly code, or summarizer while keeping the model fixed; whenever they mention Meta-Harness, harness optimization, scaffold evolution, automatic prompt/memory optimization, an evolutionary or Pareto search over candidate implementations, or "make the harness/agent better without retraining"; and whenever the gain must come from the code AROUND the model rather than the model weights. Reproduces the Meta-Harness paper's method natively, with no claude_wrapper.py and no metered solver API.
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。
Investigate merkle root mismatch alerts between relayer and validators. Use when alerts mention "merkle root mismatch", "checkpoint root does not match canonical root", or when asked to debug relayer merkle tree issues for a chain. This skill only investigates - use /fix-merkle-root-mismatch to apply fixes.
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 fixes for merkle root mismatch issues in the relayer database. Use after running /investigate-merkle-root-mismatch to investigate and identify the mismatched entries. Requires user confirmation before any database modifications.
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 fixing HustleXP revenue collection bugs including Stripe platform fee not being collected (application_fee_amount missing), escrow fee miscalculation using task.price instead of escrow.amount, self-insurance pool never funded, tip platform cut absent, subscription renewal revenue not logged, or XP tax path unreachable. Covers all platform fee issues and financial invariant checks.
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。
Audit existing mocks and test doubles — find contract drift, missing error cases, and stale fixtures. Use when asked to "audit our mocks", "find stale test fixtures", or "check for contract drift".
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 a mock server for an API — tooling selection, response fixtures, and error scenarios. Use when asked to "build a mock server", "mock this API for development", or "create response fixtures".
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。
Real-time log monitoring, crash detection, and auto-hotfixing code without human intervention / Pemantauan log real-time, deteksi kerusakan, dan perbaikan kode hotfix otomatis tanpa intervensi manusia.
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。
Elite frontend design taste for building, reviewing, and polishing web interfaces. Use whenever the user wants to design, redesign, shape, critique, audit, polish, or improve any UI (landing pages, portfolios, dashboards, product UI, components, forms, onboarding, empty states) or asks to make something look better / premium / modern, fix the styling, add or fix animations, or make a design feel less generic ("AI slop"). Covers typography, color, spacing, layout, visual hierarchy, motion, micro-interactions, component states, accessibility, responsive behavior, UX copy, and anti-pattern detection.
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。
Handles PR review comments and feedback resolution. Use when user wants to resolve PR comments, handle review feedback, fix review comments, address PR review, check review status, respond to reviewer, verify PR readiness, review PR comments, analyze review feedback, evaluate PR comments, assess review suggestions, or triage PR comments. Fetches comments via GitHub CLI, classifies by severity, applies fixes with user confirmation, commits with proper format, replies to threads.
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。
Optimize Core Web Vitals (LCP, INP, CLS) for better page experience and search ranking. Use when the task involves `improve Core Web Vitals`, `fix LCP`, `reduce CLS`, `optimize INP`, `page experience optimization`, or `fix layout shifts`.
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。
This skill should be used when validate-chunk reports errors or failures, when the user asks to "fix these errors", "resolve validation issues", "refine this chunk", or when specific build, lint, or type errors need surgical fixes. Makes precise, targeted edits to resolve specific validation issues without over-engineering.
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。