「did」の検索結果

QA a change by driving the running dev app like a real QA engineer - start the server and a real browser session, write a checklist from the agreed requirements and the diff, execute every item with evidence, then go looking for anything that looks off even where the diff did not touch. Reports findings by severity and separates regressions from pre-existing problems. Use after a change is implemented and the gates pass, when the user asks to "QA this", "test it in the app", or "check it actually works".

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。

Estimate the full development cost of an existing codebase from lines of code, architectural complexity, and team-composition overhead. Use for 'how much would this cost to build', 'what did this codebase cost', development-cost or build-cost estimates, calendar-time estimates, and Claude/AI ROI on a delivered codebase. Estimates by measured LOC and complexity, not by ticket volume.

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。

ADMET (Absorption, Distribution, Metabolism, Excretion, Toxicity) prediction for drug candidates. Use for assessing drug-likeness, PK properties, and safety risks early in drug discovery. Keywords: ADMET, PK, toxicity, drug-likeness, DILI, hERG, bioavailability

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。

Multi-age family playing in a park, golden-hour lighting, candid expressions, using reference photos

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。

Automate recruiting and hiring workflows in Ashby -- manage candidates, jobs, applications, interviews, and notes through natural language commands.

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。

Analyze recent code changes via git history and extract software engineering lessons. Use when the user asks 'what is the lesson here?', 'what can I learn from this?', 'engineering takeaway', 'what did I just learn?', 'reflect on this code', or wants to extract principles from recent work.

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。

Interactive daily standup/meeting update generator. Use when user says 'daily', 'standup', 'scrum update', 'status update', 'what did I do yesterday', 'prepare for meeting', 'morning update', or 'team sync'. Pulls activity from GitHub, Jira, and Claude Code session history. Conducts 4-question interview (yesterday, today, blockers, discussion topics) and generates formatted Markdown update.

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。

决策调研 / Decision-Driven Research：当用户面对一个具体决策需要找信息时使用——「有没有现成方案」 「怎么接入 X 平台」「这个技术可行吗」「业界怎么做 Y」「选 A 还是 B」「桌面端应该怎么定位」 「高级版和基础版怎么拉开差异」「这个产品方向对不对」。 核心行为：先框定研究层级和问题类型，再锚定决策问题，枚举竞争假设，主动找反对证据， 用排除逻辑给出有立场的结论。支持技术选型、产品策略、商业判断、竞品定位等所有需要做决定的调研。 可用中文唤起：「帮我调研」「有没有现成方案」「这个怎么接」「技术上可行吗」「帮我选一个」 「这个产品方向对不对」「我们应该怎么定位」「行业怎么做」。 与 research-topic-compiler 的边界：需要最终选择、推荐、排除理由、置信度和颠覆条件时用这个； 如果目标是长期学习、候选池沉淀或 Research Project，用 research-topic-compiler，再把 Candidate Backlog 交回本 Skill 做最终决策。 只有发现一个会实质改变结论、可研究且可关闭的证据 gap 时，才向 research-topic-compiler 发出精确 Return Request。 不用于：问题还没定义清楚时（先用 ai-collaboration-calibration L4-fuzzy 脑暴）。

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Prove — or honestly fail to prove — a specific technical claim: "the fix works", "it's deployed", "the service is running", "the site is done", "there are no vulnerabilities". Atomizes the claim, picks the shortest decisive signal on the evidence ladder, and returns a verdict from a fixed vocabulary (pass / partial / fail / skip) with an explicit coverage boundary. NOT code review, NOT a fix, NOT orchestration — only "what is proven, and what we merely hope". Triggers — "prove it works", "is it really done?", "are you sure?", "we deployed — is it live?", "verify that", "did we actually check?".

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。

Teacher mode — turn a session recap / article / docs / concept / piece of code / bug into an incremental mini-course with comprehension checks, quizzes, and an auto-saved summary note. Invoke /teach [topic or URL]. Triggers — "explain it like a teacher", "walk me through what we did", "turn this into a lesson", "quiz me", "teach me", "let's learn this together".

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Use this skill when authoring or debugging GitHub Actions workflows (.github/workflows/*.yml) — e.g. "add CI for this Drupal project on GitHub", "run phpcs/phpstan/phpunit on pull requests", "cache composer dependencies", "deploy over SSH when main is pushed", "why didn't my workflow trigger", or anything involving jobs, matrices, runners, secrets, or reusable workflows.

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。

Researches and compares free and open source software projects in a supplied domain, using either user-named candidates or a discovered shortlist. Use when evaluating FOSS alternatives, comparing GitHub popularity, maintenance, licences, domain fit, trade-offs, or producing a linked HTML comparison report.

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。

以固定的九节结构生成美国司法意见书的详细法学院案件简报：记忆钩子、事实、程序历史、 法官投票、判决要旨、逐意见分析、五个未来适用假设情形、评论和已核实的关键引文。 还构建投票表、跨案件一致性表、基于视角的评论，以及 article、Beamer 和案例教科书章节格式的 LaTeX。 当有人要求简报案件、分析或解释意见、为学生总结决定、从判决要旨生成假设情形、 评论判决、制表法官投票方式，或将案件分析转换为 LaTeX 时使用。触发词包括 "brief this case"、"case brief"、"explain the holding"、"what did the court hold"、 "hypotheticals based on"、"critique this opinion"、"vote table"、"Beamer presentation"、 "chapter brief"，以及在教学情境中对司法意见或最高法院决定的任何引用。 需要网络搜索来核实引文、投票和判决要旨。

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。

Capture, gate, and query long-term project knowledge via the gated wiki subsystem: propose candidates, recall, or search; agents propose, humans approve. NOT for short-lived memory (mk:memory).

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。

Fetch external sources (web/arXiv/GitHub) into scanner-gated wiki CANDIDATES, never canonical pages: guarded, capped, scanned. NOT for local knowledge (mk:wiki) or markdown fetch (mk:web-to-markdown).

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。

Weekly-cadence engineering retrospective. Analyzes commit history, work patterns, and code quality metrics with persistent history and trend tracking. Team-aware: breaks down per-person contributions with praise and growth areas. Use when asked to "weekly retro", "what did we ship", or "engineering retrospective". Proactively suggest at the end of a work week or sprint. NOT for per-session or per-task reflection (see mk:memory / Phase 6 Reflect).

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 surfacing architectural friction and proposing deepening refactors (shallow modules → deep modules) for testability and AI-navigability. Triggers on "improve architecture", "find deepening opportunities", "where is this codebase shallow", "architecture review". Emits structured candidates + precise patches; delegates ALL rendering to mk:preview. NOT for diagram/HTML rendering (see mk:preview); NOT for trade-off deliberation (see mk:party); NOT for plan critique (see mk:plan-ceo-review).

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。

Analyze task trajectories to propose reusable SKILL.md candidates from successful 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。

다중 세션 transcript에서 반복 실패 패턴(instinct)을 자동 채굴하여 신규 skill candidate 생성

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Prepare qualified Fusion CAM setups, operations, toolpaths and quarantined NC candidates using explicit manufacturing assets and authority. Never controls physical equipment.

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。

Reflect subskill for simmer. Records iteration results in trajectory table, tracks best candidate, handles regression rollback, and passes ASI forward to the next round. Supports both single-file and workspace modes. Do not invoke directly — called by simmer orchestrator after each judge round.

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。

Judge subskill for simmer. Scores a candidate artifact against user-defined criteria on a 1-10 scale and produces ASI (highest-leverage direction) for the next generator round. Supports judge-only, runnable evaluator, and hybrid evaluation modes. Do not invoke directly — dispatched as a subagent by the simmer orchestrator.

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。

Safely localize unknown Unity games, especially Japanese-to-Chinese projects. Use to discover Unity version/layout/backend, migrate translations across game versions, extract occurrence-mapped text from serialized assets, embedded CSV, bytecode, UI, Localization StringTables, Utage, or middleware, bridge rows through AiNiee-style translation, validate and transactionally write approved candidates, audit residual and runtime-only text or AutoTranslator diffs, diagnose TMP fonts and Addressables/IL2CPP failures, locate saves, or acceptance-test SHA-verified patches.

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Matches natural language task descriptions to appropriate skills using semantic similarity, ranks candidates by fit and performance history, and maintains the skill catalog. Use when assigning skills to DAG nodes, searching for the right skill for a task, ranking competing skills, or browsing the skill catalog. Activate on "find skill", "match skill", "which skill", "skill for this task", "skill catalog", "rank skills", "best skill". NOT for executing DAGs (use dag-runtime), creating skills (use skill-architect), or grading skills (use skill-grader).

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。