「local」の検索結果

Expert in building custom tools that solve your own problems first. The best products often start as personal tools - scratch your own itch, build for yourself, then discover others have the same itch. Covers rapid prototyping, local-first apps, CLI tools, scripts that grow into products, and the art of dogfooding. Use when "build a tool, personal tool, scratch my itch, solve my problem, CLI tool, local app, automate my, build for myself, " mentioned.

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。

The craft of weaving story into interactive systems where the player is both audience and author. This skill covers the unique challenges of game narrative: branching structures that respect player agency, environmental storytelling that rewards exploration, dialogue systems that feel alive, and the delicate balance between authored experience and emergent narrative. Unlike linear media, games don't tell stories TO players - they create the conditions for stories to emerge WITH players. The narrative designer's job is to build the scaffolding that supports infinite player-authored moments while maintaining coherent themes and emotional arcs. This skill synthesizes lessons from Disco Elysium's internal monologue as gameplay, Hades' death-as-narrative-engine, interactive fiction's branching mastery (Inkle, Twine), and procedural narrative pioneers like Dwarf Fortress. It addresses ludonarrative harmony, bark systems, cinematics that respect agency, and the "and therefore" test that separates plot from story. Use when "narrative design, game story, game writing, dialogue system, branching narrative, player choice, environmental storytelling, bark system, quest design, lore delivery, ludonarrative, interactive fiction, inkle, twine, dialogue tree, player agency, cinematic design, voice direction, localization, procedural narrative, narrative, game-writing, dialogue, branching, player-agency, environmental-storytelling, quest-design, voice-acting, localization, interactive-fiction, procedural-narrative, ludonarrative" mentioned.

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。

Expert at building multi-language applications. Covers next-intl, react-i18next, ICU message format, RTL support, date/number formatting, and translation workflows. Use when "i18n, internationalization, translation, multi-language, localization, next-intl, react-i18next, i18n, internationalization, translation, next-intl, localization" mentioned.

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。

Agent Manager Skill workflow skill. Use this skill when the user needs Manage multiple local CLI agents via tmux sessions (start/stop/monitor/assign) with cron-friendly scheduling and the operator should preserve the upstream workflow, copied support files, and provenance before merging or handing off.

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。

Agent Manager Skill workflow skill. Use this skill when the user needs Manage multiple local CLI agents via tmux sessions (start/stop/monitor/assign) with cron-friendly scheduling and the operator should preserve the upstream workflow, copied support files, and provenance before merging or handing off.

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。

招聘与猎头 (招聘与猎头 (Recruiting & Executive Search) — 面向甲方招聘负责人/HR 与市场化猎头顾问「双侧视角」的『把一个模糊的用人需求，变成一个来得了、干得好、留得住的人』的判断体系；不是候选人一侧的求职与简历面经（那是 job-hunting-coach 的范围），也不是薪酬绩效/员工关系/组织发展的泛 HR 全模块，更不是劳动法条文解读。覆盖：(a) 第一性张力 —— 这行的核心世界观分歧：**需求诊断优先 ⇄ 快速供给优先**（用人经理提来的岗位需求几乎总是一张愿望清单，资深招聘先开 intake 会把『必须有』与『最好有』拆开、把画像逼成可证伪的成功标准；但按成单计酬的猎头把诊断时间压不进单价里，于是行业里同时存在『先诊断再搜寻』和『先扔简历再说』两种作业习惯）；**结构化面试 ⇄ 看人的直觉**（工业与组织心理学近一个世纪的效度元分析一致指向：结构化面试、工作样本、认知能力测验的预测效度明显高于非结构化面谈与经验年限，但一线用人经理绝大多数仍相信自己聊两句就能看准人——这是本行最大的知行落差，也是所有循证招聘流派的出发点；顺带一提，业内长期奉为圭臬的 Schmidt-Hunter 效度排序近年被重新校正，工作样本的效度被下调，这场修正本身就是本行必须如实呈现的争议）；**能力素质 ⇄ 文化匹配**（culture fit 既是最常被写在拒信里的理由，也是被批评得最凶的偏见外壳，Google 一派主张改口叫 culture add，看的是这个人补上了团队缺的东西，而不是像不像我们）；**主动寻访 sourcing ⇄ 被动投递漏斗**（高端与稀缺技能岗只有 outbound 人才地图一条路；量大岗位靠渠道效率、转化率与自动化，两条路的技能树几乎不重叠）；**人才地图是资产 ⇄ 人才地图是浪费**（保留制猎头把 mapping 当交付物的一部分，成功付费猎头认为地图做完单子已经黄了）；**保留制 retained ⇄ 成功付费 contingency**（按阶段预付、独家、深度地图 vs 多家赛马、入职才收钱、速度压倒深度；两种商业模式塑造出两种截然不同的作业节奏、候选人对待方式与职业道德边界，比如 off-limits 不挖回自己安置过的人）；**内部招聘团队 ⇄ 外部猎头与 RPO**（成本、速度、知识沉淀、雇主品牌归属谁的长期争论；embedded recruiter 是近年的折中）；**候选人体验 ⇄ 筛选效率**（漏斗越严体验越差，被拒者也是客户与口碑）；**AI 筛选的效率 ⇄ 合规与偏见**（简历解析、AI 面试评分、自动排序已在大规模使用，同时被监管盯上：纽约市 Local Law 144 要求自动化决策工具做偏见审计并公示、欧盟 AI 法案把招聘划为高风险场景、伊利诺伊州对 AI 视频面试单独立法；业内既离不开它，也在诉讼与审计里学做记录）；**offer 谈判的锚定 ⇄ 薪酬透明**（多地薪酬区间披露立法把谈判起点从『你现在多少』改成『这个岗位值多少』，问薪酬历史在不少法域已被禁止）；**counter-offer 该不该接**（猎头几乎一致反对，认为留下来的人多数一年内还是会走，但这条业内定论的证据基础本身也在被质疑）；**入职后早期流失算谁的**（保证期与退款条款把这场争论直接写进了合同）。(b) 工具栈 —— 申请人追踪系统 ATS（Greenhouse、Lever、Ashby、Workday Recruiting、SmartRecruiters、iCIMS、Taleo，中国侧 Moka、北森、大易、e成）、猎头 CRM 与交付系统（Bullhorn、Vincere、Loxo、Clockwork、Recruit CRM）、寻访与触达（LinkedIn Recruiter、SeekOut、hireEZ、Amazing Hiring、GitHub 与学术检索，中国侧 BOSS 直聘、猎聘、脉脉、拉勾、牛客）、评估与测评（HackerRank、CodeSignal、CoderPad、结构化面试题库与 scorecard 评分卡、Hogan、SHL、Predictive Index、Criteria、案例作业与工作样本）、面试调度与视频（GoodTime、Calendly、HireVue、Spark Hire）、背景调查与合规（HireRight、Checkr、Sterling，中国侧 i背调、八方锦程，以及个人信息保护法与 GDPR 下的授权链、FCRA 的不利行动通知）、数据与漏斗分析（time to fill 与 time to hire 的口径差异、offer 接受率、通过率与转化漏斗、quality of hire 的度量困境、招聘成本 cost per hire 的口径战争）、以及最被低估的纸笔工具（intake 提纲、成功标准清单、scorecard、人才地图表格、Boolean 检索式、一页纸的岗位价值主张）—— 选型的真正分岔从来不是功能清单，而是『你的岗位是靠触达赢还是靠转化赢』。(c) 心智模型层 —— 招聘是一次双向销售而不是一场考试；岗位画像要写成结果（这个人半年内要做成什么）而不是资历清单；信号与噪音（公司名与学历是弱信号，工作样本与具体行为证据是强信号）；结构化与评分卡的意义在于让判断可比而不是显得严谨；漏斗每一层都在丢人，所以要从入职倒推触达量；稀缺人才不看招聘广告，只在熟人与私域里流动；offer 是谈判也是承诺，谈崩与反悔的代价高度不对称；招聘的质量要到入职之后才结算。(d) 工作流 —— intake 需求诊断会、岗位画像与成功标准、渠道策略与人才地图 mapping、Boolean 与主动触达、简历筛选与电话初筛、结构化面试与 debrief 定校准、工作样本与技术评估、reference check 与背调、offer 设计与谈判、counter-offer 应对、入职前 no-show 防范与 pre-boarding、试用期与早期留存复盘、招聘漏斗与数据复盘、以及岗位关闭或撤销时的收尾。(e) 表达 DNA、质量基准（什么算一次好的招聘）、反模式（外行与新手最容易犯的错：照抄 JD、面试问脑筋急转弯、用薪酬历史锚定、把候选人当库存、背调走过场、offer 口头承诺）、智识谱系（工业与组织心理学的效度学派、循证与结构化招聘派、保留制高管寻访派、增长型 sourcing 与招聘运营派、雇主品牌与候选人体验派、中国互联网大厂的人才盘点与赛马派）。) Master OS — automated mastery of 招聘与猎头 (Recruiting & Executive Search) — 面向甲方招聘负责人/HR 与市场化猎头顾问「双侧视角」的『把一个模糊的用人需求，变成一个来得了、干得好、留得住的人』的判断体系；不是候选人一侧的求职与简历面经（那是 job-hunting-coach 的范围），也不是薪酬绩效/员工关系/组织发展的泛 HR 全模块，更不是劳动法条文解读。覆盖：(a) 第一性张力 —— 这行的核心世界观分歧：**需求诊断优先 ⇄ 快速供给优先**（用人经理提来的岗位需求几乎总是一张愿望清单，资深招聘先开 intake 会把『必须有』与『最好有』拆开、把画像逼成可证伪的成功标准；但按成单计酬的猎头把诊断时间压不进单价里，于是行业里同时存在『先诊断再搜寻』和『先扔简历再说』两种作业习惯）；**结构化面试 ⇄ 看人的直觉**（工业与组织心理学近一个世纪的效度元分析一致指向：结构化面试、工作样本、认知能力测验的预测效度明显高于非结构化面谈与经验年限，但一线用人经理绝大多数仍相信自己聊两句就能看准人——这是本行最大的知行落差，也是所有循证招聘流派的出发点；顺带一提，业内长期奉为圭臬的 Schmidt-Hunter 效度排序近年被重新校正，工作样本的效度被下调，这场修正本身就是本行必须如实呈现的争议）；**能力素质 ⇄ 文化匹配**（culture fit 既是最常被写在拒信里的理由，也是被批评得最凶的偏见外壳，Google 一派主张改口叫 culture add，看的是这个人补上了团队缺的东西，而不是像不像我们）；**主动寻访 sourcing ⇄ 被动投递漏斗**（高端与稀缺技能岗只有 outbound 人才地图一条路；量大岗位靠渠道效率、转化率与自动化，两条路的技能树几乎不重叠）；**人才地图是资产 ⇄ 人才地图是浪费**（保留制猎头把 mapping 当交付物的一部分，成功付费猎头认为地图做完单子已经黄了）；**保留制 retained ⇄ 成功付费 contingency**（按阶段预付、独家、深度地图 vs 多家赛马、入职才收钱、速度压倒深度；两种商业模式塑造出两种截然不同的作业节奏、候选人对待方式与职业道德边界，比如 off-limits 不挖回自己安置过的人）；**内部招聘团队 ⇄ 外部猎头与 RPO**（成本、速度、知识沉淀、雇主品牌归属谁的长期争论；embedded recruiter 是近年的折中）；**候选人体验 ⇄ 筛选效率**（漏斗越严体验越差，被拒者也是客户与口碑）；**AI 筛选的效率 ⇄ 合规与偏见**（简历解析、AI 面试评分、自动排序已在大规模使用，同时被监管盯上：纽约市 Local Law 144 要求自动化决策工具做偏见审计并公示、欧盟 AI 法案把招聘划为高风险场景、伊利诺伊州对 AI 视频面试单独立法；业内既离不开它，也在诉讼与审计里学做记录）；**offer 谈判的锚定 ⇄ 薪酬透明**（多地

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 a local agent needs to submit a concise public work-memory report for its own completed local task through `cg report work-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。

Apply semi-formal certificate reasoning to code analysis — patch verification, fault localization, patch equivalence. Use when reviewing patches, hunting bugs across scopes, comparing fixes, or when code reasoning requires tracing execution across files/modules. Triggers on code review, bug localization, patch comparison, name shadowing, scope analysis, regression checking.

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。

Ranked content search over a text corpus you point it at, using BM25 (via xhluca/bm25s). Corpus-agnostic: cloned repos, project knowledge stores, uploaded files and archives, any local directory. In-memory BM25 index per invocation, with a session-local disk cache for repeat runs against the same corpus. Use for "rank these documents", "search this corpus", "which files are most about X", "find content about Y", or any multi-word concept query against a known body of text where grep would return everything or nothing. Needs a corpus on disk. Not for searching stored memories or prior-session decisions (remembering), not for a named symbol or a file's structure (tree-sitting), and not for a literal string you could grep.

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。

Generates git patch files from codebase modifications for local application. Use when user mentions patch, diff, export changes, bring changes back, apply locally, or after editing uploaded codebases.

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。

Watch a video from YouTube, Instagram, X/Twitter, Vimeo, TikTok or any of ~1800 yt-dlp sites (or a local path). Downloads with yt-dlp, extracts auto-scaled frames with ffmpeg, pulls the transcript from captions (or local mlx-whisper fallback, no API key), and hands the result to Claude so it can answer questions about what's in the video.

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。

Computes a numeric or categorical answer to a quantitative data-science question by cleaning and analyzing local data files (CSV, Excel, TSV, and scientific formats .npz/.fits/.h5) with pandas, numpy, and scipy. Use whenever a task ships its own dataset (in whatever local directory it provides) and asks you to derive a value via statistical, geospatial, temporal, ratio, percentage, growth-rate, correlation, signal-processing, orbital, or forecasting analysis. Spans domains including archeology (demographics, paleoclimate proxies, radiocarbon dating, historical conflicts); biomedical/bioinformatics (tumor histology, genes, proteins, peptides, genomic variants); environmental (water quality, bacterial/Enterococcus exceedance, rainfall correlations, environmental justice); legal/consumer (fraud, identity theft, consumer complaints by state/metro); wildfire (incidents, causes, suppression costs, acres burned, fatalities, geospatial intersections); and astronomy/heliophysics/space weather (satellite telemetry TLE/Swarm/SP3, indices OMNI/GOES, solar activity, atmospheric density, orbital mechanics, forecasting).

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。

Answer user questions about QwenPaw installation and configuration: first locate and read local documentation, then distill the answer; if local information is insufficient, fall back to the official website documentation.

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。

Save a site or section as local files (markdown, screenshots). Use for "download the site", offline docs, or a local copy for reference.

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。

The local task workspace, the build/test commands the hand-off gate runs, and the file and exploration tools. Use when starting work in a task workspace or before running any build, test or verification command.

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 only when the user explicitly asks to launch or inspect the LOCAL Cognee UI (the cognee-cli dev UI). For "is Cognee running/connected" or any configuration question, use the setup skill instead. Does not apply in cloud mode.

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。

Save a site or section as local files (markdown, screenshots). Use for "download the site", offline docs, or a local copy for reference.

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 production-grade i18n/l10n for React, Vue, Angular, and Next.js with ICU format and RTL support. Use when setting up or debugging localisation.

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 local AI engines for iOS. Use when wiring Apple Foundation Models, local classifiers, extraction, summarization, grounded answers, and cloud fallbacks.

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。

Runs local and self-hosted LLMs with Ollama, LM Studio, MLX, llama.cpp, and Open WebUI. Use when choosing GGUF quants, sizing VRAM, or running models privately.

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。

Install a Skill into the current workspace from a Git repository or local directory. Use this whenever the user wants to: - Add a new Skill to the agent ("install the X skill", "add the foo skill", "I want a skill that does Y, find one") - Pull the latest version of an already-installed Skill ("update the X skill", "refresh my skills") - List Skills currently active in the workspace - Remove a Skill they no longer need Trigger on phrases like "装一个 X skill", "安装技能", "install skill", "update skill", "list skills", "remove skill", "找个能 X 的 skill". Do not require the user to say the literal Skill name — if they describe a capability, propose a candidate Skill (Git URL or local path) and confirm before installing.

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。

Search synced Temu category data in the local database by keyword to find category Chinese names, English names, and category IDs for use in product/store filtering. Triggered when users mention Temu categories, Temu category ID, Temu category tree, Temu backend categories, temu categories, syncTemuCategory (Temu category sync) followed by category queries, or Temu category search. Even if the user does not mention the tool name, this skill should be triggered whenever searching for category IDs by keyword in the locally synced Temu category database.

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。

教師なし分析と EDA 前処理（欠測 / 欠損 / NaN / 補完 / imputation / 外れ値処理、クラスタリング / セグメンテーション / k-means / 階層クラスタリング / GMM / DBSCAN、次元削減 / PCA / 主成分分析 / 因子分析 / UMAP / t-SNE、異常検知 / anomaly detection / 不正検知）を実行したら必ずセットで出す図と値のルーター。fillna, dropna, fill_null, SimpleImputer, IterativeImputer, missingno, KMeans, AgglomerativeClustering, DBSCAN, GaussianMixture, silhouette_score, dendrogram, PCA, FactorAnalysis, calculate_kmo, TSNE, umap.UMAP, IsolationForest, LocalOutlierFactor, pyod がコードに現れたとき、またはユーザーが「欠損を埋めて」「クラスタリングして」「主成分で 要約して」「異常を検知して」「データをきれいにして」と言ったときに使う。安定性・k の根拠・平行分析・ベースラインに 言及がなくても適用する。SKILL.md のルーティング表で手法を特定し、対応する references/<手法>.md を読んでから実行する。 教師あり予測は predictive-modeling-diagnostics、回帰・検定は statistical-inference-diagnostics を使う。

Present pathway options and orchestrate place-based curriculum design from a local place, curriculum requirement, or community issue. Use when place should become a primary text for learning.

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。