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「quest」の検索結果

7,916 件 ・ 関連度順

概要と使いどころ

Find documentation and repository evidence for library behavior, API contracts, error messages, and known bugs. Use when a programming question needs current public documentation, issues, pull requests, or implementation examples.

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。

firecrawl/firecrawl-claude-plugin2392026年10月14日 更新

dontbesilent 商业模式诊断。两种模式:问诊(消解你的问题)和体检(拆解你的商业模式)。 触发方式:/dbs-diagnosis、/问诊、「帮我看看商业模式」「诊断一下我的业务」「我有个商业问题」 Business model diagnosis using dontbesilent's ontological framework. Two modes: consultation (dissolve your question) and checkup (analyze your business model). Trigger: /dbs-diagnosis, "diagnose my business model", "I have a business question"

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。

skillmds/skillmd2322026年10月14日 更新

Use when preparing for, running, or closing a live meeting with an AI assistant dashboard. Triggers on "meeting copilot", "live copilot", "prepare for a call", "update copilot", "close the session", or requests to turn transcript chunks into meeting questions, topic maps, decisions, and follow-ups.

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。

serejaris/personal-corp-os2302026年10月8日 更新

Code review practices with technical rigor and verification gates. Use for receiving feedback, requesting code-reviewer subagent reviews, or preventing false completion claims in pull requests.

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。

secondsky/claude-skills2292026年9月28日 更新

architect

無料

Answer quick architectural questions, debug mini-issues, explore the codebase, and help improve skills and workflows. Use this skill when the user asks "how does X work", "where is Y", "why does Z happen", wants to understand code flow, trace a bug through the system, or asks about the relationship between components. Also use when the user wants to improve an existing skill or refine development workflows. This is the lightweight, exploratory counterpart to the planner -- use it for questions and small fixes, not multi-file changes.

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。

homebridge-plugins/homebridge-eufy2252026年10月13日 更新

Guide a user from an unclear idea to an actionable plan through the agent harness's native ask tool and clickable choices. Use when the user wants a guided requirements interview, step-by-step questions, help deciding what to build, or a button-led path from goals to scope, solution, and technology choices. Do not turn an ordinary implementation request or a single clarification into an interview.

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。

scarletkc/agents2242026年9月22日 更新

Decide whether a task deserves its own git worktree and, if chosen, run it end to end: branch from the integration branch rather than the current tree, keep the main working copy untouched while the task runs, compare the result against the untouched baseline before declaring it done, and prepare it for a pull request instead of merging. Use when a request says to do the work in a new worktree or branch, when a change is large or risky enough that the main tree should stay usable, when several tasks need to run in parallel on one repository, when a result has to be diffed against current behavior, and when deciding where screenshots, builds, and other artifacts produced in a worktree should end up.

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。

scarletkc/agents2242026年9月22日 更新

Judgment rules for locating the correct boundary of a requested change: staying inert outside it while completing every required site inside it. Use when scope is ambiguous, a diff touches neighboring surfaces, required dependent edits are unclear, or a proposed compatibility layer, migration, fallback, flag, abstraction, or parallel implementation may exceed the request.

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。

scarletkc/agents2242026年9月22日 更新

Teach any topic deeply from first principles and build evidence-based paths toward exceptional capability. Use when a user asks to understand, explain, learn, or deep-dive into a topic; asks why or how something works, why it matters, how alternatives compare, or what different perspectives reveal; requests current paradigms, a complete roadmap or curriculum, deliberate practice and feedback, or a top-1%-level mastery plan. Answer explanation questions completely before offering a curriculum; route explicit mastery goals to an adaptive practice and proof-of-capability system.

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。

tamdogood/builder-essential-skills2222026年8月17日 更新

team-mode

無料

Use when a task may benefit from a bounded subagent for implementation, large-codebase discovery at task start, independent review, requested or pre-commit code simplification, or expert work on complex decisions, modeling, automation, or repeated failures. The main agent chooses whether to delegate and accepts the result. Do not use for simple questions or short work with no meaningful review or delegation.

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。

oil-oil/codex-team-mode2192026年10月1日 更新

Break down full NeurIPS reviewer responses into structured rebuttal units. Use when input contains NeurIPS reviewer fields (Summary, Strengths and Weaknesses, Questions, Limitations) and numeric scores (Rating, Confidence, Quality, Clarity, Significance, Originality). Splits questions and limitations into granular response items while preserving original wording for quoted issues.

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。

runtsang/RebuttalStudio2182026年4月4日 更新

Break down full ICML reviewer responses into structured rebuttal units. Use when input contains reviewer summary/presentation/contribution/strength/weakness/question text and the goal is to split weaknesses/questions into granular R-style response items while preserving original wording for quoted issues.

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。

runtsang/RebuttalStudio2182026年4月4日 更新

Break down full ICLR reviewer responses into structured rebuttal units. Use when input contains reviewer summary/presentation/contribution/strength/weakness/question text and the goal is to split weaknesses/questions into granular R-style response items while preserving original wording for quoted issues.

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。

runtsang/RebuttalStudio2182026年4月4日 更新

Schedules meetings with internal and external stakeholders by parsing natural language requests, resolving time zones, checking calendar availability, proposing optimal slots, and managing invitations and RSVPs. Use when the user requests meeting scheduler or provides relevant inputs for this workflow.

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。

seb1n/awesome-ai-agent-skills2142026年8月10日 更新

Perform systematic exploratory data analysis to understand dataset structure, distributions, relationships, and anomalies before modeling. Use when a dataset is new, its quality is unknown, or the user requests open-ended profiling; use data-analysis instead for a defined hypothesis or decision question.

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。

seb1n/awesome-ai-agent-skills2142026年8月10日 更新

Write clear, searchable help center articles and FAQ entries based on support data, product documentation, and common customer questions. Use when the user requests knowledge base article writing or provides relevant inputs for this workflow.

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。

seb1n/awesome-ai-agent-skills2142026年8月10日 更新

Manage Git repositories and collaborative workflows — branching strategies, commit hygiene, conflict resolution, pull requests, hooks, and .gitignore management. Use when the user requests version control or provides relevant inputs for this workflow.

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。

seb1n/awesome-ai-agent-skills2142026年8月10日 更新

Perform thorough code reviews on files or pull requests, checking for bugs, security vulnerabilities, performance issues, and style violations. Use when the user requests code review or provides relevant inputs for this workflow.

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。

seb1n/awesome-ai-agent-skills2142026年8月10日 更新

Analyze datasets to answer defined questions through statistical methods, trend identification, hypothesis testing, and correlation analysis. Use when the user needs evidence-backed findings or decisions from data; use exploratory-data-analysis instead for open-ended first-pass profiling before questions are defined.

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。

seb1n/awesome-ai-agent-skills2142026年8月10日 更新

Use when user asks to analyze an image, describe image contents, or answer questions about a picture. iFlytek Image Understanding (图片理解) — analyze and answer questions about images using Spark Vision model. WebSocket API, pure Python stdlib, no pip dependencies.

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。

iflytek/iFly-Skills2092026年10月15日 更新

Generate content ideas backed by real audience demand data from Reddit questions, YouTube search gaps, Twitter discussions, and web search trends. Identifies proven topics, underserved questions, and content formats that outperform in your niche.

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。

sandbaseai/sandbase-skills2022026年9月26日 更新

localnet

無料

Start and interact with the Boundless localnet (docker compose-based local development network). Covers dev mode (fake proofs, broker included) and full proving mode, submitting requests, and debugging order flow. Use when the user wants to start localnet, run the local network, test proof requests locally, or debug broker/order-stream issues.

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。

boundless-xyz/boundless1932026年8月27日 更新

Internal — for Boundless team members only. Query Boundless broker telemetry tables on Redshift for prod/staging operational data. Use when the user asks about broker health, request evaluations, request completions, proving times, skip rates, telemetry data, or wants to run SQL against the telemetry database on live networks. Also covers historical telemetry through 2026-04-24 stored as Parquet archives in S3 (queried via DuckDB). Do NOT use for debugging local code changes, reviewing PRs, or investigating issues in the codebase itself.

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。

boundless-xyz/boundless1932026年8月27日 更新

Turn a decision you can't fully answer into a questionnaire for someone else to fill in.

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。

tt-a1i/matt-skills-with-to-goal1852026年10月10日 更新