760 件 ・ 関連度順
概要と使いどころ
Deep Interactive courses. Plans the course so the learner manipulates something on most pages — simulations, diagrams they explore, code they run, games, 3D scenes — with slides reserved for the opening frame and the closing consolidation. Use when the topic has a mechanism, a variable to vary, a process to trace, or a structure to inspect.
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 the user needs a local file converted between common image, audio, video, document, or data formats. Select installed tools, preserve originals, and verify the output.
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 cloud costs across AWS, Azure, GCP, and OCI through resource rightsizing, tagging strategies, reserved instances, and spending analysis. Use when reducing cloud expenses, analyzing infrastructure costs, or implementing cost governance policies.
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。
Migrates Oracle PL/SQL stored procedures to PostgreSQL PL/pgSQL. Translates Oracle-specific syntax, preserves method signatures and type-anchored parameters, leverages orafce where appropriate, and applies explicit collation mapping (`COLLATE "C"` only when appropriate, locale collations when required). Use when converting Oracle stored procedures or functions to PostgreSQL equivalents during a database migration.
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。
Audits, writes, and refines maintained first-party source-code comments and declaration-level documentation across languages. Use when adding, editing, reviewing, cleaning up, or auditing comments, doc comments, docstrings, TODO, FIXME, NOTE, suppressions, or other source commentary, including while modifying code and deciding whether a comment is warranted at all. Defaults to no comment unless it preserves meaningful, non-obvious information that cannot reasonably be recovered from the code or nearby repository context.
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。
Build an auditable evidence map for a contested technical choice, research synthesis, proposal review, or consequential decision. Use when Copilot must preserve supporting, contradicting, qualifying, and missing evidence with exact source regions instead of collapsing disagreement into prose.
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。
Stablecoin supply and flow analysis — USDT/USDC mint-burn signals, exchange stablecoin reserves, on-chain stablecoin velocity, and capital rotation indicators for crypto market timing.
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。
Reserved and on-demand GPU cloud instances for ML training and inference. Use when you need dedicated GPU instances with simple SSH access, persistent filesystems, or high-performance multi-node clusters for large-scale training.
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。
Take any book (EPUB/PDF), produce a personalized chapter-by-chapter analysis. Each chapter is preserved in detail (The Chapter) and mirrored back to the reader's actual life (The Mirror) using brain context. The mirror observes and resonates — a friend pointing out parallels, NOT a consultant rearranging the reader's life, NOT a therapist assigning homework. The reader decides what to do about it. Layout is a top-aligned HTML table or stacked sections, never a bare markdown pipe table (pipe tables center-misalign uneven columns). Output is a single brain page at media/books/<slug>-personalized.md plus an optional PDF via brain-pdf.
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。
When you report a brain page to the user — created, edited, committed, or relayed from a subagent — a working link is part of the deliverable, in the SAME message. Derive the path mechanically (git ls-files --full-name), push BEFORE linking, verify the link resolves when a hosted remote exists, and degrade through a defined fallback chain when it doesn't. Inside brain pages the rule inverts: relative links preserve the link graph; absolute URLs are for chat deliverables only.
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 an insight, decision, or learning to agentmemory's long-term storage with searchable concept tags. Use when the user says "remember this", "save this", "note that", "don't forget", or wants to preserve knowledge for future sessions.
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。
Write contextual commits that capture intent, decisions, and constraints alongside code changes. Use when committing code, finishing a task, or when the user asks to commit. Extends Conventional Commits with structured action lines in the commit body that preserve WHY code was written, not just WHAT changed.
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。
Company Architect: builds a business from scratch as an OKF (Open Knowledge Format) bundle — a tree of version-controllable .md files with frontmatter type, links forming a graph, and reserved index.md/log.md, readable by humans and agents. Guides the founder through a 12-phase interview (foundation, strategy, market, financial, sales, marketing, product, operations, tech, people, legal, governance), one phase at a time, few questions per block, and generates the concepts as conformant markdown. Trigger when the user wants to create, structure, or document an entire company in folders and .md files; when they mention build my company from scratch, company as code, company knowledge base for AI to read, company wiki for agents, OKF, or knowledge bundle. In English.
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 long-running agent sessions need context compression, structured summarization, compaction, token-per-task optimization, or durable handoff summaries that preserve decisions, files, risks, and next actions.
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。
Reserved and on-demand GPU cloud instances for ML training and inference. Use when you need dedicated GPU instances with simple SSH access, persistent filesystems, or high-performance multi-node clusters for large-scale training.
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 reasoning about what survives compaction/context-loss/restart/seat-refresh, designing a high-fidelity restore packet, or distinguishing native runtime resume vs fork vs artifact-backed mental-model rebuild. Covers the 4 failure modes that prevent honest restore (compacted seat drops hot potato; restore packet preserves details but loses product intent; runtime resume mistaken for handover or fork; rebuilt seat starts with stale instructions).
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 an agent is preparing or performing an OpenRig CLI/daemon upgrade and must preserve live seats, verify each mutation, or reconcile managed plugin and skill files without overwriting local 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。
Use when a question, decision, plan, tradeoff, or claim needs a rigorous verdict and one perspective is not enough. Spawns a panel of 3 to 5 subagent jurors that form independent blind opinions, deliberate anonymously under an anti-anchoring and anti-sycophancy protocol, and return one committed verdict with confidence, preserved dissent, and a concrete next action. Domain-agnostic across engineering, architecture, data, product, hiring, strategy, vendor choice, build-vs-buy, and research design. Trigger phrases include "convene a jury", "have agents debate and decide", "get a panel to decide", "multi-agent decision", "stress-test this and decide", "monte um juri", "tribunal de agentes", "painel para decidir". Do NOT use to only critique without deciding (use the-fool for that), to build a plan or write the solution itself, or for simple factual lookups.
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 preparing iPolloWork local changes for GitHub: stash or preserve local edits, sync the current personal branch with remote main, re-apply local work, diagnose conflicts, commit in English, push to the current remote branch, and open a PR to main without creating extra branches.
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 connected Notion pages and databases, verify the relevant sources, and produce concise answers that preserve links and uncertainty.
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。
Prevent and remove generic AI-generated design defaults, incoherent visual choices, and established UI defects while creating, revising, or reviewing websites, apps, screenshots, mockups, and design code. Use as a passive quality gate during UI work or for an explicit anti-slop cleanup; preserve the chosen art direction instead of forcing a neutral redesign.
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 LoopX must manage a multi-PR or multi-MR delivery program across one or more repositories: inventory current change requests, reconcile new/merged/closed or retargeted work, preserve requirement and dependency priorities, maintain a roadmap document, or monitor material lifecycle/check/review changes over time. Use provider-neutral snapshots and one grouped continuous monitor; do not use for deep per-PR code review, approval, commenting, or merge actions.
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。
Manage the user's shared agent-skill library via skills-manager-cli — install, update, remove, deploy or undeploy skills per agent, manage presets, organize tags, search, and adopt existing skills. Use this whenever the user wants Claude Code, Codex, Cursor, or another agent to gain or lose a skill, wants to organize the central library, or asks what is installed or deployed. Prefer this over direct agent-folder installs because Skills Manager preserves source metadata, preset membership, updates, and cross-agent deployment 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。
Use this skill before answering or editing whenever an MSTest v1/v2 project is being upgraded or repaired for v3. Triggers include QualityTools assembly references; MSTest.TestFramework/TestAdapter 1.x-2.x; "upgrade to MSTest v3"; comparing v1 and v2 migration paths; choosing MSTest or MSTest.Sdk; CS0411/CS1503 after a v3 package bump; DataRow type mismatch, MSTEST0014, or "Test data doesn't match method parameters"; .testsettings/LegacySettings to .runsettings; timeout changes; and net5.0 or other dropped v3 TFMs. Still use it when packages say 3.x but migration source errors or legacy settings remain. Preserve VSTest/MTP. Do not use for a clean v3 project, v3-to-v4, framework conversion, or runner-only migration.
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。