「grounding」の検索結果

Use this skill to verify CLAIM-LEVEL grounding of a documentation page (or set of pages) against the source code. Activate when you have specific pages to check for factual accuracy -- not when sweeping a whole corpus (use docs-corpus-audit for that) and not when triaging a PR diff (use docs-sync for that). Trigger nouns: "is this doc accurate", "verify the page against the code", "fact-check this section", "any claims that drifted from source", "fact-checking", "grounding audit", "drift hunt", "claim verification". Returns per-claim verdicts (GROUNDED | PARTIAL | CONTRADICTED | UNSUPPORTED) with file:line evidence citations. Catches paragraph-level inaccuracies that page-level audit averages over -- e.g. a paragraph with 5 claims where 4 are grounded and 1 is fabricated. Does NOT modify files (returns advisory only); does NOT re-architect the docs; does NOT triage PRs.

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构建 GUI 自动化 Agent、让 Agent 像人一样看屏幕并用鼠标键盘操作桌面或浏览器软件时使用。 覆盖感知-思考-行动循环、动作空间（GUI/bash/文件编辑）、视觉定位 Grounding 三条路线 （结构化元素索引、Set-of-Mark、纯坐标预测）、分辨率坐标缩放、关键帧观察接口、世界模型与移动端生态壁垒。 触发词：Computer Use、GUI 自动化、截图、Grounding、browser-use、Set-of-Mark、视觉定位、坐标缩放、OSWorld。

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.NET MAUI app lifecycle guidance — the four app states, cross-platform Window lifecycle events (Created, Activated, Deactivated, Stopped, Resumed, Destroying), platform-specific lifecycle mapping, backgrounding and resume behavior, and state-preservation patterns. USE FOR: "app lifecycle", "window lifecycle events", "save state on background", "resume app", "OnStopped", "OnResumed", "backgrounding", "deactivated event", "ConfigureLifecycleEvents", "platform lifecycle hooks". DO NOT USE FOR: navigation events (use maui-shell-navigation), dependency injection setup (use maui-dependency-injection), platform API invocation (use conditional compilation and partial classes).

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[omh] Deep dive before a decision: deep research engine - grounding for specs and decisions: study open-source reference implementations with pinned refs, gather live web evidence with citation discipline, verify contested claims, and distill a decision-grounding dossier that planning consumes; for a decision brief use research-brief, for upstream guidance use web-research. Use when the user says: research plan, literature review, research literature, review recent papers, deep research, deep-research, exhaustive research, saturation research.

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Establish what is actually true and current for the surface you are about to change — not just search. Grounding = locate the authoritative source and reconcile sources that disagree (code vs doc, migration vs schema, memory vs current code, live vs archived), not take the first hit. Use before any grep/find/explore of the codebase or docs, when deciding which of several definitions is the real one, or when a doc or memory conflicts with the code. Covers the source-of-truth hierarchy, reconciliation discipline, scoped ripgrep, and the docs/tags.yml + docsearch.py index.

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。

.NET MAUI app lifecycle guidance — the four app states, cross-platform Window lifecycle events (Created, Activated, Deactivated, Stopped, Resumed, Destroying), platform-specific lifecycle mapping, backgrounding and resume behavior, and state-preservation patterns. USE FOR: "app lifecycle", "window lifecycle events", "save state on background", "resume app", "OnStopped", "OnResumed", "backgrounding", "deactivated event", "ConfigureLifecycleEvents", "platform lifecycle hooks". DO NOT USE FOR: navigation events (use maui-shell-navigation), dependency injection setup (use maui-dependency-injection), platform API invocation (use conditional compilation and partial classes).

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。

Test AI/LLM features that ship in your product. Covers prompt regression testing, response quality evaluation, tool-call validation, hallucination and RAG grounding checks, nondeterministic-output strategies, red-team/safety scans, eval frameworks, and agent-as-target injection (indirect injection via tool output / RAG / scan reports, self-propagating payloads, data exfiltration via an agent) plus a bundled detector for untrusted content. Use when: "test our LLM feature," "prompt regression test," "eval framework," "hallucination test," "RAG grounding," "nondeterministic output," "AI feature testing," "red-team our chatbot," "indirect prompt injection," "agent reading untrusted tool output," "production AI quality." Not for: using AI to generate your own test code — use ai-test-generation. Not for: classifying CI failures with AI — use ai-bug-triage. Not for: EU AI Act / GDPR conformity of an AI feature — use compliance-testing. Not for: canary/flag rollout of an AI feature — use testing-in-production. Related: ai-test-generation, ai-qa-review, api-testing, compliance-testing, security-testing, risk-based-testing, test-data-management.

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。

Grounding-theory primitives for common ground and repair. Use when deciding whether to ask a clarifying question, confirming a handoff was understood, or fixing multi-turn 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。

Use when Agentforce run costs are climbing, you need to forecast scale, or you want to reduce tokens per conversation without hurting quality. Covers topic (now subagent) design impact on cost, prompt/template reuse, grounding size discipline, caching, and model-tier selection. Triggers: 'agentforce cost', 'tokens per conversation too high', 'reduce agentforce runs spend', 'forecast agentforce scale cost', 'einstein trust layer tokens'. NOT for capping spend per user with a budget gate and fallback — use agentforce/agent-rate-limit-strategy. NOT for org-wide model-tier and BYOLLM platform strategy — use architect/ai-platform-architecture.

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Router for the 53 SfSkills `agentforce` skill packages. Agentforce and Einstein: agents, topics, actions, prompt templates, grounding, guardrails, evaluation and production readiness. Use when the request mentions Agentforce, agent topic, agent action, prompt builder, Einstein, Trust Layer, grounding, RAG, guardrails, agent evaluation, prompt injection. Finds and opens the exact skill package to read; it does not contain the guidance 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。

Forces Claude to extract exact quotes from files before making claims about them. Prevents hallucinations by grounding every statement in actual text from the codebase. Use when working with large files or unfamiliar code.

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。

Shared corpus-grounding engine — BM25 + structured filters + decision rules over CSV corpora via a domain manifest. Use when a skill needs grounded pre-action option-space constraints.

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。

稳定化技术：着陆技术（Grounding）、安全岛/安全场所（Safe Place）、封存/保险箱技术（Containment）及呼吸练习。用于应对急性心理困扰和惊恐发作的即时干预技术。

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Техники стабилизации: Заземление (grounding), безопасное место, техника контейнирования и дыхательные упражнения. Экстренные техники при остром стрессе и панических атаках.

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。

Técnicas de estabilización: Anclaje (grounding), lugar seguro, técnica de contenedor y ejercicios de respiración. Técnicas inmediatas para malestar agudo y ataques de pánico.

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。

Stabilization techniques: Grounding, safe place, containment, and breathing exercises. Immediate techniques for acute distress and panic attacks.

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。

Erstellt oder überarbeitet einen Skill FÜR DIESES ÖKOSYSTEM: delegiert die generische Interview-/Entwurfs-/Eval-Schleife an das offizielle skill-creator-Plugin (Anthropic, Apache-2.0), setzt aber zusätzlich die ellmos-Anforderungen durch, die das offizielle Plugin nicht kennt — Haus-Frontmatter (9 Felder), Kategorie/Sichtbarkeits-Regeln, anbieter-/nutzer-/ellmos-neutrale aber ellmos-sensitive Erkennung via grounding-seed, mitgelieferte config.json (inkl. Lernvertrag) + connections.json, Anbieter-/Vendor-Bewusstsein (State-of-the-Art-Alternativen inkl. eigener ellmos-Komponenten vorschlagen), einen Selbstaktualisierungs-Abschnitt UND einen wiederverwendbaren Lern-/Abdeckungs-Dateisatz (user-usecases.json, usecase-gaps.json, known-providers-and-abilities.json, gap-closing-analysis.json — an skill-creators evals.json und A2A/AgentSkill angelehnt, kein Parallelstandard). IMMER nutzen, wenn ein NEUER Skill für dieses System entstehen oder ein bestehender auf ellmos-Konformität nachgerüstet werden soll — auch bei "erstelle einen Skill", "bau mir einen Skill für X", "skill-creator nutzen", "neuen Skill anlegen", "diesen Skill ellmos-konform machen", "Lernvertrag/Verhaltenscodex für einen Skill anlegen", "Usecase-Abdeckung eines Skills prüfen". Für reines Skill-FINDEN/ROUTEN stattdessen skill-finder, für Landschafts-Audit skill-explorer.

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 live fieldwork layer for psycho-logic — go look at the actual target market NOW instead of reasoning from your training-data stereotype of it. Use when a psycho-logic move needs grounding in a specific place: the user asks 'what do competitors in [region/country] actually do', 'what's the real price band / norm here', 'how do local leaders position themselves', 'research this market before we localise', 'what signals trust to buyers in X', or is about to launch/adapt in a market you haven't studied. Runs structured web research in the local language — local competitors and their signals, price bands, category conventions, review/trust sources, local terminology, taboos and regulations — and synthesises a compact perception profile the four moves consume. Inspired by Rory Sutherland's *Alchemy*. Routed to from psycho-logic; pair with cultural-context (the lens that tells you what to look for). 日本語・中文の相談（「現地の実態を調べて」「调研当地市场」）にも使う。

集めた素材から記事の展開を複数提案し、選んだ内容を一段ずつ書き進めます。読者が知っている概念を確認し、必要な説明を先に置きながら文章を組み立てるスキルです。

• 収集済みのメモを記事にしたいとき
• 記事の書き出しを比較したいとき
• 初心者向けに説明順を整えたいとき

記事やメモ、動画などをもとに、書き手の語り口を保ちながら、XやLinkedInの投稿、動画台本、ニュースレターを媒体に合う形で作るスキル。

• 一つの記事を複数媒体に展開したいとき
• 製品公開に向けた投稿の準備
• 短編動画やYouTubeの台本作成

Deduplicate and synthesize raw concept stubs into a tiered intellectual map (T1 Canon to T4 Riff), tracing idea evolution across sources over time. Transforms thousands of raw concept pages into a curated intellectual fingerprint. Includes a reversible curation cull pass (Phase 5) with hard keep/delete/merge verdicts, substance gates, grounding labels, cluster budgets, and merge-with-backlinks salience promotion.

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Discovers requirements and designs an end-to-end governed agentic analytics solution using Knowledge Catalog and Managed Service for Apache Spark (Lightning Engine). Use when designing data science and analytics workflows across structured and unstructured distributed data (including in S3, Azure Blob, AlloyDB, and Iceberg), establishing metadata governance with Knowledge Catalog aspect types, or grounding agentic IDEs (VS Code, Antigravity) by using the Google Cloud Data Agent Kit. Don't use for provisioning borderless data lakehouse infrastructure (use google-cloud-solution-agentic-ai-borderless-data-lakehouse instead).

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。

Workflow 4: Submission rebuttal pipeline. Parses external reviews, enforces coverage and grounding, drafts a safe text-only rebuttal under venue limits, and manages follow-up rounds. Use when user says "rebuttal", "reply to reviewers", "ICML rebuttal", "OpenReview response", or wants to answer external reviews safely.

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。

Research a competitive landscape with cited snapshots, a comparison matrix, and so-what implications. Use when a product decision needs competitive grounding, not a market 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。