1.6万 件 ・ 関連度順
概要と使いどころ
Frame multi-agent designs through explicit environment, autonomy, information, coordination, commitment, incentive, and verification assumptions. NOT for endorsing multi-agent architecture without need or claiming runtime correctness from conceptual methods.
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 or audit an agent identity, credential, session, continuity, and reputation plan. Use when attributed outcomes must survive key rotation, restart, recovery, or review; when choosing Elo, TrueSkill, a contextual bandit, or an LLM judge; and when making Sybil, newcomer, calibration, collusion, and evidence limits explicit. Produces a supplied-plan consistency audit, never proof of observed delivery, cryptographic identity, or live enforcement. NOT for proving personhood, global Sybil resistance, or an unobserved delivery.
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。
Implement WCAG 2.2 AA/AAA compliance with automated testing, keyboard navigation, screen reader support, and focus management. Activate on: accessibility audit, WCAG compliance, keyboard navigation, screen reader, aria attributes, axe-core, focus trap. NOT for: design-level accessibility review (use design-accessibility-auditor), color contrast only (use css-in-js-architect).
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 or review a declared control-command profile and its verb/backend lifecycle matrix. Distinguish policy denial, unsupported capability, delivery acknowledgement, independently observed effect, and unknown outcome; bind authorization to principal, target, scope, current policy, expiry, and fencing epoch. NOT for claiming runtime correctness, proving an adapter from declarations, or approving a control-panel button without independent runtime evidence.
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 in 3D computer vision labeling tools, workflows, and AI-assisted annotation for LiDAR, point clouds, and sensor fusion. Covers SAM4D/Point-SAM, human-in-the-loop architectures, and vertical-specific training strategies. Activate on '3D labeling', 'point cloud annotation', 'LiDAR labeling', 'SAM 3D', 'SAM4D', 'sensor fusion annotation', '3D bounding box', 'semantic segmentation point cloud'. NOT for 2D image labeling (use clip-aware-embeddings), general ML training (use ml-engineer), video annotation without 3D (use computer-vision-pipeline), or VLM prompt engineering (use prompt-engineer).
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 bounded applications and workflows for an always-on AI agent with episodic memory. Covers product ideas, persistence-dependent workflows, and constructed examples that make delegation, interruption, evidence, and opt-out explicit. Activate on: "what can an always-on agent do", "persistent agent use cases", "agent applications", "proactive agent ideas", "what to build with episodic memory", "always-on agent product", "personal AI assistant ideas", "/always-on-agent-applications". NOT for: building the architecture (use always-on-agent-architecture), designing inputs (use always-on-agent-inputs), safety and privacy (use always-on-agent-safety).
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。
Declare an agentic application's interaction disclosure, state, context, capabilities, and effect-control boundaries. Use for a reviewable design specification and static consistency audit before implementation. NOT for proving that controls are deployed or enforced, exposing private chain-of-thought, selecting a model/router, or designing a multi-agent protocol.
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。
Discover failure modes in Coval runs, uploaded conversations or local conversation exports using scoped sampling and transcript, audio and trace evidence. Prepare human review without inventing ground truth or launching new runs.
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。
Launch a specific Coval evaluation with explicit cases and execution bounds. Use when resources are already selected; for result analysis use quick-eval.
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。
Turn a large dataset (an existing oversized Coval test set, an export of past conversations, or a CSV/JSON of cases) into a small, high-signal Coval test set by removing duplicates, identifying unique scenarios, and selecting a representative, failure-weighted subset — then bulk-loading it with no row cap. Use when the user says "I have thousands of cases", "dedupe my test set", "my test set is too big", "turn this dataset into a test set", "pick representative scenarios", or "my CSV import only kept 10 / uploaded everything".
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。
Execute a bounded Coval evaluation on explicit test cases, then audit conversation, recording and metric evidence. Use when the user requests a run; does not automatically rerun, tune an agent or schedule evaluations.
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 a compact Coval test set from product requirements, observed conversation failures or a coverage gap. Design realistic scenarios with separate expected behaviors, provenance and controlled voice/persona variation.
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。
Archive a completed change in the experimental workflow. Use when the user wants to finalize and archive a change after implementation is complete.
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。
Ahrefs API analyst (extension). Reads referring domains, backlinks, organic keywords, and content explorer data via the tested @ahrefs/mcp@0.0.11 server. Pairs with seo-backlinks for multi-source confidence weighting.
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 content for AI Overviews (formerly SGE), ChatGPT web search, Perplexity, and other AI-powered search experiences. Generative Engine Optimization (GEO) analysis including brand mention signals, AI crawler accessibility, llms.txt compliance, passage-level citability scoring, and platform-specific optimization. Use when user says "AI Overviews", "SGE", "GEO", "AI search", "LLM optimization", "Perplexity", "AI citations", "ChatGPT search", or "AI visibility".
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。
Orchestrator that runs one UI brief through all four ui-* posture skills in parallel, then picks and merges a winner. Use when a screen matters enough to explore several directions, or the user says 'build it a few ways', 'design options', 'bake-off', 'show me variations', or 'compare approaches'.
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。
Discovery batch that grows the Provider Access Launch queue. Use when asked to find more user-connected OAuth, API, API-key, remote MCP, marketplace, or partner-access campaigns for a capability, provider family, MCP/plugin catalog, or competitive gap. NOT for client Local Listings distribution.
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。
Printing and PDF export for AI response blocks and messages via @ai-matrx/print. Use when adding a print button or BlockPrinter to a render block, wiring PrintOptionsDialog/usePrintOptions, captureBlockElement, or useDomCapturePrint, or when a print window shows no images or a print fails silently.
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。
Sizing tokens for compact sidebars, nav panels, and menu lists. Use when building or refactoring a sidebar, settings menu, category list, filter bar, or expandable nav tree, or when a sidebar looks too wide, too padded, or wastes space.
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 universal v3 right-click menu (EditableContextMenu / NonEditableContextMenu). Use when adding a right-click menu to a surface, fixing a fake menu with no Copy or Export, a missing Download as Markdown, or a bespoke per-surface menu. NOT for an assigned rollout shard (use context-menu-rollout).
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。
Find and identify the CBasePlayerPawn::CommitSuicide virtual function's vtable slot in the CS2 server binary using IDA Pro MCP. Use this skill when reverse engineering server.dll or libserver.so to locate the self-inflicted-death handler (used by the "kill"/bot_kill console commands and related gameplay code) by RTTI-walking CBasePlayerPawn's primary vtable and reading its known slot index directly, then confirming the body matches CommitSuicide(bool bExplode, bool bForce) semantics. Trigger: CBasePlayerPawn_CommitSuicide
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。
Locate CBasePlayerController::FakeClientFlags in CS2 server.dll / libserver.so via IDA Pro MCP and emit a fresh, minimal-unique signature or offset for the local gamedata entry "CBasePlayerController::FakeClientFlags" (symbol CBasePlayerController_FakeClientFlags). This is a VIRTUAL function - resolve the CBasePlayerController::FakeClientFlags vtable via RTTI and identify the slot, then emit the slot. Verify by xrefs from expected call sites. vtable slots commonly differ between platforms - never assume identical indices. Trigger: CBasePlayerController_FakeClientFlags, CBasePlayerController::FakeClientFlags
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。
Locate BotProfile::Cost in CS2 server.dll / libserver.so via IDA Pro MCP and emit a fresh, minimal-unique signature or offset for the local gamedata entry "BotProfile::Cost" (symbol BotProfile_Cost). This is a VIRTUAL function - resolve the BotProfile::Cost vtable via RTTI and identify the slot, then emit the slot. Verify by xrefs from expected call sites. vtable slots commonly differ between platforms - never assume identical indices. Trigger: BotProfile_Cost, BotProfile::Cost
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。
Locate BotProfile::ReactionTime in CS2 server.dll / libserver.so via IDA Pro MCP and emit a fresh, minimal-unique signature or offset for the local gamedata entry "BotProfile::ReactionTime" (symbol BotProfile_ReactionTime). This is a VIRTUAL function - resolve the BotProfile::ReactionTime vtable via RTTI and identify the slot, then emit the slot. Verify by xrefs from expected call sites. vtable slots commonly differ between platforms - never assume identical indices. Trigger: BotProfile_ReactionTime, BotProfile::ReactionTime
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。