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Use when the user wants to set up, check, repair, or report the SuperCtx state for this repository. Consolidated command for global context convergence.

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 contextual replies to comments, mentions, and DMs on social posts. Classifies engagement as lead signal, customer question, partnership opportunity, or troll/spam. Uses brand voice from agency.config.json.

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。

Generate structured call scripts by persona and lead 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。

Generates detailed design briefs for social media creative assets. Covers image specs per platform, copy overlay text, color palette, and format specs for stories, carousels, singles, and reel covers.

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。

Draft professional emails for various contexts including business, technical, and customer communication. Use when the user needs help writing emails or composing professional messages.

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。

Architects the encryption, codec/transport, and premium-feature layer of a group video-calling product, on top of an already-chosen SFU topology. Covers E2EE patterns (Zoom leader-fan-out, Signal pairwise-fan-out, MLS/TreeKEM as in Discord's DAVE, Telegram's ledger consensus), the SFrame (RFC 9605) + WebRTC Insertable Streams mechanism letting an SFU relay encrypted frames it can't read, codec/transport choice (AV1/VP9 SVC vs. simulcast, Opus, congestion control, Media-over-QUIC, WHIP/WHEP), and which "premium" features (virtual backgrounds, live captions, recording, breakout rooms, spatial audio) survive E2EE vs. structurally can't. Use when adding E2EE to an SFU-based call, choosing a 2026 codec/SVC strategy, or deciding which features to disable under E2EE mode. NOT for call topology/platform choice (see webrtc-adhoc-video-chat, which this composes with). NOT for one-way broadcast (see managed-video-streaming-pipeline). NOT for the DM/group-chat text backend (see realtime-messaging-backend-architecture).

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 temporal event detection, spatio-temporal clustering (ST-DBSCAN), and photo context understanding. Use for detecting photo events, clustering by time/location, shareability prediction, place recognition, event significance scoring, and life event detection. Activate on 'event detection', 'temporal clustering', 'ST-DBSCAN', 'spatio-temporal', 'shareability prediction', 'place recognition', 'life events', 'photo events', 'temporal diversity'. NOT for individual photo aesthetic quality (use photo-composition-critic), color palette analysis (use color-theory-palette-harmony-expert), face recognition implementation (use photo-content-recognition-curation-expert), or basic EXIF timestamp extraction.

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。

Advanced CV for infrastructure inspection including forest fire detection, wildfire precondition assessment, roof inspection, hail damage analysis, thermal imaging, and 3D Gaussian Splatting reconstruction. Expert in multi-modal detection, insurance risk modeling, and reinsurance data pipelines. Activate on "fire detection", "wildfire risk", "roof inspection", "hail damage", "thermal analysis", "Gaussian Splatting", "3DGS", "insurance inspection", "defensible space", "property assessment", "catastrophe modeling", "NDVI", "fuel load". NOT for general drone flight control, SLAM, path planning, or sensor fusion (use drone-cv-expert), GPU shader development (use metal-shader-expert), or generic object detection without inspection context (use clip-aware-embeddings).

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。

Generate, fill, and assemble PDF documents at scale. Handles legal forms, contracts, invoices, certificates. Supports form filling (pdf-lib), template rendering (Puppeteer, LaTeX), digital signatures (DocuSign), and document assembly. Use for legal tech, HR automation, invoice generation. Activate on "PDF generation", "form filling", "document automation", "digital signatures". NOT for simple PDF viewing, basic file conversion, or OCR text extraction.

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。

Master of text-based visual communication using ASCII art, Unicode box-drawing, and structured diagram notation. Creates clear, maintainable diagrams for systems, processes, hierarchies, relationships, and psychological structures. Proactively generates diagrams to enhance understanding. Activate on visualization needs, system architecture, process flows, psychological mapping, or when complex concepts would benefit from visual representation. NOT for photo editing, vector graphics, or GUI-based design tools.

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 drone systems, computer vision, and autonomous navigation. Specializes in flight control, SLAM, object detection, sensor fusion, and path planning. Activate on "drone", "UAV", "SLAM", "visual odometry", "PID control", "MAVLink", "Pixhawk", "path planning", "A*", "RRT", "EKF", "sensor fusion", "optical flow", "ByteTrack". NOT for domain-specific inspection tasks like fire detection, roof damage assessment, or thermal analysis (use drone-inspection-specialist), GPU shader optimization (use metal-shader-expert), or general image classification without drone context (use clip-aware-embeddings).

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。

Operations, debugging, and optimization for DAG workflows. Performs root cause analysis on failures, profiles execution performance, aggregates results from parallel branches, bridges context between nodes, and learns patterns from execution history. Activate on "DAG failed", "why did it fail", "root cause", "performance profile", "aggregate results", "merge branches", "execution patterns", "optimize DAG". NOT for planning DAGs (use dag-planner), executing DAGs (use dag-runtime), or validating outputs (use dag-quality).

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。

Detects and fixes color contrast violations using WCAG 2.1 guidelines and perceptual analysis. Expert in contrast ratio calculation, color blindness simulation, and providing accessible alternatives. Activate on "check contrast", "color accessibility", "WCAG audit", "readability check", "contrast ratio", "hard to read", "can't see text". NOT for general color theory (use color-theory-palette-harmony-expert), brand color selection (use web-design-expert), or non-visual accessibility (use ux-friction-analyzer).

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。

Identify and counteract cognitive biases in medical decision-making through systematic error analysis and contextual algorithm application. For diagnostic reasoning, treatment decisions, and clinical judgment improvement. NOT for basic medical knowledge, technical procedures, or non-clinical healthcare domains.

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 comprehensive, context-aware code review checklists tailored to the specific codebase, programming language, and team standards. Analyzes PR diffs and suggests what reviewers should focus on.

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 an executable BDI agent cycle with events, context-guarded plans, intention stacks, selection functions, and belief revision. Use when designing or debugging AgentSpeak-style runtimes or concrete BDI program semantics. NOT for high-level BDI adoption, organizational modeling, norms, or hypertree team planning.

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。

Produces a narrow-interval quality signal for a WinDAGs skill that a third party can verify without inspecting model weights or method internals. The mechanism is attribution-kNN over a tamper-evident outcome log (task→skills→accept/reject store), combined with a conformal-prediction calibration certificate that provides a formal coverage guarantee. Thompson/Beta sampling is explicitly rejected as a category error: it produces a selection signal for stationary i.i.d. rewards, not an attestation signal for context-dependent LLM output quality. The resulting bundle — outcome-log Merkle root + conformal threshold + optional TEE guardrail signature — constitutes a "narrow-interval trust" credential: verifiable, bounded, and internals-opaque.

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 AgentSpeak-style BDI plan libraries with explicit event, context, failure, and authority boundaries. NOT for treating BDI plans as safety approval or guaranteed execution.

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。

Designs digital experiences for ADHD brains using neuroscience research and UX principles. Expert in reducing cognitive load, time blindness solutions, dopamine-driven engagement, and compassionate design patterns. Activate on 'ADHD design', 'cognitive load', 'accessibility', 'neurodivergent UX', 'time blindness', 'dopamine-driven', 'executive function'. NOT for general accessibility (WCAG only), neurotypical UX design, or simple UI styling without ADHD 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。

Fundamental patterns for effective agentic behavior. Teaches decomposition, tool orchestration, error recovery, context management, quality self-assessment, and knowing when to stop. Model-agnostic principles that make any agent more effective regardless of domain. Activate on: "how should I structure this agent", "agentic workflow", "agent patterns", "multi-step task", "tool orchestration", "/agentic-patterns", "decompose this", "agent best practices", "chain of actions", "when should the agent stop", "agent loop design". NOT for: creating agent infrastructure (use agent-creator), building DAGs (use jury_rig-architect), specific tool implementation.

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 low-friction UX, interaction patterns, and comeback loops for AI coding assistant apps, agent consoles, background coding agents, and Port Daddy swarm/operator surfaces. Use when creating flows like prompt-to-diff, context attach, plan/apply/review, checkpoint rollback, background-agent dashboards, visual proof, or multi-agent invocation. NOT for generic landing pages, static dashboards, or implementation-only changes without product flow.

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。

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。

Data structures and serialization formats for agent-to-agent communication. Covers message envelopes, structured output schemas, capability declarations, task handoff payloads, error/retry signaling, and context windows as data structures. Compares the version-pinned A2A, MCP, and JSON-RPC role boundaries covered by this bundle; OpenAI and LangChain-specific APIs require their own current sources. Teaches when to use rigid schemas versus free-form content with validation, typed versus untyped boundaries, and streaming versus batch. Activate on: "agent message format", "agent communication schema", "agent-to-agent protocol", "A2A protocol", "MCP message format", "structured output for agents", "agent interop", "interchange format", "agent serialization", "task handoff format", "capability declaration". NOT for: what agents say to each other (use agent-conversation-protocols), orchestration topology (use multi-agent-coordination), building agent infrastructure (use agentic-infrastructure-2026).

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。