37 件 ・ 関連度順
概要と使いどころ
Design a learning task where mixed-age students work together with mutual benefit for all age groups. Use when planning cross-age tutoring, vertical grouping, or multi-year group activities.
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 a learning task where mixed-age students work together with mutual benefit for all age groups. Use when planning cross-age tutoring, vertical grouping, or multi-year group activities.
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 the user asks to "share memory between agents", "KV cache compaction for multi-agent", "orchestrator worker context", "latent briefing", "reduce worker tokens", "cross-agent memory without summarization", or discusses Attention Matching compaction, recursive language models with workers, or token explosion in hierarchical agents.
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 agent work needs file-backed context: durable scratchpads, tool-output offloading, just-in-time discovery, cross-agent handoff files, filesystem memory, or cleanup policies for context stored outside the prompt.
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。
Standard collaboration patterns for all squad agents — worktree awareness, decisions, cross-agent communication
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 one AI agent's raw history for a specific topic, ingest only matching sessions, and return a synthesized answer. Use for targeted cross-agent recall; use wiki-history-ingest for bulk archival ingestion.
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。
Ingest OpenClaw session/history data into Obsidian as distilled knowledge. Use for importing or mining ~/.openclaw sessions, memory files, or logs; use wiki-agent for targeted topic-only cross-agent recall.
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。
Ingest Hermes agent history into Obsidian as distilled knowledge. Use for importing or mining ~/.hermes sessions, memories, or logs; use wiki-agent for targeted topic-only cross-agent recall.
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。
Complete AI coding workflow system. Orchestration patterns, 18 hook events, 8 agents, cross-agent support, reference guides, and searchable learnings. Works with Claude Code, Cursor, and 32+ agents.
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。
Standard collaboration patterns for all squad agents — worktree awareness, decisions, cross-agent communication
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 Trellis channel for live multi-agent collaboration, spawned workers, cross-agent review, progress inspection, forum channels, and channel log debugging.
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。
Cross-agent collaboration protocols, workflow handoff patterns, and commit message formats for TDD/Mikado/refactoring workflows
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。
Plan, execute, document, and retest authorized security assessments of AI agents and multi-agent workflows using safe adversarial cases, synthetic identities, canaries, and evidence-based findings. Use when defining red-team rules of engagement, assessing prompt injection or excessive agency, testing tool and identity boundaries, evaluating memory or cross-agent attacks, scoring a campaign, or verifying remediation in an approved environment.
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。
Threat-model and harden AI agents, RAG systems, assistants, and tool-using workflows against direct, indirect, stored, cross-agent, and multimodal prompt injection. Use when reviewing an agent architecture, isolating untrusted content, constraining tools and egress, protecting secrets, adding injection-focused tests, investigating a suspected injection incident, or documenting residual prompt-injection risk.
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。
Cross-agent self-inspection of your AI-agent stack. Audits skills, MCP servers, hooks, plugins, commands, credentials, and memory files across Claude Code, Codex, OpenClaw, and NanoClaw. Produces a structured inventory and narrative briefing with cross-ecosystem risk analysis. Use when the user asks to audit their own setup, check what they have installed, review their agent stack security posture, or understand cross-tool interactions. Use when a user has accumulated skills/plugins/MCP servers over time and wants visibility into their attack surface. Use after installing new skills or plugins. Do NOT use for vetting external code before install (that is repo-forensics). Do NOT use for incident response during active attacks. Do NOT use for fixing or patching vulnerabilities (forensify is read-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。
Orchestrating ecosystem self-evolution: lifecycle-phase detection, agent relevance, cross-agent knowledge synthesis, evolution proposals. Use when auditing skill-ecosystem health or fitness.
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。
Curating cross-agent knowledge and institutional memory: extracts patterns from agent journals into METAPATTERNS.md, detects knowledge decay, propagates best practices. Use for memory curation.
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。
CASS Memory System - procedural memory for AI coding agents. Three-layer cognitive architecture with confidence decay, anti-pattern learning, cross-agent knowledge transfer, trauma guard safety system. Bun/TypeScript CLI.
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 knowledge synthesizer specializing in extracting insights from multi-agent interactions, identifying patterns, and building collective intelligence. Masters cross-agent learning, best practice extraction, and continuous system improvement through knowledge 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。
Use HarnessKit to inventory, audit, enable, disable, and deploy skills, MCP servers, plugins, hooks, CLIs, configs, memory, and rules across multiple coding agents.
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 Chops to discover, search, edit, and organize local or remote agent skills across Claude Code, Cursor, Codex, Windsurf, Amp, Copilot, and Aider.
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 creating, auditing, or maintaining AGENTS.md files and Codex CLI configuration for any project—including initializing AGENTS.md for cross-agent compatibility (Codex, Cursor, Copilot, Devin, Jules, Amp, Gemini CLI), generating config.toml or .rules files, scaffolding .agents/skills/, converting CLAUDE.md to AGENTS.md, or auditing existing agent configs for bloat and staleness. Complementary to codex-orchestrator (which executes subagents; this skill creates the config files they consume).
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。
Deep code review after beads have landed — random exploration + cross-agent review, alternating. Use every 30–60 min during active implementation, or after any epic lands.
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。