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概要と使いどころ
Use when the user wants Reasonix to build, refine, test, or validate a CLI-Anything harness for a GUI application or source repository. Adapts the CLI-Anything methodology to Reasonix without changing the generated Python harness format.
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 wants Hermes Agent to build, refine, test, or validate a CLI-Anything harness for a GUI application or source repository. Adapts the CLI-Anything methodology to Hermes without changing the generated Python harness format.
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 wants OpenClaw to build, refine, test, or validate a CLI-Anything harness for a GUI application or source repository. Adapts the CLI-Anything methodology to OpenClaw without changing the generated Python harness format.
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 wants Codex to build, refine, test, validate, or list CLI-Anything harnesses for GUI applications or source repositories. Adapts the full CLI-Anything methodology to Codex without changing the generated Python harness format.
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 when designing, generating an MVP blueprint for, auditing, troubleshooting, refactoring, or explaining an agentic harness for any domain. Covers provider-neutral agent architecture for OpenAI, Anthropic, and OpenAI-compatible APIs: agent loops, tool design, record provenance, interactive presentation, user-memory lifecycles, environment-adaptive tools, speculative tool execution, late-bound capabilities, permissions, system prompts, planning, goals, always-on agents and durable runtime, adaptive agent teams, context compaction, memory, skills, MCP/external connectors, public-board communications, hardware agents and board deployment, self-refining recursive harnesses, programmable context, continual refinement, observability, evals, prompt caching, agent-legible environments, feedback loops, and 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。
An Agentforce agent is moving from build or sandbox to live end-user traffic and the team needs a comprehensive readiness gate: coverage testing, Trust Layer config, guardrails, cost telemetry, observability, rate limits, permissions, rollout strategy, rollback plan, performance benchmarks. Triggers: 'we want to ship our Agentforce agent next week', 'pre-prod readiness review for our Service Agent', 'what do we need before turning the agent on for real customers', 'agent went live and is hallucinating, what should we have caught', 'cost monitoring for our internal sales agent', 'rollout strategy from internal pilot to GA'. NOT for the lighter five-block activation sign-off artifact — use agentforce/agent-deployment-checklist. NOT for authoring the guardrails themselves — use agentforce/agentforce-guardrails. NOT for building the test harness — use agentforce/agentforce-eval-harness. NOT for Trust Layer feature setup in isolation — use agentforce/einstein-trust-layer.
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 for harness sdk protocol recipes when optimizing a Coworld player.
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 for reusable harness sdk protocol recipes in software and coding-agent 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 for Crewrift-specific harness sdk protocol recipes when optimizing a player.
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 for harness sdk protocol recipes in scripted Coworld policy optimization.
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 task-local harnesses, eval gates, and reusable skill extraction for Claude dynamic workflow mode and other adaptive agent harnesses.
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 auditing DecisionsAI, Codex, Claude, Cursor, Gemini, Pi, Cline, RTK, workflow pre_chain skills, hooks, projected commands, skill routing, or harness setup for drift, duplication, dead references, slow hooks, bloated context, or stale config.
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 index for DecisionsAI harness setup — ECC, Ponytail, Fallow, RTK, browser/content skills, and IDE thread 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。
Launch Marcus multi-agent experiments with independent CLI agents in tmux panes. Use when the user says "build X with Marcus", "run a Marcus experiment", "spawn N agents with Marcus", "/marcus", or references the Marcus multi-agent framework. This skill handles experiment setup, config generation, and spawning independent agent CLI processes that coordinate via the Marcus MCP server. Each agent runs in its own tmux pane with full autonomy. NOT for ClawTeam — this is specifically for the Marcus MCP-based multi-agent system. NOTE: "Marcus" is also the name of the MCP server that agents use for coordination. The /marcus skill launches experiments that USE the Marcus MCP server — they are complementary, not competing. The MCP server must be running before invoking this skill. The Marcus MCP server is agent-agnostic; this skill supports Anthropic's claude CLI, OpenAI's codex CLI, and Google's gemini CLI as agent harnesses (selected via --harness).
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 Marcus multi-agent experiments with independent CLI agents in tmux panes. Use when the user says "build X with Marcus", "run a Marcus experiment", "spawn N agents with Marcus", "/marcus", or references the Marcus multi-agent framework. This skill handles experiment setup, config generation, and spawning independent agent CLI processes that coordinate via the Marcus MCP server. Each agent runs in its own tmux pane with full autonomy. NOT for ClawTeam — this is specifically for the Marcus MCP-based multi-agent system. NOTE: "Marcus" is also the name of the MCP server that agents use for coordination. The /marcus skill launches experiments that USE the Marcus MCP server — they are complementary, not competing. The MCP server must be running before invoking this skill. The Marcus MCP server is agent-agnostic; this skill supports both Anthropic's claude CLI and OpenAI's codex CLI as agent harnesses (selected via --harness).
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。
Harness Engineering 設計模式 — 基於 Claude Code 原始碼逆向分析的 12 條可遷移原則。Use when: 設計 agent 系統架構、實作 tool orchestration、設計 context 管理策略、建構 agent loop。
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。
Analyzes harness trace logs to surface recurring failure patterns and suggest harness improvements. Scatter-gather across last N runs with a mandatory HITL gate before any change is applied.
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 running an autonomous multi-hour build of a green-field product — orchestrates planner → contract → generator ⇄ evaluator loop with adaptive scaffolding density per model tier. Triggers on /mk:autobuild, "build me a kanban app", "build a retro game maker", "autonomous build", or any green-field product spec. NOT for scoped single-task work (see mk:cook); NOT for initial project scaffolding only (see mk:bootstrap).
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。
Experimental/manual harness canary procedure. It records benchmark manifests and scores but does not provide a fully automated runner.
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。
Auto-detect project context and optimize harness — deactivate unused agents/skills, suggest missing experts, generate project profile
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。
Structured SE task evaluation using 15 benchmark definitions from claude-code-harness research
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。
Autonomously improve a real artifact (code, training recipe, agent harness, data pipeline, prompt) against an objective and an evaluator, using Hypothesis Tree Refinement (HTR) from the Arbor paper. Use this whenever someone wants to iteratively optimize something over many experiments without overfitting — e.g. "get my model's eval score up", "improve this agent/harness", "tune this pipeline", "beat the baseline on this benchmark", "run a search over approaches and keep the best", "do an MLE-bench / Kaggle-style optimization", or any long-horizon "make this artifact better and don't just memorize the dev set" task. Trigger it even when the user doesn't say "Arbor" or "hypothesis tree" but describes repeated experiment-and-evaluate loops, branching exploration of competing ideas, or worries about a dev/test gap. Runs Claude itself as the coordinator with subagent executors in isolated git worktrees; for the standalone `arbor` CLI tool see references/arbor-upstream.md.
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 Phase 6 — TDD coordinator. Decides the scenario recipe and the implementation contract in main context, writes them to a state file, seeds per-worker tasks (scenario, implement, verify-tick, design-ui-tick) into the TaskList, and yields with harness_state continue so the harness invokes each worker as its own tick. No subagent delegation; no nested Skill calls.
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 Phase 9 — Integration and Verification. Runs the full test suite, stamps the binding verdict at .claude/state/last_test_result, optionally runs a cross-engine smoke check, and writes harness_state so the harness auto-continues or yields. No subagent delegation.
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。