菜单
Review upstream changes to the local my-opencode reviewer swarm before selectively applying them. Use whenever the user asks to pull, sync, inspect, compare, or adopt reviewer or swarm changes from ~/Documents/yo/my-opencode. Never use it to install the upstream configuration wholesale.
用 Codex 或 Claude 帮你安装 复制这段 Prompt，粘贴到 Codex、Claude 或其他助手里，让它检查 Skill 页面并帮你完成安装。
基于 SOC 职业分类
| name | review-swarm-upstream |
| description | Review upstream changes to the local my-opencode reviewer swarm before selectively applying them. Use whenever the user asks to pull, sync, inspect, compare, or adopt reviewer or swarm changes from ~/Documents/yo/my-opencode. Never use it to install the upstream configuration wholesale. |
The upstream repository is a reference for review agents only. Local OpenCode configuration, authentication, plugins, MCP servers, commands, permissions, and primary agents remain authoritative.
Review only these upstream files:
agents/reviewer.md for orchestration ideasagents/reviewer-quick.mdagents/reviewer-reasoning.mdagents/reviewer-arch.mdagents/reviewer-e2e.mdMap specialist agents to local files with the same names. Do not import upstream reviewer.md as a local primary agent; local code-reviewer remains the orchestrator.
Never run bun run setup, bun run cleanup, or any upstream install script. Never copy upstream opencode.json, package.json, .opencode/plugins/, .opencode/tools/, templates, or AGENTS.example.md.
~/.config/opencode/opencode.json, agents/code-reviewer.md, and local specialist agents.~/Documents/yo/my-opencode with git status --short. Stop if it is dirty.git pull --ff-only in the upstream repository.Adopt, Reject, and Needs decision, citing both paths and lines.Default agents and reviewer specialists use only openai/*, opencode/*, or opencode-go/* models. Do not import an upstream model outside those providers.
The local task tool provides cross-model recovery. Use the configured model by default, model for a preferred first attempt, or models for an exact ordered chain with no implicit fallbacks.
Record accepted upstream changes in CODE/LLMs/opencode/setup.md and update the relevant Obsidian agent or skill note. Never record credentials or tokens.
## Upstream
<commit range or no new commits>
## Adopt
- <local path:line> <- <upstream path:line>: <reason>
## Reject
- <upstream path:line>: <reason>
## Needs Decision
- <difference and consequence>
Quick-reference card for all caveman modes, skills, and commands. One-shot display, not a persistent mode. Trigger: /caveman-help, "caveman help", "what caveman commands", "how do I use caveman".
Helps users discover and install agent skills when they ask questions like "how do I do X", "find a skill for X", "is there a skill that can...", or express interest in extending capabilities. This skill should be used when the user is looking for functionality that might exist as an installable skill.
Review upstream changes to the local my-opencode reviewer swarm before selectively applying them. Use whenever the user asks to pull, sync, inspect, compare, or adopt reviewer or swarm changes from ~/Documents/yo/my-opencode. Never use it to install the upstream configuration wholesale.
Quick-reference card for all ponytail modes, skills, and commands. One-shot display, not a persistent mode. Trigger: /ponytail-help, "ponytail help", "what ponytail commands", "how do I use ponytail".
Forces the laziest solution that actually works, simplest, shortest, most minimal. Channels a senior dev who has seen everything: question whether the task needs to exist at all (YAGNI), reach for the standard library before custom code, native platform features before dependencies, one line before fifty. Supports intensity levels: lite, full (default), ultra. Use whenever the user says "ponytail", "be lazy", "lazy mode", "simplest solution", "minimal solution", "yagni", "do less", or "shortest path", and whenever they complain about over-engineering, bloat, boilerplate, or unnecessary dependencies.
Use whenever the task involves writing, drafting, revising, or reviewing a system prompt for an AI agent — autonomous or semi-autonomous LLM systems that use tools in a loop, including operator agents, research/sub-agents, tool-using assistants, MCP servers, multi-agent orchestrators, and coding agents. Trigger even when the user says "instructions", "system message", "agent persona", or "rules for the model", not just the word "prompt". Do NOT use for one-shot prompts (classification, single generation, single Q&A) — those need lighter prompt techniques, not the full agent skeleton.