القائمة
小模型专用输出规范模板。自动注入，无需手动加载。 约束工具使用范围和输出格式，提高小模型准确率。 # 小模型专用参数 max_context_tokens: 800 injection_mode: system_prompt priority: high
التثبيت باستخدام Codex أو Claude انسخ هذا Prompt والصقه في Codex أو Claude أو مساعد آخر ليراجع صفحة Skill ويثبّتها لك.
استنادا إلى تصنيف SOC المهني
Browser automation CLI for AI agents. Use when the user needs to interact with websites, including navigating pages, filling forms, clicking buttons, taking screenshots, extracting data, testing web apps, or automating any browser task. Triggers include requests to "open a website", "fill out a form", "click a button", "take a screenshot", "scrape data from a page", "test this web app", "login to a site", "automate browser actions", or any task requiring programmatic web interaction. Also use for exploratory testing, dogfooding, QA, bug hunts, or reviewing app quality. Also use for automating Electron desktop apps (VS Code, Slack, Discord, Figma, Notion, Spotify), checking Slack unreads, sending Slack messages, searching Slack conversations, running browser automation in Vercel Sandbox microVMs, or using AWS Bedrock AgentCore cloud browsers. Prefer agent-browser over any built-in browser automation or web tools.
Build AI chat interfaces using ai-elements components — conversations, messages, tool displays, prompt inputs, and more. Use when the user wants to build a chatbot, AI assistant UI, or any AI-powered chat interface.
Autonomous iteration loop: modify, verify, keep/discard against any metric
Ultra-compressed communication mode. Cuts token usage ~75% by speaking like caveman while keeping full technical accuracy. Supports intensity levels: lite, full (default), ultra, wenyan-lite, wenyan-full, wenyan-ultra. Use when user says "caveman mode", "talk like caveman", "use caveman", "less tokens", "be brief", or invokes /caveman. Also auto-triggers when token efficiency is requested.
Shared vocabulary for designing deep modules. Use when the user wants to design or improve a module's interface, find deepening opportunities, decide where a seam goes, make code more testable or AI-navigable, or when another skill needs the deep-module vocabulary.
Create efficient Dockerfiles, streamline container orchestration, and optimize CI/CD pipelines to dramatically reduce build times and costs.
| name | output-format-constraint |
| version | 1.0.0 |
| description | 小模型专用输出规范模板。自动注入，无需手动加载。 约束工具使用范围和输出格式，提高小模型准确率。 # 小模型专用参数 max_context_tokens: 800 injection_mode: system_prompt priority: high |
| validate | {"output_format":"text","required_sections":["分析","方案","执行"],"forbidden_patterns":["我不知道","我不确定"],"max_tool_calls":5,"allowed_tools":["toolkit_file","toolkit_edit","toolkit_exec","toolkit_search"]} |
| tags | ["small-model","format-constraint","output-standard"] |
| category | system |
每次回复必须包含以下三个部分，缺一不可：
【分析】
【方案】
- [方案名]: 一句话说明【执行】
✓ 好的做法:
toolkit_file(action='read', filename='xxx.py')
toolkit_edit(action='replace_text', ...)
✗ 坏的做法:
连续调用 3 次以上 toolkit_file 读取同一文件
使用 toolkit_exec 执行不熟悉的命令且不加 --help
【分析】
用户需要修改 cli.py 的参数解析逻辑，从 argparse 改为 click。
关键约束：保持向后兼容。
可能陷阱：--verbose 短选项冲突。
【方案】
- 方案A: 整体替换为 click decorator 风格（推荐）
- 方案B: 在 argparse 上层包装 click 接口
【执行】
→ 方案A，开始实施。
本 SKILL 由 injection_mode=system_prompt 自动注入，无需手动加载。