Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx skills add cafe3310/public-agent-skills --skill use-claude-plugingit clone --depth 1 https://github.com/cafe3310/public-agent-skillsWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/skills/cafe3310/public-agent-skills/use-claude-plugin)<a href="https://agentmods.dev/skills/cafe3310/public-agent-skills/use-claude-plugin"><img src="https://agentmods.dev/badge/skills/cafe3310/public-agent-skills/use-claude-plugin/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/cafe3310/public-agent-skills/use-claude-plugin"><img src="https://agentmods.dev/badge/skills/cafe3310/public-agent-skills/use-claude-plugin.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector pass
What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00024 | $0.02867 |
| Opus 5 | $0.00012 | $0.01434 |
| Sonnet 5 | $0.00005 | $0.00573 |
| Haiku 4.5 | $0.00002 | $0.00287 |
Grade A, and why
plugin-search-and-use scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 11d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
How it starts
The opening of the file, as written. The whole thing — 175 lines — stays where its author put it; the contents beside it link to each section on GitHub.
检索和使用 Claude Plugin
此技能旨在帮助用户快速定位、理解并执行本地目录中的 Claude 插件（Plugins）及其关联的技能（Skills）。
工作流
1. 确认插件库目录
在开始检索前，必须确保用户已经将插件库所在的目录添加到当前上下文中。
- 内置库路径：
skills/use-claude-plugin/knowledge-work-plugins。 - 如果需要使用额外的库，请明确提示用户：“请先使用
add dir命令添加包含 Claude 插件的根目录。” - 确认目录下存在
GEMINI.md或各子目录中包含.claude-plugin/plugin.json。
2. 检索匹配的插件与技能
根据用户提出的具体任务（例如：“帮我做个竞品分析”或“审查这段代码”）：
- 扫描索引：首先查阅插件库根目录下的
GEMINI.md文件或参考下方的“受支持的插件库”列表，寻找与任务描述最匹配的插件名称。 - 深度定位：
- 进入对应的插件目录（如
marketing/或engineering/）。 - 在
skills/目录下寻找相关的子目录及其SKILL.md文件。 - 阅读
SKILL.md的 frontmatter 和描述，确认其功能是否覆盖用户需求。
- 进入对应的插件目录（如
3. 读取并遵循技能指令
一旦定位到正确的 SKILL.md：
- 解析工作流：仔细阅读文档中的“Usage”、“How It Works”或“Workflow”章节。
- 识别工具要求：检查是否需要特定的 MCP 连接器（参考插件根目录下的
CONNECTORS.md或.mcp.json）。 - 遵循格式规范：严格按照
SKILL.md中定义的输出格式（Markdown 结构、表格样式等）进行回复。
4. 执行任务
模拟该插件的身份，根据 SKILL.md 中的专家指令完成用户的具体任务。
注意事项
- 命名空间：在引用或模拟执行时，应意识到插件的命名空间格式（例如
/engineering:code-review）。 - 降级处理：如果相关的 MCP 连接器不可用，应按照插件文档中的“Standalone”模式运行，手动要求用户提供必要的输入。
- 反馈确认：在执行前，可以简要告知用户：“我已找到
[插件名]插件中的[技能名]技能，现在将按照该专家的标准为您处理任务。”
环境兼容性处理 (Gemini CLI)
由于本项目是基于 Claude 设计的，在 Gemini CLI 中调用这些插件时，Agent 需遵循以下适配规则：
| Claude 机制 | Gemini CLI 处理方式 |
|---|---|
Manifest (plugin.json) |
仅参考。获取插件元数据，不执行安装逻辑。 |
Skills (skills/) |
重点阅读。读取 SKILL.md 并将其指令注入到当前对话逻辑。 |
Commands (commands/) |
视作普通指令。按照 Markdown 中的步骤执行任务。 |
Hooks (hooks.json) |
手动模拟。Gemini 不会自动触发。若有必要，Agent 需手动执行钩子定义的命令（如 npm run lint）。 |
LSP (.lsp.json) |
跳过。Gemini CLI 暂不支持通过插件动态加载 LSP。 |
Settings (settings.json) |
角色模拟。根据 agent 字段调整语气和系统指令。 |
受支持的插件库 (来自内置插件库)
Productivity (生产力)
- task-management: 基于 Markdown 的任务跟踪，管理 TASKS.md 文件。
- memory-management: 两层记忆系统（工作记忆与深度存储），学习用户术语和背景。
- start: 初始化任务、记忆系统并启动可视化仪表板。
- update: 分拣陈旧项目，检查记忆差距，并从外部工具同步数据。
Engineering (工程)
- code-review: 审查代码的安全性、性能、正确性和可维护性。
- incident-response: 管理生产事故，包括分拣、通信、缓解和复盘。
- system-design: 设计系统和服务，包括架构图、API 设计 and 数据建模。
- tech-debt: 识别、分类并优先处理技术债。
- testing-strategy: 设计测试策略，涵盖单元、集成和端到端测试。
- documentation: 编写和维护技术文档、README 和运行手册。
- standup: 根据提交记录、PR 和任务自动生成站会更新。
- architecture: 创建或评估架构决策（ADR 格式）。
- deploy-checklist: 部署前验证，检查测试、依赖和回滚计划。
- debug: 结构化调试会话，涵盖复现、隔离、诊断和修复。
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 11d ago First seen · 175 lines · 24 tokens per session scan A bd01b0107a00
plugin-search-and-use is a skill published in the GitHub repository cafe3310/public-agent-skills (253 stars, last pushed 2mo ago), licensed Apache-2.0. It adds 24 tokens to every session and 2,867 once invoked, about $0.0001 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.
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