nano-banana-pro-prompts-recommend-skill
AI skill for OpenClaw & Claude Code — recommend from 10000+ Nano Banana Pro (Gemini) image prompts. Smart search by use case, content remix, sample images.
Sync Feishu docs into local cache for OpenClaw-first reading, reducing API calls and token cost. / 把飞书文档同步为本地缓存供 OpenClaw 优先读取,显著降低飞书 API 请求频率与 token 成本。
Follow the repository instructions for this skill and your agent. Review the files and dependencies before adding it to your workflow.
SkillHub CLI
skillhub install gooderno1/larksync-feishu-local-cacheInspect the source and compatibility requirements, then follow its installation steps.
Give your agent the source link and ask it to inspect instructions and dependencies before explaining the installation steps.
参考:
OPENCLAW_AGENT_GUIDE.md:面向 OpenClaw 代理的自动执行 runbook(首次授权分支、无人值守分支、失败分支)download_only with low-frequency schedule (daily by default).bidirectional and upload_only are supported when explicitly requested.download_only + 每日低频同步(可自定义时间与周期)。bidirectional(双向)和 upload_only,但仅在用户明确要求时启用。download_only)。使用以下脚本作为统一入口(返回 JSON,便于自动化编排):
python integrations/openclaw/skills/larksync_feishu_local_cache/scripts/larksync_skill_helper.py check
python integrations/openclaw/skills/larksync_feishu_local_cache/scripts/larksync_skill_helper.py configure-download --download-value 1 --download-unit days --downl...
These signals come from indexed source analysis and may lag behind changes. Check the current source files.
把飞书文档“变成本地知识库”的 OpenClaw 集成技能。
核心目标:让 OpenClaw 优先读本地同步副本,而不是每次都打飞书 API,从源头降低 token 消耗与限流风险。
An OpenClaw integration that turns Feishu docs into a local knowledge cache.
Core goal: make OpenClaw read local synced files first instead of calling Feishu API on every query.
download_only mode, with optional advanced bidirectional mode.download_only,需要时可升级到双向同步。download_only
integrations/openclaw/skills/larksync_feishu_local_cache/
SKILL.md
OPENCLAW_AGENT_GUIDE.md
README.md
scripts/
larksync_skill_helper.py
OPENCLAW_AGENT_GUIDE.md
http://localhost:8000)。localhost/127.0.0.1/::1。# 1) 环境检查
python integrations/openclaw/skills/larksync_feishu_local_cache/scripts/larksync_skill...
# LarkSync Feishu Local Cache Skill 参考: - `OPENCLAW_AGENT_GUIDE.md`:面向 OpenClaw 代理的自动执行 runbook(首次授权分支、无人值守分支、失败分支) ## English Overview - Purpose: sync Feishu documents to local markdown/files and let OpenClaw read local cache first. - Value: fewer Feishu API calls, lower token consumption, and more stable retrieval latency. - Default mode: `download_only` with low-frequency schedule (daily by default). - Advanced mode: `bidirectional` and `upload_only` are supported when explicitly requested. ### Typical intents (EN) - "Set up a daily 01:00 sync from this Feishu folder to local cache." - "Check my current LarkSync auth and task status first." - "Switch this task to bidirectional sync and explain the risk." ## 价值主张 - 让 OpenClaw 的高频文档问答“走本地、不走云端接口”。 - 把 API 调用从“每次问答触发”变成“低频定时同步触发”。 - 在不改用户飞书使用习惯的前提下,直接获得更稳、更省的文档检索链路。 ## 适用目标 - 目标:减少 OpenClaw 直接调用飞书 API 的频率,优先读取本地 Markdown/附件。 - 默认策略:`download_only` + 每日低频同步(可自定义时间与周期)。 - 进阶策略:支持 `bidirectional`(双向)和 `upload_only`,但仅在用户明确要求时启用。 - Windows 侧建议直接使用 LarkSync 安装包版运行服务,不需要源码构建。 ## 触发意图(示例) - “把飞书生产测试文件夹每天 01:00 同步到本地,给我配置好。” - “先检查 LarkSync 当前授权和同步任务状态。” - “我想把这个目录切成双向同步,先评估风险再改。” ## 默认执行流程 1. 检查本地 LarkSync 服务与授权状态。 2. 配置低频下载策略(默认每天一次)。 3. 创建同步任务(默认 `download_only`)。 4. 按需触发一次立即同步,建立本地缓存基线。 5. 后续回答用户文档问题时,优先读取本地同步目录。 ## 命令入口 使用以下脚本作为统一入口(返回 JSON,便于自动化编排): ```bash python integrations/openclaw/skills/larksync_feishu_local_cache/scripts/larksync_skill_helper.py check python integrations/openclaw/skills/larksync_feishu_local_cache/scripts/larksync_skill_helper.py configure-download --download-value 1 --download-unit days --downl...
# LarkSync Feishu Local Cache Skill
把飞书文档“变成本地知识库”的 OpenClaw 集成技能。
核心目标:让 OpenClaw **优先读本地同步副本**,而不是每次都打飞书 API,从源头降低 token 消耗与限流风险。
## English Overview
An OpenClaw integration that turns Feishu docs into a local knowledge cache.
Core goal: make OpenClaw read local synced files first instead of calling Feishu API on every query.
- Lower cost: shift frequent Q&A reads from Feishu API to local filesystem.
- Better stability: local cache still works when cloud API is throttled.
- Faster retrieval: local-first access for daily queries.
- Safe by default: `download_only` mode, with optional advanced bidirectional mode.
## 为什么值得安装
- 省额度:把高频问答读取从飞书 API 转到本地文件系统。
- 更稳:飞书偶发限流/网络波动时,本地副本仍可读。
- 更快:日常检索直接命中本地目录,不必每次远程拉取。
- 可扩展:默认低风险 `download_only`,需要时可升级到双向同步。
## 一句话效果(Before / After)
- Before:问一个文档问题 -> 调一次飞书 API -> 累积额度消耗。
- After:每天低频同步一次 -> 多次问答都走本地读取 -> API 用量大幅下降。
## 适合谁
- 已经在飞书沉淀大量文档、同时用 OpenClaw 做日常知识检索的人。
- 想把飞书纳入 NAS/本地知识管理体系的人。
- 关注“可持续调用成本”的个人或团队。
## 默认推荐模式
- 同步模式:`download_only`
- 下载频率:每日 1 次(可配置时间)
- 读取策略:OpenClaw 优先本地目录检索与引用
## 目录结构
```text
integrations/openclaw/skills/larksync_feishu_local_cache/
SKILL.md
OPENCLAW_AGENT_GUIDE.md
README.md
scripts/
larksync_skill_helper.py
```
## Agent Runbook
- OpenClaw 代理专用执行说明:[`OPENCLAW_AGENT_GUIDE.md`](./OPENCLAW_AGENT_GUIDE.md)
## 依赖前提
1. Windows 侧已安装并运行 LarkSync(安装包版即可,不需要拉源码构建;后端可访问 `http://localhost:8000`)。
2. 已在 LarkSync 中完成飞书 OAuth 授权。
3. 出于安全考虑,helper 默认只允许连接本机 `localhost/127.0.0.1/::1`。
## 30 秒快速上手
```bash
# 1) 环境检查
python integrations/openclaw/skills/larksync_feishu_local_cache/scripts/larksync_skill...AI skill for OpenClaw & Claude Code — recommend from 10000+ Nano Banana Pro (Gemini) image prompts. Smart search by use case, content remix, sample images.
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