Hope Agent is a cross-device personal AI assistant that remembers context, uses tools, and continues working toward goals through dynamically organized workflows. Individuals use it from desktop, web, server, or messaging environments to manage projects, knowledge, designs, and long-running tasks. The catalogue add-ons extend its agent workflows and capabilities.
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 shiwenwen/hope-agent --skill feishugit clone --depth 1 https://github.com/shiwenwen/hope-agentWrote 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/shiwenwen/hope-agent/feishu)<a href="https://agentmods.dev/skills/shiwenwen/hope-agent/feishu"><img src="https://agentmods.dev/badge/skills/shiwenwen/hope-agent/feishu/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/shiwenwen/hope-agent/feishu"><img src="https://agentmods.dev/badge/skills/shiwenwen/hope-agent/feishu.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 | $0.00189 | $0.02222 |
| Opus 5.5 | $0.00076 | $0.00889 |
| Sonnet 5.5 | $0.00038 | $0.00444 |
| Haiku 4.5 | $0.00019 | $0.00222 |
Grade A, and why
feishu 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 1mo 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 — 161 lines — stays where its author put it; the contents beside it link to each section on GitHub.
飞书 (Lark) 工作流套件
35 个 feishu_* tool 覆盖飞书除 IM 之外的核心业务面：docx / bitable / drive / wiki / approval / calendar / contact / hire。所有 tool 共享同一个账号路由——account 参数仅在配了 ≥2 个飞书账号时才必须，否则自动选唯一一个。
典型工作流剧本
1. OKR 周报：bitable → docx → drive
1. feishu_bitable_list_records({app_token, table_id, view_id?})
→ 拿到本周的 OKR 进度数据
2. feishu_docx_create({title: "OKR Weekly W#"})
→ 拿到 document_id
3. feishu_docx_append_block({document_id, parent_block_id: document_id,
block: {block_type: 2, text: {style: {}, elements: [...]}}})
→ 写多段
4. feishu_drive_upload_media({path: "/tmp/screenshot.png",
folder_token: "...", mime: "image/png"})
→ 把截图传上去（≤20MB，本地路径必须绝对）
2. 排会议：calendar → attendees
1. feishu_calendar_list() → 选目标 calendar_id
2. feishu_calendar_create_event({calendar_id, event: {
summary: "OKR review", start_time: {timestamp: "1700000000",
timezone: "Asia/Shanghai"}, end_time: {...}}})
→ 拿到 event_id
3. feishu_calendar_attendees_create({calendar_id, event_id, attendees: [
{type: "user", user_id: "ou_xxx"},
{type: "chat", chat_id: "oc_xxx"}]})
3. 查同事：contact
1. feishu_contact_get_user({user_id: "ou_xxx"}) // 或先 search 找 ID
→ 名字 / email / 部门 / 上级
2. feishu_contact_search_users_by_department({department_id: "..."})
→ 整个团队
⚠️ contact 系列返回员工个人信息（手机号 / 邮箱 / 部门），不要把原始 JSON 直接 echo 回 IM 群聊——总结关键字段即可。
4. 审批：approval
1. feishu_approval_create_instance({approval_code, user_id, form: "[...]"})
→ ⚠️ HIGH RISK：在调之前一定问用户「我准备发起 X 审批，form 字段是 Y/Z，确认吗？」
2. feishu_approval_get_instance({instance_code}) → 看 status / timeline
3. 撤销也是 HIGH：feishu_approval_cancel_instance({approval_code, instance_code, user_id})
5. wiki 链接：先解析再读
用户给一个形如 https://xxx.feishu.cn/wiki/wikcnXxx 的链接时：
1. feishu_wiki_get_node({token: "wikcnXxx"})
→ 拿到 obj_token / obj_type
2. obj_type == "docx" → feishu_docx_get_blocks({document_id: obj_token})
obj_type == "bitable" → feishu_bitable_list_records({app_token: obj_token, table_id: ...})
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.
- 1mo ago First seen · 161 lines · 189 tokens per session scan A eaf435c12014
feishu is a skill published in the GitHub repository shiwenwen/hope-agent (1,859 stars, last pushed today), licensed MIT. It adds 189 tokens to every session and 2,222 once invoked, about $0.0008 per session on Opus 5.5. 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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