webhook-transforms
|
Works with
---
name: webhook-transforms
description: |
license: MIT
---
# Webhook Transforms
## Contract
This skill guarantees:
- External events are transformed into brain pages with proper citations
- Raw payloads are preserved (dead-letter queue if transform fails)
- Entity extraction runs on every transformed event
- Input sanitization: no raw HTML/script passes to brain pages
- Error handling: transform failure logs raw payload, retries once
## Phases
1. **Define transform.** Map event schema to brain page format:
- Input: raw webhook payload (JSON)
- Output: brain page content (markdown) + metadata (slug, type, citations)
- Must sanitize: strip HTML tags, escape script content
2. **Register webhook URL.** Provide the external service with the webhook endpoint.
3. **On event received:**
- Parse payload
- Run transform function
- Write brain page via `gbrain put`
- Extract entities, run enrichment
- Add timeline entries to mentioned entities
- Sync: `gbrain sync`
4. **Error handling:**
- If transform throws: log raw payload to `_dead-letter/{timestamp}.md`
- Surface error type to agent
- Retry once
- Don't lose events
## Example Transforms
### SMS Received
```
Input: {from: "+1555...", body: "Meeting moved to 3pm", timestamp: "..."}
Output: Timeline entry on sender's brain page + task update if action item detected
```
### Meeting Completed
```
Input: {title: "Weekly sync", attendees: [...], transcript: "...", summary: "..."}
Output: Delegate to meeting-ingestion skill
```
### Social Mention
```
Input: {platform: "twitter", author: "@handle", text: "...", url: "..."}
Output: Brain page in media/ + entity extraction + backlinks
```
## Output Format
Event transformed and written to brain. Report: "Webhook: {event_type} from {source}
→ {brain_page_path}"
## Anti-Patterns
- Passing raw HTML/script to brain pages (XSS risk)
- Silently dropping events when transform fails (use dead-letter queue)
- Processing webhooks without entity extraction
- Not sanitizing external input before brain writesMore API Design skills
lark-event
larksuite/cli
Lark/Feishu real-time event listening / subscribing / consuming: stream events as NDJSON via `lark-cli event consume <EventKey>` (covers IM messages/reactions/chat changes, Approval status changes, Task updates, VC meeting started/joined/ended, Minutes generated, Whiteboard updated, etc.). Use for Lark bots, real-time message processing, long-running subscribers, streaming webhook/push handlers. Supports `--max-events` / `--timeout` bounded runs and a stderr ready-marker contract — designed for AI agents running as subprocesses.
lark-contact
larksuite/cli
飞书 / Lark 通讯录:按姓名 / 邮箱解析成 open_id,或按 open_id 反查姓名 / 部门 / 邮箱 / 联系方式 / 个人状态 / 签名,以及按关键词搜索当前用户可见的机器人 / 智能体(agent)。当用户提到一个名字要下一步发消息 / 排日程,或拿到 open_id 想查具体信息时使用。不负责部门树遍历、按部门列员工、组织架构图,这类需求走原生 OpenAPI。
lark-openapi-explorer
larksuite/cli
飞书/Lark 原生 OpenAPI 探索:从官方文档库中挖掘未经 CLI 封装的原生 OpenAPI 接口。当用户的需求无法被现有 lark-* skill 或 lark-cli 已注册命令满足,需要查找并调用原生飞书 OpenAPI 时使用。

