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Feishu Notify

CommunityPopular
wanshuiyin
feishu-notify

Send notifications to Feishu/Lark. Internal utility used by other skills, or manually via /feishu-notify. Use when user says "发飞书", "notify feishu", or other skills need to send status updates.

Overview

Publisherwanshuiyin
RepositoryAuto-claude-code-research-in-sleep
Skill namefeishu-notify
Stars
16.3K
Forks
1.4K
Bundled files
Instructions only
LicenseMIT
Links
  • Markdown instructions

    A SKILL.md file the model loads on demand, so it only costs tokens when a request actually matches.

  • Works with any LLM

    AI skills are plain Markdown, not provider-specific code, so this works with GPT, Claude, Gemini, Grok, or a local model.

  • Self-contained

    Everything the model needs lives in the instructions — no extra files to sync.

  • Open source

    Published by wanshuiyin on GitHub. Read the source before you install it.

Installation

Install the Feishu Notify AI skill in TypingMind to use it with any LLM, or drop it into another agent that reads SKILL.md.

1

Install in TypingMind

TypingMind installs a skill straight from its GitHub folder — it reads SKILL.md, bundles the resource files, and stores the result locally.

  1. Open the app and go to Plugins → Skills.
  2. Choose "Install from GitHub".
  3. Paste the skill folder URL below and confirm.
  4. Enable the skill in any chat where you want it available.
Plugins → Skills → Add skill → From GitHub URL, then paste the folder URL and press Continue.
2

Install in another agent

Any agent that reads the Agent Skills format can use this skill — copy the folder into that agent's skills directory.

Claude Code — .claude/skills
git clone --depth 1 https://github.com/wanshuiyin/Auto-claude-code-research-in-sleep.git /tmp/Auto-claude-code-research-in-sleep
mkdir -p .claude/skills
cp -r /tmp/Auto-claude-code-research-in-sleep/skills/feishu-notify .claude/skills/feishu-notify
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Feishu Notify in any TypingMind chat and the model takes it from there. Its name and description sit in the system prompt, and the moment a request matches, the model loads the full instructions itself — you never invoke it by hand, and it costs no tokens until it is actually used.

The model loads Feishu Notify on its own as soon as a request matches it.

Works with any AI model

AI skills are plain Markdown instructions rather than provider-specific code, so Feishu Notify is not tied to the model it was written for. Install it once in TypingMind and use it with GPT-5, Claude, Gemini, Grok, DeepSeek, Mistral, Llama, or a local model you run yourself — all on your own API keys.

  • Loaded only when it is needed

    The system prompt carries just the name and description. The instructions are fetched on the first matching request, so an idle skill costs nothing.

  • Switch models mid-chat

    Because the skill is instructions rather than code, changing model does not break it — the next model reads the same SKILL.md.

Skill instructions

This is the SKILL.md content the model loads. Read it before installing — a skill is instructions your model will follow.

Feishu/Lark Notification

Send a notification: $ARGUMENTS

Overview

This skill provides Feishu/Lark integration for ARIS. It is designed as an internal utility — other skills call it at key events (experiment done, review scored, checkpoint waiting). It can also be invoked manually.

Zero-impact guarantee: If no feishu.json config exists, this skill does nothing and returns silently. All existing workflows are completely unaffected.

Configuration

The skill reads ~/.claude/feishu.json. If this file does not exist, all Feishu functionality is disabled — skills behave exactly as before.

Config Format

json
{
  "mode": "push",
  "webhook_url": "https://open.feishu.cn/open-apis/bot/v2/hook/YOUR_WEBHOOK_ID",
  "interactive": {
    "bridge_url": "http://localhost:5000",
    "timeout_seconds": 300
  }
}

Modes

Mode"mode" valueWhat it doesRequires
Off"off" or file absentNothing. Pure CLI as-isNothing
Push only"push"Send webhook notifications at key events. Mobile push, no replyFeishu bot webhook URL
Interactive"interactive"Full bidirectional. Approve/reject from Feishu, reply to checkpointsfeishu-claude-code running

Workflow

Step 1: Read Config

bash
cat ~/.claude/feishu.json 2>/dev/null
  • File not found → return silently, do nothing
  • "mode": "off" → return silently, do nothing
  • "mode": "push" → proceed to Step 2 (push)
  • "mode": "interactive" → proceed to Step 3 (interactive)

Step 2: Push Notification (webhook)

Send a rich card to the Feishu webhook:

bash
curl -s -X POST "$WEBHOOK_URL" \
  -H "Content-Type: application/json" \
  -d '{
    "msg_type": "interactive",
    "card": {
      "header": {
        "title": {"tag": "plain_text", "content": "TITLE"},
        "template": "COLOR"
      },
      "elements": [
        {"tag": "markdown", "content": "BODY"}
      ]
    }
  }'

Card templates by event type:

EventTitleColorBody
experiment_doneExperiment CompletegreenResults table, delta vs baseline
review_scoredReview Round N: X/10blue (≥6) / orange (<6)Score, verdict, top 3 weaknesses
checkpointCheckpoint: Waiting for InputyellowQuestion, options, context
errorError: [type]redError message, what failed
pipeline_donePipeline CompletepurpleFinal summary, deliverables
customCustomblueFree-form message from $ARGUMENTS

Return immediately after curl — push mode never waits for a response.

Step 3: Interactive Notification (bidirectional)

Interactive mode uses feishu-claude-code as a bridge:

  1. Send message to the bridge:

    bash
    curl -s -X POST "$BRIDGE_URL/send" \
      -H "Content-Type: application/json" \
      -d '{"type": "EVENT_TYPE", "title": "TITLE", "body": "BODY", "options": ["approve", "reject", "custom"]}'
  2. Wait for reply (with timeout):

    bash
    curl -s "$BRIDGE_URL/poll?timeout=$TIMEOUT_SECONDS"

    Returns: {"reply": "approve"} or {"reply": "reject"} or {"reply": "user typed message"} or {"timeout": true}

  3. On timeout: Fall back to AUTO_PROCEED behavior (proceed with default option).

  4. Return the user's reply to the calling skill so it can act on it.

Step 4: Verify Delivery

  • Push mode: Check curl exit code. If non-zero, log warning but do NOT block the workflow.
  • Interactive mode: If bridge is unreachable, fall back to push mode (if webhook configured) or skip silently.

Helper Function (for other skills)

Other skills should use this pattern to send notifications:

markdown
### Feishu Notification (if configured)

Check if `~/.claude/feishu.json` exists and mode is not "off":
- If **push** mode: send webhook notification with event summary
- If **interactive** mode: send notification and wait for user reply
- If **off** or file absent: skip entirely (no-op)

This check is always guarded. If the config file doesn't exist, the skill skips the notification block entirely — zero overhead, zero side effects.

Event Catalog

Skills send these events at these moments:

SkillEventWhen
/auto-review-loopreview_scoredAfter each round's review score
/auto-review-looppipeline_doneLoop complete (positive or max rounds)
/auto-paper-improvement-loopreview_scoredAfter each round's review score
/auto-paper-improvement-looppipeline_doneAll rounds complete
/run-experimentexperiment_doneScreen session finishes
/idea-discoverycheckpointBetween phases (if interactive)
/idea-discoverypipeline_doneFinal report ready
/monitor-experimentexperiment_doneResults collected
/research-pipelinecheckpointBetween workflow stages
/research-pipelinepipeline_doneFull pipeline complete

Key Rules

  • NEVER block a workflow because Feishu is unreachable. Always fail open.
  • NEVER require Feishu config — all skills must work without it.
  • Config file absent = mode off. No error, no warning, no log.
  • Push mode is fire-and-forget. Send curl, check exit code, move on.
  • Interactive timeout = auto-proceed. Don't hang forever waiting for a reply.
  • Respect AUTO_PROCEED: In interactive mode, if the user doesn't reply within timeout, use the same auto-proceed logic as the calling skill.
  • No secrets in notifications. Never include API keys, tokens, or passwords in Feishu messages.

Frequently asked questions

What does the Feishu Notify AI skill do?

Send notifications to Feishu/Lark. Internal utility used by other skills, or manually via /feishu-notify. Use when user says "发飞书", "notify feishu", or other skills need to send status updates.

Why use Feishu Notify on TypingMind?

Because you install it once and use it with any model. Feishu Notify is plain Markdown rather than provider-specific code, so the same skill runs on GPT-5, Claude, Gemini, Grok, or a local model — and you can switch model mid-chat without it breaking. TypingMind runs on your own API keys, so you pay providers directly instead of a per-seat subscription, and your skills and chats stay in your own storage.

How do I install Feishu Notify in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/wanshuiyin/Auto-claude-code-research-in-sleep/tree/main/skills/feishu-notify. TypingMind reads its SKILL.md and installs it as a skill you can enable per chat.

Which AI models can use Feishu Notify?

Any model you connect in TypingMind. AI skills are plain Markdown instructions rather than provider-specific code, so GPT, Claude, Gemini, Grok, and local models can all load this skill when a request matches it.

How many AI models can I use with Feishu Notify?

As many as you like. As long as a model supports skills, you can use Feishu Notify with it — GPT, Claude, Gemini, Grok, DeepSeek, Mistral, Llama and more — all on TypingMind with your own API keys.

Is the Feishu Notify AI skill free?

Yes. It is published on GitHub by wanshuiyin under the MIT license. You only pay your own AI provider for the tokens you use.

What are AI skills?

An AI skill is a reusable instruction bundle that teaches an AI model how to do one specific task. It follows the open Agent Skills format: a SKILL.md file with a name and description, plus any scripts, templates or reference files the model may need. The model reads the instructions only when your request matches the skill, so an installed skill costs nothing until it is used.

How are AI skills different from plugins or MCP servers?

A plugin or MCP server gives a model new tools to call — code that runs somewhere and returns a result. An AI skill gives the model knowledge and process instead: how to approach a task, which steps to follow, what good output looks like. Skills are plain Markdown, so they need no server, no API key and no runtime, and they work with any model.

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