feishu-notify

Send notifications to Feishu/Lark. Internal utility used by other skills, or manually via /feishu-notify. Supports push-only (webhook) and interactive (bidirectional) modes. Use when user says "发飞书", "notify feishu", or other skills need to send status updates.

5,407 stars

Best use case

feishu-notify is best used when you need a repeatable AI agent workflow instead of a one-off prompt.

Send notifications to Feishu/Lark. Internal utility used by other skills, or manually via /feishu-notify. Supports push-only (webhook) and interactive (bidirectional) modes. Use when user says "发飞书", "notify feishu", or other skills need to send status updates.

Teams using feishu-notify should expect a more consistent output, faster repeated execution, less prompt rewriting.

When to use this skill

  • You want a reusable workflow that can be run more than once with consistent structure.

When not to use this skill

  • You only need a quick one-off answer and do not need a reusable workflow.
  • You cannot install or maintain the underlying files, dependencies, or repository context.

Installation

Claude Code / Cursor / Codex

$curl -o ~/.claude/skills/feishu-notify/SKILL.md --create-dirs "https://raw.githubusercontent.com/wanshuiyin/Auto-claude-code-research-in-sleep/main/skills/feishu-notify/SKILL.md"

Manual Installation

  1. Download SKILL.md from GitHub
  2. Place it in .claude/skills/feishu-notify/SKILL.md inside your project
  3. Restart your AI agent — it will auto-discover the skill

How feishu-notify Compares

Feature / Agentfeishu-notifyStandard Approach
Platform SupportNot specifiedLimited / Varies
Context Awareness High Baseline
Installation ComplexityUnknownN/A

Frequently Asked Questions

What does this skill do?

Send notifications to Feishu/Lark. Internal utility used by other skills, or manually via /feishu-notify. Supports push-only (webhook) and interactive (bidirectional) modes. Use when user says "发飞书", "notify feishu", or other skills need to send status updates.

Where can I find the source code?

You can find the source code on GitHub using the link provided at the top of the page.

Related Guides

SKILL.md Source

# 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"` value | What it does | Requires |
|------|----------------|--------------|----------|
| **Off** | `"off"` or file absent | Nothing. Pure CLI as-is | Nothing |
| **Push only** | `"push"` | Send webhook notifications at key events. Mobile push, no reply | Feishu bot webhook URL |
| **Interactive** | `"interactive"` | Full bidirectional. Approve/reject from Feishu, reply to checkpoints | [feishu-claude-code](https://github.com/joewongjc/feishu-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:**

| Event | Title | Color | Body |
|-------|-------|-------|------|
| `experiment_done` | Experiment Complete | `green` | Results table, delta vs baseline |
| `review_scored` | Review Round N: X/10 | `blue` (≥6) / `orange` (<6) | Score, verdict, top 3 weaknesses |
| `checkpoint` | Checkpoint: Waiting for Input | `yellow` | Question, options, context |
| `error` | Error: [type] | `red` | Error message, what failed |
| `pipeline_done` | Pipeline Complete | `purple` | Final summary, deliverables |
| `custom` | Custom | `blue` | Free-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](https://github.com/joewongjc/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:

| Skill | Event | When |
|-------|-------|------|
| `/auto-review-loop` | `review_scored` | After each round's review score |
| `/auto-review-loop` | `pipeline_done` | Loop complete (positive or max rounds) |
| `/auto-paper-improvement-loop` | `review_scored` | After each round's review score |
| `/auto-paper-improvement-loop` | `pipeline_done` | All rounds complete |
| `/run-experiment` | `experiment_done` | Screen session finishes |
| `/idea-discovery` | `checkpoint` | Between phases (if interactive) |
| `/idea-discovery` | `pipeline_done` | Final report ready |
| `/monitor-experiment` | `experiment_done` | Results collected |
| `/research-pipeline` | `checkpoint` | Between workflow stages |
| `/research-pipeline` | `pipeline_done` | Full 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.

Related Skills

vast-gpu

5407
from wanshuiyin/Auto-claude-code-research-in-sleep

Rent, manage, and destroy GPU instances on vast.ai. Use when user says "rent gpu", "vast.ai", "rent a server", "cloud gpu", or needs on-demand GPU without owning hardware.

system-profile

5407
from wanshuiyin/Auto-claude-code-research-in-sleep

Profile a target (script, process, GPU, memory, interconnect) using external tools and code instrumentation. Produces structured performance reports with actionable recommendations. Use when user says "profile", "benchmark", "bottleneck", or wants performance analysis.

training-check

5407
from wanshuiyin/Auto-claude-code-research-in-sleep

Periodically check WandB metrics during training to catch problems early (NaN, loss divergence, idle GPUs). Avoids wasting GPU hours on broken runs. Use when training is running and you want automated health checks.

serverless-modal

5407
from wanshuiyin/Auto-claude-code-research-in-sleep

Run GPU workloads on Modal — training, fine-tuning, inference, batch processing. Zero-config serverless: no SSH, no Docker, auto scale-to-zero. Use when user says "modal run", "modal training", "modal inference", "deploy to modal", "need a GPU", "run on modal", "serverless GPU", or needs remote GPU compute.

semantic-scholar

5407
from wanshuiyin/Auto-claude-code-research-in-sleep

Search published venue papers (IEEE, ACM, Springer, etc.) via Semantic Scholar API. Complements /arxiv (preprints) with citation counts, venue metadata, and TLDR. Use when user says "search semantic scholar", "find IEEE papers", "find journal papers", "venue papers", "citation search", or wants published literature beyond arXiv preprints.

run-experiment

5407
from wanshuiyin/Auto-claude-code-research-in-sleep

Deploy and run ML experiments on local, remote, Vast.ai, or Modal serverless GPU. Use when user says "run experiment", "deploy to server", "跑实验", or needs to launch training jobs.

result-to-claim

5407
from wanshuiyin/Auto-claude-code-research-in-sleep

Use when experiments complete to judge what claims the results support, what they don't, and what evidence is still missing. Codex MCP evaluates results against intended claims and routes to next action (pivot, supplement, or confirm). Use after experiments finish — before writing the paper or running ablations.

research-review

5407
from wanshuiyin/Auto-claude-code-research-in-sleep

Get a deep critical review of research from GPT via Codex MCP. Use when user says "review my research", "help me review", "get external review", or wants critical feedback on research ideas, papers, or experimental results.

research-refine

5407
from wanshuiyin/Auto-claude-code-research-in-sleep

Turn a vague research direction into a problem-anchored, elegant, frontier-aware, implementation-oriented method plan via iterative GPT-5.4 review. Use when the user says "refine my approach", "帮我细化方案", "decompose this problem", "打磨idea", "refine research plan", "细化研究方案", or wants a concrete research method that stays simple, focused, and top-venue ready instead of a vague or overbuilt idea.

research-refine-pipeline

5407
from wanshuiyin/Auto-claude-code-research-in-sleep

Run an end-to-end workflow that chains `research-refine` and `experiment-plan`. Use when the user wants a one-shot pipeline from vague research direction to focused final proposal plus detailed experiment roadmap, or asks to "串起来", build a pipeline, do it end-to-end, or generate both the method and experiment plan together.

research-pipeline

5407
from wanshuiyin/Auto-claude-code-research-in-sleep

Full research pipeline: Workflow 1 (idea discovery) → implementation → Workflow 2 (auto review loop). Goes from a broad research direction all the way to a submission-ready paper. Use when user says "全流程", "full pipeline", "从找idea到投稿", "end-to-end research", or wants the complete autonomous research lifecycle.

research-lit

5407
from wanshuiyin/Auto-claude-code-research-in-sleep

Search and analyze research papers, find related work, summarize key ideas. Use when user says "find papers", "related work", "literature review", "what does this paper say", or needs to understand academic papers.