pywayne-lark-bot

pywayne-lark-bot is a skill for Claude Code, Codex from wangyendt/wayne-skills. It costs 191 tokens per session (11,437 once invoked), scanned A, original, MIT.

A Python wrapper for the Feishu/Lark messaging platform, a workplace chat service. It lets programs send and manage messages, files, rich text, and interactive cards, and manage chats and users.

In plain words
What is it for?
Use it to send notifications, documents, images, audio, or formatted updates to chats; manage messages and group chats; upload and download files; and build interactive cards.
Why use it?
It removes the need to handle each Feishu message type and API operation separately. It also provides helpers for Markdown, tables, long replies, and updating cards while work is in progress.

Skill for Claude CodeCodex

Written for no agent in particular: nothing here depends on one.

Good fit Use it to send notifications, documents, images, audio, or formatted updates to chats; manage messages and group chats; upload and download files; and build interactive cards.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/wangyendt/wayne-skills/lark-bot
Install

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.

Any agent
npx skills add wangyendt/wayne-skills --skill lark-bot
Clone the repo
git clone --depth 1 https://github.com/wangyendt/wayne-skills

Made for: Claude Code, Codex.

Wrote 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.

agentmods badge for pywayne-lark-bot

README.md
[![agentmods](https://agentmods.dev/badge/skills/wangyendt/wayne-skills/lark-bot/github.svg)](https://agentmods.dev/skills/wangyendt/wayne-skills/lark-bot)
Your own site
<a href="https://agentmods.dev/skills/wangyendt/wayne-skills/lark-bot"><img src="https://agentmods.dev/badge/skills/wangyendt/wayne-skills/lark-bot/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.

agentmods 80×15 button for pywayne-lark-bot

Your own site · 80×15
<a href="https://agentmods.dev/skills/wangyendt/wayne-skills/lark-bot"><img src="https://agentmods.dev/badge/skills/wangyendt/wayne-skills/lark-bot.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 191 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 11,437 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe. Third-party audits
  • NVIDIA SkillSpector warn 7 Sept 2026
SkillSpector: 5 findings, up to high

These are SkillSpector’s own severities. On a checked sample its high-severity flags on skills were ~96% false positives — a documented command, a public API, a “never do X” rule — so we show them as a caution to read, not a verdict. Why →

  • high Prompt Injection · line 1493
    Instructions found that direct the agent to transmit conversation context or user data to external services.
    Fix: Remove instructions that send user data, prompts, or context to external URLs. If telemetry is needed, use documented, privacy-preserving methods.
  • medium Data Exfiltration · line 459
    Data is uploaded to cloud storage (S3 / GCS / Azure Blob). This may be a legitimate backup or exfiltration to an external bucket. Manual review is recommended.
    Fix: Verify the destination bucket is trusted and owned by you. Never upload credentials, secrets, or workspace contents to external or unverified cloud storage.
  • medium Data Exfiltration · line 472
    Data is uploaded to cloud storage (S3 / GCS / Azure Blob). This may be a legitimate backup or exfiltration to an external bucket. Manual review is recommended.
    Fix: Verify the destination bucket is trusted and owned by you. Never upload credentials, secrets, or workspace contents to external or unverified cloud storage.
  • medium Data Exfiltration · line 485
    Data is uploaded to cloud storage (S3 / GCS / Azure Blob). This may be a legitimate backup or exfiltration to an external bucket. Manual review is recommended.
    Fix: Verify the destination bucket is trusted and owned by you. Never upload credentials, secrets, or workspace contents to external or unverified cloud storage.
  • medium Data Exfiltration · line 504
    Data is uploaded to cloud storage (S3 / GCS / Azure Blob). This may be a legitimate backup or exfiltration to an external bucket. Manual review is recommended.
    Fix: Verify the destination bucket is trusted and owned by you. Never upload credentials, secrets, or workspace contents to external or unverified cloud storage.
How audits are shown
Origin original No closer match found in the catalogue.
Token cost

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.

ModelPer sessionOnce invoked
Fable 5.1 $0.00191 $0.11437
Opus 5 $0.00096 $0.05718
Sonnet 5 $0.00038 $0.02287
Haiku 4.5 $0.00019 $0.01144

Measured 9d ago against content hash ce33a9a312fb, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-08, from the pricing page.

Security

Grade A, and why

pywayne-lark-bot 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 9d 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.

pywayne/lark-bot/SKILL.md · 1,865 lines

How it starts

The opening of the file, as written. The whole thing — 1,865 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Overview

LarkBot is a comprehensive Feishu (Lark) application bot wrapper that provides complete bidirectional interaction capabilities. It's designed for scenarios requiring full message lifecycle management, chat administration, and complex card-based interactions.

Key Capabilities:

  • Send all message types (text, image, audio, video, file, rich_text, card)
  • Reply, forward, recall, update messages
  • Edit sent text/rich_text/card messages with semantic helper methods
  • Build and update in-place streaming cards for long-running or LLM-style responses
  • Reactions, pins, read receipts, urgent notifications
  • Chat management (create, delete, update, members, admins, announcements)
  • File upload/download with message resource handling
  • User and group information queries
  • Batch messaging to users/departments
  • Recommended: send_markdown_message_to_chat with auto-chunking and table fallback

Companion Classes:

  • TextContent: Quick text formatting (@mentions, bold, italic, links)
  • PostContent: Rich text builder with Markdown table handling
  • CardContentV2: Schema 2.0 card builder
  • LarkBotListener: Event listener for incoming messages (separate skill)

Installation

pip install pywayne lark-oapi

Quick Start

from pywayne.lark_bot import LarkBot

# Initialize bot
bot = LarkBot(
    app_id="cli_xxxxxxxxxxxx",
    app_secret="your_app_secret"
)

# Send text to user
bot.send_text_to_user("ou_xxxxxxxx", "Hello from LarkBot!")

# Send text to chat group
bot.send_text_to_chat("oc_xxxxxxxx", "Hello, everyone!")

LarkBot Class

Constructor

bot = LarkBot(
    app_id: str,        # Feishu application ID
    app_secret: str     # Feishu application secret
)

Instance Attributes:

  • client: Underlying lark.Client for advanced usage
  • All methods return Dict with API response data

Helper Classes

TextContent - Quick Text Formatting

Read the full file on GitHub · 1,865 lines

Changes

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.

  1. 9d ago First seen · 1,865 lines · 191 tokens per session scan A ce33a9a312fb

Subscribe to this mod's changes

pywayne-lark-bot is a skill published in the GitHub repository wangyendt/wayne-skills (8 stars, last pushed 12d ago), licensed MIT. It adds 191 tokens to every session and 11,437 once invoked, about $0.0010 per session on Opus 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 2026-08-31.

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