Cc Connect
archibate/dotfiles-opencode
This skill should be used when sending images, files, or notifications back to the user via messaging platforms (Discord, Feishu, Telegram, etc.) through cc-connect.
Sends interactive Feishu group-chat cards that mix markdown text with uploaded chart or diagram images, for progress updates and analysis results.
$ npx skills add xjtulyc/MedgeClaw --skill feishu-rich-card -a claude-codeProject install by default; add -g for ~/.claude/skills/.
$ gh skill install xjtulyc/MedgeClaw feishu-rich-card --agent claude-codeProject scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).
$ git clone --depth 1 https://github.com/xjtulyc/MedgeClaw.git skills-src && mkdir -p .claude/skills && cp -r skills-src/skills/feishu-rich-card .claude/skills/feishu-rich-card && rm -rf skills-srcUse ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.
Claude Code skills documentation · loads skills from .claude/skills/
Install the "feishu-rich-card" agent skill from https://github.com/xjtulyc/MedgeClaw/tree/main/skills/feishu-rich-card into .claude/skills/feishu-rich-card/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "feishu-rich-card", then confirm the skill loads.Claude Code copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$skill-installer install https://github.com/xjtulyc/MedgeClaw/tree/main/skills/feishu-rich-cardType this inside Codex. $skill-installer <name> installs a curated skill from openai/skills. The installer writes to $CODEX_HOME/skills (default ~/.codex/skills). Restart Codex if the skill does not show up.
$ npx skills add xjtulyc/MedgeClaw --skill feishu-rich-card -a codexProject install goes to .agents/skills/; add -g for ~/.codex/skills/.
$ gh skill install xjtulyc/MedgeClaw feishu-rich-card --agent codexProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/xjtulyc/MedgeClaw.git skills-src && mkdir -p .agents/skills && cp -r skills-src/skills/feishu-rich-card .agents/skills/feishu-rich-card && rm -rf skills-srcUse ~/.agents/skills/ instead of .agents/skills for a personal install.
Codex skills documentation · loads skills from .agents/skills/
Install the "feishu-rich-card" agent skill from https://github.com/xjtulyc/MedgeClaw/tree/main/skills/feishu-rich-card into .agents/skills/feishu-rich-card/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "feishu-rich-card", then confirm the skill loads.Codex copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ npx skills add xjtulyc/MedgeClaw --skill feishu-rich-card -a cursorProject install goes to .agents/skills/; add -g for ~/.cursor/skills/.
$ gh skill install xjtulyc/MedgeClaw feishu-rich-card --agent cursorProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/xjtulyc/MedgeClaw.git skills-src && mkdir -p .cursor/skills && cp -r skills-src/skills/feishu-rich-card .cursor/skills/feishu-rich-card && rm -rf skills-srcUse ~/.cursor/skills/ instead of .cursor/skills for a personal install.
Cursor skills documentation · loads skills from .cursor/skills/, .agents/skills/, .claude/skills/, .codex/skills/
Install the "feishu-rich-card" agent skill from https://github.com/xjtulyc/MedgeClaw/tree/main/skills/feishu-rich-card into .cursor/skills/feishu-rich-card/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "feishu-rich-card", then confirm the skill loads.Cursor copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ gemini skills install https://github.com/xjtulyc/MedgeClaw.git --path skills/feishu-rich-card--scope user (default) or --scope workspace; --path is the subfolder of the repo that holds the skill; --consent skips the security confirmation prompt.
$ npx skills add xjtulyc/MedgeClaw --skill feishu-rich-card -a gemini-cliProject install goes to .agents/skills/; add -g for ~/.gemini/skills/.
$ gh skill install xjtulyc/MedgeClaw feishu-rich-card --agent gemini-cliProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/xjtulyc/MedgeClaw.git skills-src && mkdir -p .gemini/skills && cp -r skills-src/skills/feishu-rich-card .gemini/skills/feishu-rich-card && rm -rf skills-srcUse ~/.gemini/skills/ instead of .gemini/skills for a personal install, then run /skills reload.
Gemini CLI skills documentation · loads skills from .gemini/skills/, .agents/skills/
Install the "feishu-rich-card" agent skill from https://github.com/xjtulyc/MedgeClaw/tree/main/skills/feishu-rich-card into .gemini/skills/feishu-rich-card/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "feishu-rich-card", then confirm the skill loads.Gemini CLI copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ gh skill install xjtulyc/MedgeClaw feishu-rich-cardInstalls for Copilot at project scope by default; add --scope user for a personal install. Preview a skill first with gh skill preview. Needs GitHub CLI 2.90.0 or later (public preview).
$ npx skills add xjtulyc/MedgeClaw --skill feishu-rich-card -a github-copilotProject install goes to .agents/skills/; add -g for ~/.copilot/skills/.
$ git clone --depth 1 https://github.com/xjtulyc/MedgeClaw.git skills-src && mkdir -p .github/skills && cp -r skills-src/skills/feishu-rich-card .github/skills/feishu-rich-card && rm -rf skills-srcUse ~/.copilot/skills/ instead of .github/skills for a personal install. Commit .github/skills so cloud agent and code review can use it.
GitHub Copilot skills documentation · loads skills from .github/skills/, .claude/skills/, .agents/skills/
Install the "feishu-rich-card" agent skill from https://github.com/xjtulyc/MedgeClaw/tree/main/skills/feishu-rich-card into .github/skills/feishu-rich-card/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "feishu-rich-card", then confirm the skill loads.GitHub Copilot copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ npx skills add xjtulyc/MedgeClaw --skill feishu-rich-card -a opencodeOpenCode documents no install command of its own. Project install goes to .agents/skills/; add -g for ~/.config/opencode/skills/.
$ gh skill install xjtulyc/MedgeClaw feishu-rich-card --agent opencodeProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/xjtulyc/MedgeClaw.git skills-src && mkdir -p .opencode/skills && cp -r skills-src/skills/feishu-rich-card .opencode/skills/feishu-rich-card && rm -rf skills-srcUse ~/.config/opencode/skills/ instead of .opencode/skills for a personal install.
OpenCode skills documentation · loads skills from .opencode/skills/, .claude/skills/, .agents/skills/
Install the "feishu-rich-card" agent skill from https://github.com/xjtulyc/MedgeClaw/tree/main/skills/feishu-rich-card into .opencode/skills/feishu-rich-card/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "feishu-rich-card", then confirm the skill loads.OpenCode copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
feishu-rich-cardSends interactive Feishu group-chat cards that mix markdown text with uploaded chart or diagram images, for progress updates and analysis results.
Covers the path from generated image to posted card: a chart or diagram is produced with SVG templates converted to PNG, matplotlib or seaborn, or Pillow, then uploaded to Feishu to obtain an `image_key`, since a card cannot reference an image by URL. A helper class in `references/send_card.py` wraps the upload-and-send steps, with a one-line `send_image_report()` method for simple cases.
The card itself is built from a fixed set of elements — markdown blocks, standalone image elements, dividers, multi-column layouts and a footer note — capped at 50 elements per card and declared with card schema version 2.0. Markdown blocks cannot embed images directly; each image needs its own element. A default chat id is read from an environment variable, and the skill notes that the agent's own normal reply should be suppressed after sending a card to avoid a duplicate message.
3 steps, taken from the step headings in SKILL.md.
Read from SKILL.md and the folder at commit fef51d3. It shows what the files ask for, not the result of running them.
Pre-approves nothing: there is no allowed-tools line, so your agent's usual permission prompts apply.
From allowed-tools in the SKILL.md frontmatter.
Ships script files (Python), which the agent can run.
Shell commands in SKILL.md call:
python3From the folder's file list and the shell code blocks in SKILL.md.
No URLs in SKILL.md.
From URLs in SKILL.md, links to its own repository left out.
Names no API keys, tokens, secrets or passwords.
From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.
Feishu Rich Card Sender loads about 734 tokens when it runs, and up to ~3.3k if it reads all its reference files. Until then it costs about 76 tokens; SKILL.md has 136 words of instructions outside code blocks.
Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.
The automated check noted patterns worth knowing about, such as sudo or a known installer.
通过环境变量配置:`FEISHU_DEFAULT_CHAT_ID`(在 `.env` 中设置)Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); files beside SKILL.md are not scanned.
Without a licence we can't republish the file, so here is its outline and opening line. It has 136 words (~734 tokens).
SKILL.md and 1 other file (references) in skills/feishu-rich-card of xjtulyc/MedgeClaw.
Open the folder on GitHubat commit fef51d3
We found 1 copy of this SKILL.md (exact, near-identical or edited) in other folders, from 1 other GitHub owner. This page covers the copy in xjtulyc/MedgeClaw, which our catalogue first saw on October 7, 2026.
Feishu Rich Card Sender next to the 5 skills that share the most tags, products or categories with it. Stars are the repository's; “used in” counts other GitHub owners with a copy.
| Skill | Stars | Used in | Tokens | Auto-check | Licence | Repo updated |
|---|---|---|---|---|---|---|
| Feishu Rich Card Sender this skillxjtulyc/MedgeClaw | 617 | 1 repos | ~734 | Automated safety check: Notes | None | |
| Cc Connectarchibate/dotfiles-opencode | 108 | — | ~1.2k | Automated safety check: Pass | None | |
| Chrome Daily Update Checkdragon-hh/ai-boshu-crawler | 106 | — | ~1.3k | Automated safety check: Pass | None | |
| Ae Systeminfometa/workbuddyskills | 348 | — | ~4.9k | Automated safety check: Pass | None | |
| Feishu Docopenclaw/openclaw | 392k | — | ~516 | Automated safety check: Pass | MIT | |
| Claude To Imop7418/Claude-to-IM-skill | 2.9k | — | ~3.4k | Automated safety check: Notes | MIT |
archibate/dotfiles-opencode
This skill should be used when sending images, files, or notifications back to the user via messaging platforms (Discord, Feishu, Telegram, etc.) through cc-connect.
dragon-hh/ai-boshu-crawler
Run the AI blogger crawler daily update check for Bilibili, Douyin, Xiaohongshu, and YouTube with Chrome producers only where required, the merged Xiaohongshu profile-video skill, and the yt-dlp…
infometa/workbuddyskills
AE Agent system administration CLI for root and agent administrators.
openclaw/openclaw
Feishu document read/write workflows. An agent skill from openclaw/openclaw.
op7418/Claude-to-IM-skill
Bridge THIS Claude Code or Codex session to Telegram, Discord, Feishu/Lark, QQ, or WeChat so the user can chat with Claude from their phone.
raucvr/Group-Goki
Feishu document read/write operations. An agent skill from raucvr/Group-Goki.
xjtulyc/MedgeClaw
Guides an agent through reproducing papers built on the CHARLS health and retirement survey, from variable mapping to cognition, depression and isolation scores.
xjtulyc/MedgeClaw
Routes bioinformatics, drug discovery, clinical and multi-omics tasks from a chat interface to Claude Code sessions running K-Dense scientific skills, with a live dashboard per task.
xjtulyc/MedgeClaw
Detects a usable Chinese, Japanese or Korean font and configures matplotlib so chart labels, titles and legends render instead of showing empty boxes.
xjtulyc/MedgeClaw
Six-phase process for reproducing a published paper's results from provided data, from variable mapping and sample filtering through regression tables and a written report.
xjtulyc/MedgeClaw
Generate professional SVG UI panels for structured information display.
Works with
Sends interactive Feishu group-chat cards that mix markdown text with uploaded chart or diagram images, for progress updates and analysis results. Covers the path from generated image to posted card: a chart or diagram is produced with SVG templates converted to PNG, matplotlib or seaborn, or Pillow, then uploaded to Feishu to obtain an `image_key`, since a card cannot reference an image by URL.py` wraps the upload-and-send steps, with a one-line `send_image_report()` method for simple cases.
Feishu Rich Card Sender fits situations like: reporting analysis progress to a Feishu group with a chart attached; sending a research summary that mixes text and an image in one card; posting a project status update with a multi-column layout to Feishu; combining a matplotlib chart with written commentary in a single message.
Run `npx skills add xjtulyc/MedgeClaw --skill feishu-rich-card -a claude-code`. Or copy the skill folder (skills/feishu-rich-card in xjtulyc/MedgeClaw) into .claude/skills/feishu-rich-card in your project. Claude Code loads it when a task matches its description.
Run `npx skills add xjtulyc/MedgeClaw --skill feishu-rich-card -a codex`. Or copy the skill folder (skills/feishu-rich-card in xjtulyc/MedgeClaw) into .agents/skills/feishu-rich-card in your project. Codex loads it when a task matches its description.
Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add xjtulyc/MedgeClaw --skill feishu-rich-card -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/feishu-rich-card, .gemini/skills/feishu-rich-card, .github/skills/feishu-rich-card and .opencode/skills/feishu-rich-card in your project.
Going by SKILL.md and its folder, Feishu Rich Card Sender needs Python for the scripts in its folder and the command-line tools its instructions call (python3). Our summary lists: A Feishu bot with Card Kit access; matplotlib, PIL or cairosvg for generating the images.
SKILL.md contains no URLs. Any network use would come from the scripts or tools the agent runs. This is read from the text; nothing was executed.
Our automated static check of SKILL.md found notes only (mentions a .env file), nothing it rates as a warning. It is not a guarantee. Review the folder before installing.
No licence was found for Feishu Rich Card Sender or its repository. Without one, default copyright applies: ask the author before reusing or redistributing it.
About 734 tokens (SKILL.md is roughly 2.9k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full. Its references folder adds about 2.6k tokens, read only when the agent opens those files.
Skills that share tags, products or a category with Feishu Rich Card Sender: Cc Connect (archibate/dotfiles-opencode, 108 stars), Chrome Daily Update Check (dragon-hh/ai-boshu-crawler, 106 stars), Ae System (infometa/workbuddyskills, 348 stars) and Feishu Doc (openclaw/openclaw, 392k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.
xjtulyc (a GitHub user) maintains it in xjtulyc/MedgeClaw, which has 617 GitHub stars. The repository holds 6 skills in this directory. The repository was last updated on March 12, 2026.
Source: xjtulyc/MedgeClaw on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.