Feedgrab
iBigQiang/feedgrab
Universal content grabber — fetch any URL and return structured Markdown.
OpenLark Rust SDK 的代码设计/公共 API 规范审查技能(面向 crate/模块)。用于系统化检查入口设计、feature gating、Request/Service/Builder 一致性、端点体系、Config/错误处理、导出与文档同步、测试与告警控制,并输出按优先级排序的整改清单与可落地改造方案。触发关键词:设计审查、crate 设计、API 设计、public…
$ npx skills add foxzool/openlark --skill openlark-design-review -a claude-codeProject install by default; add -g for ~/.claude/skills/.
$ gh skill install foxzool/openlark openlark-design-review --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/foxzool/openlark.git skills-src && mkdir -p .claude/skills && cp -r skills-src/.agents/skills/openlark-design-review .claude/skills/openlark-design-review && 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 "openlark-design-review" agent skill from https://github.com/foxzool/openlark/tree/main/.agents/skills/openlark-design-review into .claude/skills/openlark-design-review/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "openlark-design-review", 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/foxzool/openlark/tree/main/.agents/skills/openlark-design-reviewType 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 foxzool/openlark --skill openlark-design-review -a codexProject install goes to .agents/skills/; add -g for ~/.codex/skills/.
$ gh skill install foxzool/openlark openlark-design-review --agent codexProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/foxzool/openlark.git skills-src && mkdir -p .agents/skills && cp -r skills-src/.agents/skills/openlark-design-review .agents/skills/openlark-design-review && rm -rf skills-srcUse ~/.agents/skills/ instead of .agents/skills for a personal install.
Codex skills documentation · loads skills from .agents/skills/
Install the "openlark-design-review" agent skill from https://github.com/foxzool/openlark/tree/main/.agents/skills/openlark-design-review into .agents/skills/openlark-design-review/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "openlark-design-review", 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 foxzool/openlark --skill openlark-design-review -a cursorProject install goes to .agents/skills/; add -g for ~/.cursor/skills/.
$ gh skill install foxzool/openlark openlark-design-review --agent cursorProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/foxzool/openlark.git skills-src && mkdir -p .cursor/skills && cp -r skills-src/.agents/skills/openlark-design-review .cursor/skills/openlark-design-review && 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 "openlark-design-review" agent skill from https://github.com/foxzool/openlark/tree/main/.agents/skills/openlark-design-review into .cursor/skills/openlark-design-review/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "openlark-design-review", 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/foxzool/openlark.git --path .agents/skills/openlark-design-review--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 foxzool/openlark --skill openlark-design-review -a gemini-cliProject install goes to .agents/skills/; add -g for ~/.gemini/skills/.
$ gh skill install foxzool/openlark openlark-design-review --agent gemini-cliProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/foxzool/openlark.git skills-src && mkdir -p .gemini/skills && cp -r skills-src/.agents/skills/openlark-design-review .gemini/skills/openlark-design-review && 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 "openlark-design-review" agent skill from https://github.com/foxzool/openlark/tree/main/.agents/skills/openlark-design-review into .gemini/skills/openlark-design-review/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "openlark-design-review", 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 foxzool/openlark openlark-design-reviewInstalls 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 foxzool/openlark --skill openlark-design-review -a github-copilotProject install goes to .agents/skills/; add -g for ~/.copilot/skills/.
$ git clone --depth 1 https://github.com/foxzool/openlark.git skills-src && mkdir -p .github/skills && cp -r skills-src/.agents/skills/openlark-design-review .github/skills/openlark-design-review && 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 "openlark-design-review" agent skill from https://github.com/foxzool/openlark/tree/main/.agents/skills/openlark-design-review into .github/skills/openlark-design-review/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "openlark-design-review", 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 foxzool/openlark --skill openlark-design-review -a opencodeOpenCode documents no install command of its own. Project install goes to .agents/skills/; add -g for ~/.config/opencode/skills/.
$ gh skill install foxzool/openlark openlark-design-review --agent opencodeProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/foxzool/openlark.git skills-src && mkdir -p .opencode/skills && cp -r skills-src/.agents/skills/openlark-design-review .opencode/skills/openlark-design-review && 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 "openlark-design-review" agent skill from https://github.com/foxzool/openlark/tree/main/.agents/skills/openlark-design-review into .opencode/skills/openlark-design-review/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "openlark-design-review", 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.
openlark-design-reviewOpenLark Rust SDK 的代码设计/公共 API 规范审查技能(面向 crate/模块)。用于系统化检查入口设计、feature gating、Request/Service/Builder 一致性、端点体系、Config/错误处理、导出与文档同步、测试与告警控制,并输出按优先级排序的整改清单与可落地改造方案。触发关键词:设计审查、crate 设计、API 设计、public…
Openlark Design Review is an agent skill from foxzool/openlark. OpenLark Rust SDK 的代码设计/公共 API 规范审查技能(面向 crate/模块)。用于系统化检查入口设计、feature gating、Request/Service/Builder 一致性、端点体系、Config/错误处理、导出与文档同步、测试与告警控制,并输出按优先级排序的整改清单与可落地改造方案。触发关键词:设计审查、crate 设计、API 设计、public API、feature flag、端点、Builder/Service、架构一致性
Its SKILL.md is about 2.1k tokens, which your agent loads only when the skill is triggered. The skill folder holds 2 other files, including reference files (for example `references/design-review-report-template.md`).
It sits in Media & Creative, covering Design review and critique and Messaging and chat bots. It works with Rust and Feishu (Lark). The repository describes itself as: 飞书开放平台的非官方 Rust SDK,支持自定义机器人、长连接机器人、云文档、飞书卡片、消息、群组等 API 调用。 The licence is Apache-2.0.
6 steps, taken from the step headings in SKILL.md.
Read from SKILL.md and the folder at commit 393f140. It shows what the files ask for, not the result of running them.
Pre-approves these tools, so the agent can use them without asking each time:
ReadGrepGlobEditBashFrom allowed-tools in the SKILL.md frontmatter.
Shell commands in SKILL.md call:
rgpython3cargoFrom 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.
Openlark Design Review loads about 2.1k tokens when it runs, and up to ~2.9k if it reads all its reference files. Until then it costs about 65 tokens; SKILL.md has 514 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.
allowed-tools: Read, Grep, Glob, Edit, BashAutomated 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.
The full file from foxzool/openlark at commit 393f140, republished under its Apache-2.0 licence (© foxzool). 514 words, ~2,066 tokens.
.claude/skills/openlark-design-review/SKILL.md (or your agent's skills folder). This skill also uses 1 other file; get the full folder from GitHub.本技能适用场景:
其他技能:
Skill(openlark-code-standards)Skill(openlark-api)validate() 写法 → Skill(openlark-validation-style)openlark-design-reviewopenlark-code-standardsopenlark-validation-styleopenlark-apiopenlark-api-validationopenlark-code-standards。openlark-validation-style。把“设计审查”变成可重复执行的流程,而不是随手点评。
你要输出:
meta.Version=old)crates/openlark-docs/)或任意模块树(如 src/ccm/wiki/v2/)目的:把“我觉得实现了很多”变成可验证数据。统计口径默认排除
meta.Version=old。
使用仓库已有脚本直接对比 CSV 与落盘实现(strict 命名规范):
python3 tools/validate_apis.py --crate <crate-name>输出包含:API 总数/已实现/未实现/完成率,以及按 bizTag 的统计表;同时会生成默认报告到 reports/api_validation/<crate>.md。
python3 tools/validate_apis.py --src <crate-src-path> --filter <bizTag...>若需要快速确认“某 bizTag 的有效 API 总数(排除 old)”,可参考仓库文档 crates.md 的统计表(数据源为 api_list_export.csv)。
如需从 api_list_export.csv 重新生成 bizTag 统计(排除 old),可运行:
python3 - <<'PY'
import csv
from collections import Counter
counts = Counter()
counts_all = Counter()
with open("api_list_export.csv", newline="", encoding="utf-8") as f:
r = csv.DictReader(f)
for row in r:
biz = row.get("bizTag")
ver = row.get("meta.Version")
if not biz:
continue
counts_all[biz] += 1
if ver != "old":
counts[biz] += 1
print("bizTag,total,exclude_old,old")
for biz in sorted(counts_all.keys()):
total = counts_all[biz]
ex = counts[biz]
print(f"{biz},{total},{ex},{total-ex}")
print(f"TOTAL,{sum(counts_all.values())},{sum(counts.values())},{sum(counts_all.values())-sum(counts.values())}")
PY如果用户没说清楚范围,必须先追问 2 个问题:
openlark-client/openlark-core)?按以下结构输出,不得随意变形:
现象 → 证据(文件:行) → 影响 → 建议注:证据必须精确到
path:line,避免“我觉得/好像”。
适用:大量端点、调用侧更偏“链式设置参数”。
特征:
Request::new(Config) 保存 ConfigRequest::execute() / execute_with_options(RequestOption)适用:希望把“执行上下文(Config/Transport)”都集中在 Service 上,便于 mock/注入。
特征:
openlark_core::trait_system::ExecutableBuilder 提供(trait 定义在 crates/openlark-core/src/trait_system/executable_builder.rs:11,业务 crate 通过宏批量 impl,例如 crates/openlark-meeting/src/common/macros.rs 的 impl_executable_builder!/impl_executable_builder_owned!)⚠️ trait 名核实:现码中 trait 名是
ExecutableBuilder(不是单字母n)。引用时写完整路径openlark_core::trait_system::ExecutableBuilder,不要写成trait_system::n。
规则:同一个 project/version 内不得同时出现 A+B;若历史原因混用,必须定义清晰的迁移路线。
Client/Service/MainService)导致用户困惑?ambiguous_glob_reexports 需要大量 allow?prelude 是否只导出“高频且稳定”的类型,避免把内部实现细节暴露出去?LarkWsClient 同类),仅在所属业务 crate(如 openlark-communication)暴露,不进 declare_client!/ServiceRegistry 注册表(统一 client 仅注册 P0/P1 资源客户端)。详见 docs/CI_TEST_TARGET_COVERAGE.md(#228 决策)。Cargo.toml 的 feature 是否与 lib.rs/mod.rs 的 #[cfg(feature = "...")] 对齐?default features 是否合理(默认开启过多会放大编译成本与 API 面积)?检查点:
"/open-apis/...")?详细规范见
Skill(openlark-api) §3.2(模板)和§4.3(检查清单)
openlark-core::Config 本身已使用 Arc 共享;crate 内再包一层 Arc<Config> 通常是冗余设计。RequestOption 是否在所有对外执行入口都可用并被透传?禁止模式:
LarkClient 作为具体类型(它是 openlark_client::traits 中的 trait).unwrap() 调用 Config::build()(build() 直接返回 Config)正确模式(参考 openlark-docs/src/common/chain.rs):
Arc<Config>new(Arc<Config>) 透传配置openlark_core::http::Transport(pub struct Transport<T>,http.rs:23,prelude 导出于 lib.rs:93)处理Config::build() 直接返回 Config,不需要 .unwrap()检查点:
# 搜索错误的 LarkClient 用法
# 注:本仓已历史清零(无命中),此命令作“回归守卫”——命中即 P0。
rg "LarkClient::new" crates/
# 搜索错误的 Config::build().unwrap() 用法
# 注:本仓已历史清零(无命中),此命令作“回归守卫”——命中即 P0。
rg "Config::builder\(\).*\.build\(\)\.unwrap\(\)" crates/Transport 精确路径:HTTP 传输统一走
openlark_core::http::Transport(pub struct Transport<T>,定义在crates/openlark-core/src/http.rs:23,由crates/openlark-core/src/lib.rs:93的 prelude 导出)。
Skill(openlark-validation-style))cargo check --all-features 是否无 warning?(deprecated/unused 要么修,要么显式 allow)compile(必要时 no_run/ignore 但要有理由)背景:CI clippy 三个维度(all-features / no-default-features / 各 feature 组合)统一加
--all-targets(#250/#254),把 test/bench target 纳入 lint;门控写法不当会直接被 CI 拦或触发E0601/missing_docs。详见docs/CI_TEST_TARGET_COVERAGE.md。
检查点:
example 必须在 Cargo.toml [[example]] 声明 required-features(CI clippy 跑 --all-targets 会编译 example)。
#。crates/openlark-docs/Cargo.toml 的 required-features = ["baike", "bitable", "ccm-core"]。feature 契约测试文件结构约定://! 文档注释 在前 + #![cfg(feature="x")] 紧随其后。
//! ... 文档;#![cfg(...)] 放第 2 行(顺序反了会触发 clippy missing_docs)。#[cfg] 包整文件,不要把 #![cfg] 放在 //! 之前。crates/openlark-application/tests/application_contract_models.rs:1-2(//! 在第 1 行,#![cfg(feature = "v1")] 在第 2 行)。检查命令:
# 测试文件门控写法(确认 //! 在前、#![cfg(feature)] 紧随)
rg -n '^#!\[cfg\(feature' crates/<crate>/tests/
# example 是否声明 required-features
rg -n 'required-features' crates/<crate>/Cargo.tomlDocsClient),其余入口标 deprecated 并给迁移路径。wiki/v2)试点,再逐步复制到同域其他模块。mod 粒度切到能明显减少编译体积的位置(以“用户开哪个 feature 就编进来什么”为目标)。当用户说“审查 XXX 设计”时:
cargo check/testreferences/design-review-report-template.md© foxzool, Apache-2.0. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file
SKILL.md and 1 other file (references) in .agents/skills/openlark-design-review of foxzool/openlark.
Open the folder on GitHubat commit 393f140
Openlark Design Review 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 |
|---|---|---|---|---|---|---|
| Openlark Design Review this skillfoxzool/openlark | 106 | — | ~2.1k | Automated safety check: Notes | Apache-2.0 | |
| FeedgrabiBigQiang/feedgrab | 614 | — | ~2k | Automated safety check: Pass | MIT | |
| Feishu Seedance Video Pipelinedracohu2025-cloud/draco-skills-collection | 227 | — | ~5k | Automated safety check: Notes | MIT | |
| Qiaomu Mondo Poster Designnexu-io/nexu | 3.3k | 1 repos | ~4.1k | Automated safety check: Pass | MIT | |
| Beautiful Feishu Whiteboardzarazhangrui/beautiful-feishu-whiteboard | 756 | — | ~1.3k | Automated safety check: Pass | MIT | |
| Bili Following Latestdragon-hh/ai-boshu-crawler | 106 | — | ~1.9k | Automated safety check: Pass | None |
iBigQiang/feedgrab
Universal content grabber — fetch any URL and return structured Markdown.
dracohu2025-cloud/draco-skills-collection
A skill your agent uses when running a Feishu/Lark Base-centered Seedance video production pipeline: inspect/backfill the Base row, create/reference assets, build Row-24-style Chinese Seedance…
nexu-io/nexu
一句话生成大师级海报、书籍封面、专辑封面和各类设计作品。无需懂PS、配色或艺术史,AI自动选择最佳风格(基于33+位传奇设计师)。支持多平台多比例:公众号封面(21:9)、小红书配图(3:4)、文章配图(16:9)、书籍封面(9:16)、专辑封面(1:1)、电影海报(9:16)。包含AI提示词优化、风格对比、图生图转换功能。触发词:"Mondo风格"、"书籍封面设计"、"专辑封面"、"海报设计"…
zarazhangrui/beautiful-feishu-whiteboard
A library of 35 curated colour palette styles for building beautiful, editable Feishu / Lark (飞书) whiteboards from SVG.
dragon-hh/ai-boshu-crawler
Run the AI博主爬取 project workflow that downloads the latest Bilibili videos for Feishu Base creators marked 是否持续跟踪=true, writes successful downloads to the Feishu 视频 table, and writes a 爬取任务日志 record.
openclaw/openclaw
Feishu document read/write workflows. An agent skill from openclaw/openclaw.
foxzool/openlark
Prove OpenLark (Feishu/Lark Rust SDK) changes the way a maintainer does — cargo build/test, public examples, API coverage and field-verify harnesses.
foxzool/openlark
OpenLark 项目 API 接口实现规范(速查)。用于添加/重构飞书开放平台 API:确定落盘路径、实现 Body/Response + Builder(Request)、对齐 endpoints 常量/enum、补齐 mod.rs 导出,并明确"调用服务端 API"的方法签名/RequestOption 传递约定。触发关键词:API 接口、API 文件、飞书 API、添加…
foxzool/openlark
OpenLark API 字段核对技能。用于新增/重构飞书 API 后,核对 Rust 实现的请求体/响应体字段是否与飞书官方文档一致。通过 playwright 渲染飞书 SPA 文档页面,提取真实的请求/响应字段定义,对比代码实现找出不符项。触发关键词:字段核对、字段验证、字段不符、文档核对、核对请求字段、核对响应字段、飞书文档字段、推断字段、user 级接口、用户级接口字段
foxzool/openlark
OpenLark 项目代码规范检查技能。用于快速审查仓库内的架构一致性、API 实现套路、参数校验、命名与导出规范,并输出可执行检查清单与证据路径。Triggers: code review / consistency check / architecture audit / 规范检查 / 风格一致性 / 体检 / 对齐约定。项目锚点见 AGENTS.mdCONVENTIONS 与…
foxzool/openlark
OpenLark API 覆盖率验证技能。用于验证各 crate 的 API 实现数量与覆盖率,基于 tools/validateapis.py 脚本和 apilistexport.csv 对比实际代码实现。触发关键词:API 验证、API 覆盖率、验证 API 数量、检查 API 实现、API 统计
foxzool/openlark
OpenLark Rust SDK 命名与对外 API 表达规范(Client/Service/Resource/Request/Builder)。用于新增/重构公开类型、设计 meta 调用链、调整模块导出与 prelude、或排查 Service 同名/语义错配/V{N}Service 版本层错位、Resource 与 Service 同类型两名、以及…
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OpenLark Rust SDK 的代码设计/公共 API 规范审查技能(面向 crate/模块)。用于系统化检查入口设计、feature gating、Request/Service/Builder 一致性、端点体系、Config/错误处理、导出与文档同步、测试与告警控制,并输出按优先级排序的整改清单与可落地改造方案。触发关键词:设计审查、crate 设计、API 设计、public…. Openlark Design Review is an agent skill from foxzool/openlark.
Openlark Design Review fits situations like: tasks that involve Design review and critique; tasks that involve Messaging and chat bots.
Run `npx skills add foxzool/openlark --skill openlark-design-review -a claude-code`. Or copy the skill folder (.agents/skills/openlark-design-review in foxzool/openlark) into .claude/skills/openlark-design-review in your project. Claude Code loads it when a task matches its description.
Run `npx skills add foxzool/openlark --skill openlark-design-review -a codex`. Or copy the skill folder (.agents/skills/openlark-design-review in foxzool/openlark) into .agents/skills/openlark-design-review 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 foxzool/openlark --skill openlark-design-review -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/openlark-design-review, .gemini/skills/openlark-design-review, .github/skills/openlark-design-review and .opencode/skills/openlark-design-review in your project.
Going by SKILL.md and its folder, Openlark Design Review needs the command-line tools its instructions call (rg, python3 and cargo). Our summary lists: Python 3. Its frontmatter pre-approves these tools: Read, Grep, Glob, Edit, Bash.
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 (pre-approves every shell command (allowed-tools: bash)), nothing it rates as a warning. It is not a guarantee. Review the folder before installing.
Openlark Design Review is published under the Apache-2.0 licence (the repository's licence). It allows redistribution, so the full SKILL.md is shown on this page.
About 2.1k tokens (SKILL.md is roughly 8.3k 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 875 tokens, read only when the agent opens those files.
Skills that share tags, products or a category with Openlark Design Review: Feedgrab (iBigQiang/feedgrab, 614 stars), Feishu Seedance Video Pipeline (dracohu2025-cloud/draco-skills-collection, 227 stars), Qiaomu Mondo Poster Design (nexu-io/nexu, 3.3k stars) and Beautiful Feishu Whiteboard (zarazhangrui/beautiful-feishu-whiteboard, 756 stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.
foxzool (a GitHub user) maintains it in foxzool/openlark, which has 106 GitHub stars. The repository holds 8 skills in this directory. The repository was last updated on October 9, 2026.
Source: foxzool/openlark on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.