Agent skill

Openlark API Validation

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

Apache-2.0Auto-check: notesDocuments & Office

Install Openlark API Validation

skills CLI

$ npx skills add foxzool/openlark --skill openlark-api-validation -a claude-code

Project install by default; add -g for ~/.claude/skills/.

GitHub CLI

$ gh skill install foxzool/openlark openlark-api-validation --agent claude-code

Project scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).

Manual copy

$ git clone --depth 1 https://github.com/foxzool/openlark.git skills-src && mkdir -p .claude/skills && cp -r skills-src/.agents/skills/openlark-api-validation .claude/skills/openlark-api-validation && rm -rf skills-src

Use ~/.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/

Paste into Claude Code

Install the "openlark-api-validation" agent skill from https://github.com/foxzool/openlark/tree/main/.agents/skills/openlark-api-validation into .claude/skills/openlark-api-validation/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "openlark-api-validation", 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

$skill-installer install https://github.com/foxzool/openlark/tree/main/.agents/skills/openlark-api-validation

Type 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.

skills CLI

$ npx skills add foxzool/openlark --skill openlark-api-validation -a codex

Project install goes to .agents/skills/; add -g for ~/.codex/skills/.

GitHub CLI

$ gh skill install foxzool/openlark openlark-api-validation --agent codex

Project scope by default (.agents/skills/); add --scope user for a personal install.

Manual copy

$ git clone --depth 1 https://github.com/foxzool/openlark.git skills-src && mkdir -p .agents/skills && cp -r skills-src/.agents/skills/openlark-api-validation .agents/skills/openlark-api-validation && rm -rf skills-src

Use ~/.agents/skills/ instead of .agents/skills for a personal install.

Codex skills documentation · loads skills from .agents/skills/

Paste into Codex

Install the "openlark-api-validation" agent skill from https://github.com/foxzool/openlark/tree/main/.agents/skills/openlark-api-validation into .agents/skills/openlark-api-validation/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "openlark-api-validation", 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.

skills CLI

$ npx skills add foxzool/openlark --skill openlark-api-validation -a cursor

Project install goes to .agents/skills/; add -g for ~/.cursor/skills/.

GitHub CLI

$ gh skill install foxzool/openlark openlark-api-validation --agent cursor

Project scope by default (.agents/skills/); add --scope user for a personal install.

Manual copy

$ git clone --depth 1 https://github.com/foxzool/openlark.git skills-src && mkdir -p .cursor/skills && cp -r skills-src/.agents/skills/openlark-api-validation .cursor/skills/openlark-api-validation && rm -rf skills-src

Use ~/.cursor/skills/ instead of .cursor/skills for a personal install.

Cursor skills documentation · loads skills from .cursor/skills/, .agents/skills/, .claude/skills/, .codex/skills/

Paste into Cursor

Install the "openlark-api-validation" agent skill from https://github.com/foxzool/openlark/tree/main/.agents/skills/openlark-api-validation into .cursor/skills/openlark-api-validation/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "openlark-api-validation", 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

$ gemini skills install https://github.com/foxzool/openlark.git --path .agents/skills/openlark-api-validation

--scope user (default) or --scope workspace; --path is the subfolder of the repo that holds the skill; --consent skips the security confirmation prompt.

skills CLI

$ npx skills add foxzool/openlark --skill openlark-api-validation -a gemini-cli

Project install goes to .agents/skills/; add -g for ~/.gemini/skills/.

GitHub CLI

$ gh skill install foxzool/openlark openlark-api-validation --agent gemini-cli

Project scope by default (.agents/skills/); add --scope user for a personal install.

Manual copy

$ git clone --depth 1 https://github.com/foxzool/openlark.git skills-src && mkdir -p .gemini/skills && cp -r skills-src/.agents/skills/openlark-api-validation .gemini/skills/openlark-api-validation && rm -rf skills-src

Use ~/.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/

Paste into Gemini CLI

Install the "openlark-api-validation" agent skill from https://github.com/foxzool/openlark/tree/main/.agents/skills/openlark-api-validation into .gemini/skills/openlark-api-validation/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "openlark-api-validation", 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.

GitHub CLI

$ gh skill install foxzool/openlark openlark-api-validation

Installs 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).

skills CLI

$ npx skills add foxzool/openlark --skill openlark-api-validation -a github-copilot

Project install goes to .agents/skills/; add -g for ~/.copilot/skills/.

Manual copy

$ git clone --depth 1 https://github.com/foxzool/openlark.git skills-src && mkdir -p .github/skills && cp -r skills-src/.agents/skills/openlark-api-validation .github/skills/openlark-api-validation && rm -rf skills-src

Use ~/.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/

Paste into GitHub Copilot

Install the "openlark-api-validation" agent skill from https://github.com/foxzool/openlark/tree/main/.agents/skills/openlark-api-validation into .github/skills/openlark-api-validation/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "openlark-api-validation", 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.

skills CLI

$ npx skills add foxzool/openlark --skill openlark-api-validation -a opencode

OpenCode documents no install command of its own. Project install goes to .agents/skills/; add -g for ~/.config/opencode/skills/.

GitHub CLI

$ gh skill install foxzool/openlark openlark-api-validation --agent opencode

Project scope by default (.agents/skills/); add --scope user for a personal install.

Manual copy

$ git clone --depth 1 https://github.com/foxzool/openlark.git skills-src && mkdir -p .opencode/skills && cp -r skills-src/.agents/skills/openlark-api-validation .opencode/skills/openlark-api-validation && rm -rf skills-src

Use ~/.config/opencode/skills/ instead of .opencode/skills for a personal install.

OpenCode skills documentation · loads skills from .opencode/skills/, .claude/skills/, .agents/skills/

Paste into OpenCode

Install the "openlark-api-validation" agent skill from https://github.com/foxzool/openlark/tree/main/.agents/skills/openlark-api-validation into .opencode/skills/openlark-api-validation/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "openlark-api-validation", 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.

Facts

Skill name: openlark-api-validation
GitHub stars: 106
Token cost: ~2k tokens
SKILL.md length: 456 words
Files: 1
Skills in repo: 8
Repo updated: Oct 3, 2026
First seen: Oct 7, 2026
Licence: Apache-2.0

At a glance

Works in 8 steps: 验证单个 crate 的 API 覆盖率 → 列出所有可用的 crate 映射 → 自定义验证范围 → …
Tasks that involve CSV and tabular files
SKILL.md covers 🧭 技能路由指南, 🎯 技能用途, 📋 快速工作流 and 📊 报告解读, plus 6 more sections
Calls python3 and just

What it does

Openlark API Validation is an agent skill from 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

Its SKILL.md is about 2k tokens, which your agent loads only when the skill is triggered. It is a single SKILL.md file with no bundled scripts.

It sits in Documents & Office, covering CSV and tabular files and Messaging and chat bots. It works with 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.

When your agent uses it

Tasks that involve CSV and tabular files
Tasks that involve Messaging and chat bots

Example prompts

“/openlark-api-validation”

Requirements

Python 3
Pre-approved tools (allowed-tools): Bash, Read, Edit, Write

Workflow steps

8 steps, taken from the step headings in SKILL.md.

验证单个 crate 的 API 覆盖率
列出所有可用的 crate 映射
自定义验证范围
验证所有 crates（批量）
CSV 文件不存在
源码目录不存在
完成率异常
「额外文件」白名单（预期，非缺陷）

What it can do on your machine

Read from SKILL.md and the folder at commit 6128d6d. It shows what the files ask for, not the result of running them.

Tool permissions
Pre-approves these tools, so the agent can use them without asking each time:
- Bash
- Read
- Edit
- Write
From allowed-tools in the SKILL.md frontmatter.
Runs code
Shell commands in SKILL.md call:
- python3
- just
From the folder's file list and the shell code blocks in SKILL.md.
Network
No URLs in SKILL.md.
From URLs in SKILL.md, links to its own repository left out.
Credentials
Names no API keys, tokens, secrets or passwords.
From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.

Context cost

Openlark API Validation loads about 2k tokens when it runs. Until then it costs about 45 tokens; SKILL.md has 456 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it: ~45
When it runs · the whole SKILL.md, loaded when a task matches: ~2k

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.

Safety

Auto-check: notes

The automated check noted patterns worth knowing about, such as sudo or a known installer.

NotePre-approves every shell command (allowed-tools: Bash)SKILL.md
```
allowed-tools: Bash, Read, Edit, Write
```

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.

SKILL.md

The full file from foxzool/openlark at commit 6128d6d, republished under its Apache-2.0 licence (© foxzool). 456 words, ~1,955 tokens.

Download SKILL.mdSave it as .claude/skills/openlark-api-validation/SKILL.md (or your agent's skills folder).

name: openlark-api-validation
description: 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/validate_apis.py 脚本和 api_list_export.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
allowed-tools: Bash, Read, Edit, Write
argument-hint: [crate-name|path|bizTag]

OpenLark API 覆盖率验证技能

🧭 技能路由指南

本技能适用场景：

需要统计某个 crate/bizTag 的 API 覆盖率
需要输出缺失 API 清单与完成率报告
需要对比 api_list_export.csv 与实际落盘实现

其他技能：

项目级规范体检（架构/API/导出/校验一体）→ Skill(openlark-code-standards)
新增/重构具体 API → Skill(openlark-api)
字段正确性核对（文档 vs 代码）→ Skill(openlark-api-field-verify)
审查整体架构与公共 API 收敛 → Skill(openlark-design-review)

关键词触发映射

覆盖率、缺失 API、实现数量、CSV 对比、验证脚本、报告 → openlark-api-validation
字段核对、文档字段、playwright → openlark-api-field-verify
新增 API、重构 API、Builder、Request/Response、mod.rs 导出 → openlark-api
代码规范、规范检查、风格一致性、体检 → openlark-code-standards
架构设计、public API、收敛方案、feature gating、兼容策略 → openlark-design-review
validate、必填校验、validate_required、空白字符串、校验聚合 → openlark-validation-style

双向跳转规则

本技能只回答「文件在不在」；若要核对字段是否与飞书文档一致，转 openlark-api-field-verify。
若发现缺失 API 的根因是架构分层/范式混乱，转 openlark-design-review。
若发现问题是具体 API 尚未实现，转 openlark-api 落地实现。
若需要把覆盖率问题归因到全仓规范一致性，转 openlark-code-standards。

🎯 技能用途

本技能用于验证 OpenLark 项目中各 crate 的 API 实现覆盖率，通过对比 api_list_export.csv 中的 API 定义与实际代码实现，生成详细的覆盖率报告。

📋 快速工作流

1. 验证单个 crate 的 API 覆盖率

bash

# 验证 openlark-docs crate
python3 tools/validate_apis.py --crate openlark-docs

# 验证 openlark-communication crate
python3 tools/validate_apis.py --crate openlark-communication

# 验证 openlark-meeting crate
python3 tools/validate_apis.py --crate openlark-meeting

输出位置： reports/api_validation/{crate}.md

2. 列出所有可用的 crate 映射

bash

# 查看所有 crate → bizTag 映射
python3 tools/validate_apis.py --list-crates

示例输出（以实际 --list-crates 输出为准）：

📄 映射文件: tools/api_coverage.toml

- openlark-analytics: src=crates/openlark-analytics/src biz_tags=[search, report]
- openlark-application: src=crates/openlark-application/src biz_tags=[application, workplace]
- openlark-auth: src=crates/openlark-auth/src biz_tags=[auth, passport, verification_information, human_authentication]
...

映射共 15 个 crate（核对自 tools/api_coverage.toml）。新增 crate 时，在 tools/api_coverage.toml 追加 [crates.<name>] 段（src + biz_tags，可选 dashboard_groups）即自动纳入 --crate/--all-crates/--list-crates，无需改脚本。

3. 自定义验证范围

bash

# 指定源码目录和业务标签
python3 tools/validate_apis.py \
  --csv api_list_export.csv \
  --src crates/openlark-docs/src \
  --filter ccm base baike \
  --output custom_report.md

# 包含旧版本 API
python3 tools/validate_apis.py --crate openlark-docs --include-old

4. 验证所有 crates（批量）

bash

# 一条命令验证映射里的全部 crate，并生成汇总报告 + 仪表盘
python3 tools/validate_apis.py --all-crates

# 等价的日常快捷命令（just recipe）
just api-coverage

--all-crates 遍历 tools/api_coverage.toml 中映射的 15 个 crate 做汇总统计，产出（注意：不逐个刷新 per-crate 报告）：

reports/api_validation/summary.md / summary.json —— 全仓汇总
reports/api_validation/dashboards/<group>.{md,json} —— 按 dashboard_groups 分组（如 core_business）

⚠️ per-crate 的 reports/api_validation/<crate>.md 不会被 --all-crates 刷新（会保持陈旧，可能与 SUMMARY 数据漂移——例如曾出现 per-crate 报告显示 100% 而 SUMMARY 显示 41.9% 的矛盾）。要拿某 crate 的最新详细报告/缺失清单，单独跑 python3 tools/validate_apis.py --crate <crate-name>（如 --crate openlark-workflow）。

📊 报告解读

报告结构

生成的 Markdown 报告包含以下部分：

一、总体统计

API 总数：CSV 中定义的 API 数量
已实现：已实现的 API 数量
未实现：缺失的 API 数量
完成率：实现百分比
额外文件：代码中存在但 CSV 中未定义的文件

二、模块统计

按 bizTag 分组的统计信息，展示各业务域的完成率。

三、未实现的 API

详细列出所有未实现的 API，包括：

API ID
预期文件路径
API URL
文档链接

四、额外的实现文件

列出不匹配 CSV 定义的额外文件（可能是辅助文件或需要更新 CSV）。

五、已实现的 API

按模块分组列出所有已实现的 API。

示例报告片段

以下数字仅为格式示意，以实际生成的报告为准，请勿当作覆盖率基线。

markdown

## 一、总体统计

| 指标 | 数量 |
|------|------|
| **API 总数** | 254 |
| **已实现** | 240 |
| **未实现** | 14 |
| **完成率** | 94.5% |
| **额外文件** | 3 |

## 二、模块统计

| 模块 | API 数量 | 已实现 | 未实现 | 完成率 |
|------|---------|--------|--------|--------|
| BASE | 49 | 48 | 1 | 98.0% |
| BAIKE | 27 | 27 | 0 | 100.0% |
| CCM | 174 | 160 | 14 | 92.0% |
| MINUTES | 4 | 4 | 0 | 100.0% |

🔧 配置文件

tools/api_coverage.toml

定义 crate → bizTag 映射关系，用于自动补全验证参数。

格式：

toml

[crates.{crate_name}]
src = "crates/{crate_name}/src"
biz_tags = ["bizTag1", "bizTag2", ...]

添加新 crate 映射：

编辑 tools/api_coverage.toml
追加 [crates.<name>] 段（src + biz_tags，可选 dashboard_groups）
运行 --list-crates 验证配置

tools/api_priority.toml

缺失 API 的业务优先级模型，把“有多少 API 没实现”升级为“缺口按价值怎么排序”。

综合分公式（核对自 tools/validate_apis.py 的 priority_formula()）：

综合分 = 业务价值×0.50 + 高频场景×0.30 + (6 - 实现复杂度)×0.20

三个维度均取 1–5（[defaults] 默认各为 3），实现复杂度在综合分里反向计入（越难分越低）。
评分来源：[defaults] 基线 + [[rules]] 覆盖（按声明顺序匹配，后面的更具体规则覆盖前面的；可按 biz_tags / expected_file_prefixes / methods / name_prefixes 命中）。
分层：[[priority_tiers]] 定义 P0/P1/P2/P3 阈值（如 min_score = 4.4 → P0）。
覆盖路径：脚本默认 --priority-config tools/api_priority.toml（见 tools/validate_apis.py 参数定义）；如需切换模型可用该参数指向别的 toml。
输出条件：仅当该 crate 存在缺失 API 时，才在报告里写「缺失 API 优先级清单」段（含综合分、P 级、判定规则）；无缺口则不输出。

🚨 常见问题

Show full SKILL.md (184 more words)Show less

1. CSV 文件不存在

错误： ❌ 错误: CSV 文件不存在: api_list_export.csv

解决：

确保 api_list_export.csv 在项目根目录
或使用 --csv 参数指定路径

2. 源码目录不存在

错误： ❌ 错误: 源码目录不存在: crates/xxx/src

解决：

检查 crate 名称是否正确（使用 --list-crates 查看）
或使用 --src 参数手动指定路径

3. 完成率异常

现象： 完成率超过 100% 或有大量"额外文件"

可能原因：

命名规范不匹配（文件命名与 CSV 定义不一致）
存在辅助文件（service.rs、models.rs 等）
CSV 定义过时

解决：

检查命名规范：src/{bizTag}/{project}/{version}/{resource}/{name}.rs
更新 CSV 文件
检查是否需要更新 tools/api_coverage.toml 映射

4. 「额外文件」白名单（预期，非缺陷）

现象： 报告「额外的实现文件」段里反复出现一批非 API 文件，完成率看着偏低。

说明： 以下文件是 crate 的组织骨架/聚合层/测试，本就不对应任何 CSV 中的 API，不计入 API 覆盖，出现属预期：

prelude.rs、mod.rs —— 模块聚合 / 导出预导出
versions.rs —— 版本聚合入口
models.rs、models/ —— Serde 模型集中存放
services.rs、service.rs —— Service/Client 注册表
tests.rs、tests/ —— 测试

只有当「额外文件」里出现疑似真实 API 落盘但命名不匹配 CSV（例如拼错 bizTag / version / resource）时，才需要按命名规范排查。

📝 命名规范

API 文件路径严格遵循以下规范：

src/{bizTag}/{project}/{version}/{resource}/{name}.rs

规则：

meta.resource 中的 . 转换为 / 作为子目录
meta.name 中的 / 转换为 / 作为子目录
meta.name 中的 : 替换为 _（路径参数）
使用 snake_case 命名

示例：

API	文件路径
`bizTag=ccm, project=drive, version=v1, resource=file, name=create`	`src/ccm/drive/v1/file/create.rs`
`bizTag=base, project=bitable, version=v1, resource=app.table, name=record/create`	`src/base/bitable/v1/app/table/record/create.rs`

🔗 相关技能

添加新 API：Skill(openlark-api)
设计审查：Skill(openlark-design-review)
校验风格：Skill(openlark-validation-style)

📚 工作流集成

CI/CD 接线（已存在，勿重复造）

仓库没有 .github/workflows/api-validation.yml，也没有 pre-commit hook 跑覆盖率。真实接线分布在两个 workflow：

release.yml（.github/workflows/release.yml:70）—— 打 tag 发版时，github-release job 执行 python3 tools/validate_apis.py --all-crates，生成全仓覆盖率汇总。
pre-release-compatibility.yml（.github/workflows/pre-release-compatibility.yml）—— 当 tools/validate_apis.py（以及 release.yml、相关 docs/scripts、src/lib.rs）改动时触发；它调用 scripts/check-pre-release-compatibility.sh，并上传 reports/api_validation/{summary.json,summary.md,dashboards/core_business.json,dashboards/core_business.md} 作为 artifact（pre-release-compatibility-report）。

日常本地

bash

just api-coverage   # 等价 python3 tools/validate_apis.py --all-crates

仓库未配置 pre-commit hook，本地验证靠 just api-coverage 或直接跑脚本。

🎓 最佳实践

定期验证：每次添加新 API 后运行验证
保持同步：确保 CSV 文件与飞书官方文档同步
更新映射：添加新 crate 时及时更新 api_coverage.toml
审查报告：关注"额外文件"，可能需要更新 CSV 或重构代码
100% 目标：确保核心 API 实现率达到 100%

Files

Just SKILL.md in .agents/skills/openlark-api-validation of foxzool/openlark.

Open the folder on GitHubat commit 6128d6d

Compare with similar skills

Openlark API Validation 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.

Openlark API Validation compared with similar skills
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Lark Slidesaiskillstore/marketplace	430	—	~3.1k	Automated safety check: Pass	None	today
Instrument Data To Allotropeaws-samples/amazon-bedrock-agents-healthcare-lifesciences	274	2 repos	~2.7k	Automated safety check: Pass	Apache-2.0	5 days ago
Feishu Docraucvr/Group-Goki	112	3 repos	~592	Automated safety check: Pass	MIT	4 mo ago

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Works with

Feishu (Lark)

Questions about Openlark API Validation

What does Openlark API Validation do?

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. Openlark API Validation is an agent skill from foxzool/openlark.

When should I use Openlark API Validation?

Openlark API Validation fits situations like: tasks that involve CSV and tabular files; tasks that involve Messaging and chat bots.

How do I install Openlark API Validation in Claude Code?

Run `npx skills add foxzool/openlark --skill openlark-api-validation -a claude-code`. Or copy the skill folder (.agents/skills/openlark-api-validation in foxzool/openlark) into .claude/skills/openlark-api-validation in your project. Claude Code loads it when a task matches its description.

How do I install Openlark API Validation in Codex?

Run `npx skills add foxzool/openlark --skill openlark-api-validation -a codex`. Or copy the skill folder (.agents/skills/openlark-api-validation in foxzool/openlark) into .agents/skills/openlark-api-validation in your project. Codex loads it when a task matches its description.

Can I use Openlark API Validation in Cursor, Gemini CLI or GitHub Copilot?

Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add foxzool/openlark --skill openlark-api-validation -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-api-validation, .gemini/skills/openlark-api-validation, .github/skills/openlark-api-validation and .opencode/skills/openlark-api-validation in your project.

What does Openlark API Validation need to run?

Going by SKILL.md and its folder, Openlark API Validation needs the command-line tools its instructions call (python3 and just). Our summary lists: Python 3. Its frontmatter pre-approves these tools: Bash, Read, Edit, Write.

Does Openlark API Validation access the network?

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.

Is Openlark API Validation safe to install?

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.

What licence does Openlark API Validation use?

Openlark API Validation 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.

How many tokens does Openlark API Validation use?

About 2k tokens (SKILL.md is roughly 7.8k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full.

What are the alternatives to Openlark API Validation?

Skills that share tags, products or a category with Openlark API Validation: Lark Drive (appleweiping/WEIPING_WIKI, 119 stars), Review Analyzer Skill (buluslan/review-analyzer-skill, 129 stars), Lark Slides (aiskillstore/marketplace, 430 stars) and Instrument Data To Allotrope (aws-samples/amazon-bedrock-agents-healthcare-lifesciences, 274 stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Openlark API Validation?

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 3, 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.

Install Openlark API Validation

Facts

At a glance

What it does

When your agent uses it

Example prompts

Requirements

Workflow steps

What it can do on your machine

Tool permissions

Runs code

Network

Credentials

Context cost

Safety

SKILL.md

OpenLark API 覆盖率验证技能

🧭 技能路由指南

关键词触发映射

双向跳转规则

🎯 技能用途

📋 快速工作流

1. 验证单个 crate 的 API 覆盖率

2. 列出所有可用的 crate 映射

3. 自定义验证范围

4. 验证所有 crates（批量）

📊 报告解读

报告结构

一、总体统计

二、模块统计

三、未实现的 API

四、额外的实现文件

五、已实现的 API

示例报告片段

🔧 配置文件

tools/api_coverage.toml

tools/api_priority.toml

🚨 常见问题

1. CSV 文件不存在

2. 源码目录不存在

3. 完成率异常

4. 「额外文件」白名单（预期，非缺陷）

📝 命名规范

🔗 相关技能

📚 工作流集成

CI/CD 接线（已存在，勿重复造）

日常本地

🎓 最佳实践

Files

Compare with similar skills

Similar skills

More from foxzool/openlark

Related

Questions about Openlark API Validation