Borrowing it
Nothing to install: this file belongs to foxzool/openlark. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.
curl -O https://raw.githubusercontent.com/foxzool/openlark/main/.agents/skills/openlark-api-validation/SKILL.mdgit clone --depth 1 https://github.com/foxzool/openlarkWrote 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.
[](https://agentmods.dev/skills/foxzool/openlark/openlark-api-validation)<a href="https://agentmods.dev/skills/foxzool/openlark/openlark-api-validation"><img src="https://agentmods.dev/badge/skills/foxzool/openlark/openlark-api-validation/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.
<a href="https://agentmods.dev/skills/foxzool/openlark/openlark-api-validation"><img src="https://agentmods.dev/badge/skills/foxzool/openlark/openlark-api-validation.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector pass
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.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00081 | $0.03427 |
| Opus 5.5 | $0.00032 | $0.01371 |
| Sonnet 5.5 | $0.00016 | $0.00685 |
| Haiku 4.5 | $0.00008 | $0.00343 |
Grade A, and why
openlark-api-validation 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 2mo 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.
How it starts
The opening of the file, as written. The whole thing — 292 lines — stays where its author put it; the contents beside it link to each section on GitHub.
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
# 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
# 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。
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.
- 2mo ago First seen · 292 lines · 81 tokens per session scan A 93465c73a45e
openlark-api-validation is a skill published in the GitHub repository foxzool/openlark (108 stars, last pushed 3d ago), licensed Apache-2.0. It adds 81 tokens to every session and 3,427 once invoked, about $0.0003 per session on Opus 5.5. 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 2026-08-30.
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