lark-okr skillA
lark-okr is agent-read markdown (skill) from ethanyoq/skill-hub: 飞书 OKR:管理目标与关键结果。查看和编辑 OKR 周期、目标(Objective)、关键结果(Key Result)、对齐关系、量化指标和进展记录。当用户需要查看或创建 OKR、管理目标和关键结果、查看对齐关系时使用。.
Indexed from public GitHub and served as immutable, content-addressed versions. Install it pinned to an exact SHA-256 with the mdr CLI, and every file is verified against the hash recorded here before it reaches your agent. The deterministic audit below grades the latest version, and the same file always earns the same grade.
How to install
mdr add ethanyoq/skill-hub/lark-okr@v1.0.0mdr add ethanyoq/skill-hub/lark-okr@sha256:eb60b0922e324ed2Pin to a label to follow the author's releases, or to a sha256 to freeze the exact bytes forever. Either way the resolved hash is written to mdr.lock, and mdr install reproduces it on any machine.
[](https://markdownregistry.com/a/art_dor6y5l4vkxrbbxk)
0 badge views in 30 days
Versions
Audit of the latest version
- pass: Frontmatter block present
- pass: Frontmatter declares a name
- pass: Frontmatter declares a description
- pass: Size between 200 bytes and 200 KB (6254 bytes)
- pass: No zero-width or bidi control characters
- pass: No instruction hidden inside an HTML comment
- pass: No link to an exfiltration or paste host
- pass: No credential-shaped string
- pass: No instruction to send local credentials anywhere
- pass: No text hidden with inline styles
- pass: No prompt-injection phrasing
- pass: No curl or wget piped into a shell
- pass: No recursive delete of root, home or parent
- pass: No instruction to read or print local credentials
- pass: No base64 blob over 200 characters
- pass: No link to a raw IP address
- pass: No script tag
Source
ethanyoq/skill-hub · 9 stars · license MIT · pushed 2026-09-15 · branch mine
API
GET https://markdownregistry.com/api/v1/artifacts/art_dor6y5l4vkxrbbxk GET https://markdownregistry.com/api/v1/resolve?ref=ethanyoq/skill-hub/lark-okr GET https://markdownregistry.com/api/v1/blob/eb60b0922e324ed269a54e4c47904ad11b82139905b3d08d354a57a5e3e558f3
Agents talk at modelranch.com: hand yours the instructions there and it joins the network that reads files like this one.