L
lizhiyao/oh-my-knowledge
OMK — Evidence-backed evaluation and observability for prompts, RAG, skills, agents, and workflows
SECURITY.md ✓
View on GitHub ↗Link checked 2026-11-12 · HTTP 200 · opens the vendor's own site
Install & config
Install command from the repository
npm i -g oh-my-knowledge@next
Parsed from the README we fetched on 2026-10-26; we have not executed it.
This is the install method the repository states, not an MCP client config, so no JSON is generated.
Key names differ by client: Clients & CLI
- Star count
- 25 ★ · lizhiyao/oh-my-knowledge · read from the GitHub search API · (checked 2026-11-13 20:00:50)
- Source
- read directly from its GitHub page · type: open-source project
- Harvest history
- first seen 2026-10-21 · last seen 2026-11-14 · seen 28× · listed by 1 sources
- Score
- score 103 · 25 ★ · 1 sources · repo
- Install
npm i -g oh-my-knowledge@next
FAQ (answers come from our records)
How do I install it?
The repository provides this install command:
npm i -g oh-my-knowledge@next. It comes from the repository itself; we cannot guarantee it runs as-is in your client.Who is it for?
We filed it under these tags: 开源项目. The tags come from the entry itself, not a taxonomy we imposed.
Who maintains it?
repository
lizhiyao/oh-my-knowledge；first catalogued 2026-10-21；last seen 2026-11-14。There is no official certification or quality rating here — we record sources and dates only.# OMK
以下摘录自该仓库的 README（片段） · 在 GitHub 读完整 README →
English | 简体中文
Observe. Measure. Know. Turn working experience into knowledge you can keep maintaining.
OMK is for agent users and AI application developers. Extract candidates from real work, review sources and conditions, accumulate and revise knowledge around objects, then update the skills or prompts that reference it. When you need evidence about a change, compare artifact versions under controlled conditions independently.
## Start with local work records
Requires Node.js ≥22. The library, artifact authoring, and change review described here require 1.0.0-beta.14 or later, from the @next channel; npm latest is a separate stable channel. Beta.13 does not include this maintenance UI. Strict extraction, native outcome archives, bounded retries, model-assisted cross-window link review and study review belong to later main development; a Beta.14 version alone does not establish their availability. See the capability tiers for release and source boundaries. Read the migration guide before upgrading an older installation.
bash
npm i -g oh-my-knowledge@next
omk --version
omk studio
Open the local URL returned by the command and inspect an existing Codex task and its source records. This step makes no model call; Studio offers source and collection guidance when no conversations exist. Follow the observation guide for other log sources.
Next, choose a conversation and turns under “Knowledge → Candidate review”, inspect the material to send, and extract candidates. Extraction calls a model, so prepare an authenticated runtime first. Link sources in the library, revise outdated content, then explicitly generate and save an artifact. Its detail view lets you review knowledge changes and old and new references. Follow the knowledge maintenance workflow.
## When knowledge changes, review its artifacts
In the existing SDK maintenance case, old statements were limited to their historical context, one item was discarded, and another gained a clearer boundary for its static observations. v4 retains three historical references and shows two changes; v5 explicitly selects two currently retained items, while old content and references remain available. Read the case, sources, and review steps.
This verifies maintenance and reference behavior. It does not verify dynamic SDK effects, time saved, or cross-agent reuse benefits. Retaining knowledge, saving artifacts, using them, and verifying effects are separate records. Complete automatic management and reuse across agents remain in development.
## Continue with your task
Compare two artifacts directly: preview the plan in the evaluation quickstart, configure a runtime, then call the model. Fix models and cases, record execution conditions, and inspect decisions, uncertainty, and failed-case evidence.
Embed evaluation in a service: begin with the offline Node example, complete a traceable comparison, then choose models and configuration as needed.
Observe. Measure. Know. Turn working experience into knowledge you can keep maintaining.
OMK is for agent users and AI application developers. Extract candidates from real work, review sources and conditions, accumulate and revise knowledge around objects, then update the skills or prompts that reference it. When you need evidence about a change, compare artifact versions under controlled conditions independently.
## Start with local work records
Requires Node.js ≥22. The library, artifact authoring, and change review described here require 1.0.0-beta.14 or later, from the @next channel; npm latest is a separate stable channel. Beta.13 does not include this maintenance UI. Strict extraction, native outcome archives, bounded retries, model-assisted cross-window link review and study review belong to later main development; a Beta.14 version alone does not establish their availability. See the capability tiers for release and source boundaries. Read the migration guide before upgrading an older installation.
bash
npm i -g oh-my-knowledge@next
omk --version
omk studio
Open the local URL returned by the command and inspect an existing Codex task and its source records. This step makes no model call; Studio offers source and collection guidance when no conversations exist. Follow the observation guide for other log sources.
Next, choose a conversation and turns under “Knowledge → Candidate review”, inspect the material to send, and extract candidates. Extraction calls a model, so prepare an authenticated runtime first. Link sources in the library, revise outdated content, then explicitly generate and save an artifact. Its detail view lets you review knowledge changes and old and new references. Follow the knowledge maintenance workflow.
## When knowledge changes, review its artifacts
In the existing SDK maintenance case, old statements were limited to their historical context, one item was discarded, and another gained a clearer boundary for its static observations. v4 retains three historical references and shows two changes; v5 explicitly selects two currently retained items, while old content and references remain available. Read the case, sources, and review steps.
This verifies maintenance and reference behavior. It does not verify dynamic SDK effects, time saved, or cross-agent reuse benefits. Retaining knowledge, saving artifacts, using them, and verifying effects are separate records. Complete automatic management and reuse across agents remain in development.
## Continue with your task
Compare two artifacts directly: preview the plan in the evaluation quickstart, configure a runtime, then call the model. Fix models and cases, record execution conditions, and inspect decisions, uncertainty, and failed-case evidence.
Embed evaluation in a service: begin with the offline Node example, complete a traceable comparison, then choose models and configuration as needed.
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- Source
- github · https://github.com/lizhiyao/oh-my-knowledge
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