@datawhalechina
Creator · datawhalechina
Last updated · Sep 1, 2026
Llm Universe
STRONG · 76Community indexed
本项目是一个面向小白开发者的大模型应用开发教程，在线阅读地址：https://datawhalechina.github.io/llm-universe/
Creator · datawhalechina
Last updated · Sep 1, 2026
本项目是一个面向小白开发者的大模型应用开发教程，在线阅读地址：https://datawhalechina.github.io/llm-universe/
Creator · datawhalechina
Last updated · Sep 1, 2026
本项目是一个面向小白开发者的大模型应用开发教程，在线阅读地址：https://datawhalechina.github.io/llm-universe/
Creator · datawhalechina
Last updated · Sep 1, 2026
本项目是一个面向小白开发者的大模型应用开发教程，在线阅读地址：https://datawhalechina.github.io/llm-universe/
Creator · datawhalechina
Last updated · Sep 1, 2026
本项目是一个面向小白开发者的大模型应用开发教程，在线阅读地址：https://datawhalechina.github.io/llm-universe/
Review then install
Install targets
Codex install prompt
Install the "Llm Universe" agent skill from https://github.com/datawhalechina/llm-universe. Read its SKILL.md or equivalent instructions first, install only the files needed for this workspace, and summarize any required setup before using it. Skill purpose: 本项目是一个面向小白开发者的大模型应用开发教程，在线阅读地址：https://datawhalechina.github.io/llm-universe/ After the install attempt, report the result to https://www.openagentskill.com/api/agent/outcome with POST JSON {"event_id":"install_<unique-id>","skill_slug":"datawhalechina-llm-universe","task":"Install Llm Universe","agent":"codex","outcome":"success","install_used":true}. Replace event_id with a unique value and outcome with success or failed. Report success only after the skill is installed and a minimal verification passes.Supply asset profile
CSV, SQL, notebooks, dashboards, data pipelines, BI, ETL, and spreadsheet analysis.
Scenario
RAG and knowledge
I need my agent to build a RAG workflow over documents and retrieve reliable context.
Agent fit
Claude Code + LangChain + CLI
Codex, Claude Code, Cursor, CLI, or custom agents.
Install
Ready
npx skills add datawhalechina/llm-universe
Maintenance
stable
6mo since push
Risk
Needs review
License is unclear
GitHub quality
13K
95/100 Quality · 84/100 Trust
Coverage tags
Review notes
License is unclear · Financial research output is not financial advice; require human review before any live investment decision
Agent adoption scorecard
These scores combine public repository metadata, OpenAgentSkill review signals, maintenance freshness, and install readiness. They are a shortlist signal, not a replacement for human review.
Quality
ExcellentHigh-confidence pick with strong adoption and healthy maintenance signals.
Trust
Review then installGood shortlist signal, but the agent should review audit notes, install policy, and outcome evidence before running it.
Audit
Needs reviewA machine-readable review of install readiness, security metadata, maintenance, and adoption risk.
OpenAgentSkill Trust Score v5
Use as the primary candidate after human or sandbox review.
Stars
13K GitHub stars
Repo activity
13K stars, 1.4K forks
Maintenance
6mo since push
License
Unknown
Install
npx skills add datawhalechina/llm-universe
Agent-readable metadata
Use this block or the embedded JSON to decide whether an agent should install this skill, choose an alternative, or ask for human review first.
Suited tasks
Suited agents
Install decision
Trust and risk
Outcome loop
Install command
npx skills add datawhalechina/llm-universeDo not use when
Agent safety v2
Usable candidate, but the agent should surface permission and audit notes before installation.
Require human approval before installing into a real workspace.
medium
Skill likely fetches remote pages, APIs, repositories, or external services.
medium
Skill may read or write project files, documents, generated artifacts, or local workspace state.
Agent resolve plan
The Resolve API returns the selected skill, alternatives, safety policy, audit notes, install target, and copy-paste prompt an agent can follow without scraping this page.
Open JSON
/api/agent/resolve?task=Use%20Llm%20Universe%20for%20an%20agent%20workflow&agent=codex&max_risk=medium
Resolve text
/api/agent/resolve?task=Use%20Llm%20Universe%20for%20an%20agent%20workflow&agent=codex&max_risk=medium&format=text
Install handoff
/api/skills/datawhalechina-llm-universe/install
Agent should check
Copy prompt
Task: Use Llm Universe in this workspace.
Resolve first: https://www.openagentskill.com/api/agent/resolve?task=Use%20Llm%20Universe%20for%20an%20agent%20workflow&agent=codex&max_risk=medium
Review install handoff: https://www.openagentskill.com/api/skills/datawhalechina-llm-universe/install
Install command: npx skills add datawhalechina/llm-universe
Before running it, summarize audit warnings, required permissions, and the fallback skill if install is risky.Agent handoff
Use the public install endpoint to fetch the command, safety checklist, target prompts, and canonical links for this skill.
Install handoff
/api/skills/datawhalechina-llm-universe/install
LLM text format
/api/skills/datawhalechina-llm-universe/install?format=text
Find alternatives
/api/skills/search?q=Llm%20Universe&limit=3
Agent prompt
Use Llm Universe for this task. Review https://www.openagentskill.com/api/skills/datawhalechina-llm-universe/install, then install with: npx skills add datawhalechina/llm-universeRegistry metadata
This page exposes the same decision, trust, audit, use-case, and install signals through the Registry API, so agents can rank this skill without scraping the UI.
Manifest
/api/registry/manifest/datawhalechina-llm-universe
LLM text
/api/registry/manifest/datawhalechina-llm-universe?format=text
Install alias
/api/registry/install/datawhalechina-llm-universe
Recommend
/api/registry/recommend?task=Use%20Llm%20Universe%20in%20an%20agent%20workflow&limit=3
Agent fit
RAG and knowledge
Use-case tags
Platforms
Jupyter Notebook, RAG, Claude Code, LangChain
Audit report
A machine-readable review of install readiness, security metadata, maintenance, and adoption risk.
Agent decision cockpit
Use this as a leading candidate, then validate the README and install path in your own agent stack.
Role in stack
Primary pick
Primary fit
RAG and knowledge
Trust label
Production-ready
Install path
Command ready
Use when
Evidence
review first
Implementation path
Trust profile
Good shortlist signal, but the agent should review audit notes, install policy, and outcome evidence before running it.
GitHub adoption
PASS13K GitHub stars
Stars/forks activity
PASS13K stars, 1.4K forks; issue activity unavailable in current metadata
Recent maintenance
INFO6mo since push
License clarity
CHECKUnknown
Good signals
Review before install
Recommended action
Use as the primary candidate after human or sandbox review.
Quality profile
High-confidence pick with strong adoption and healthy maintenance signals.
Workflow fit
Search private knowledge
I need my agent to build a RAG workflow over documents and retrieve reliable context.
Build and ship code
I need a coding agent that can understand a repository, edit code, and review pull requests.
Automate repeated work
I need my agent to automate a repeated workflow across tools and files.
Workflow fit
Ingest, retrieve, and cite
A workflow for document-heavy agents that ingest files, create searchable knowledge, retrieve relevant context, and answer with grounded sources.
Turn skills into distribution
A workflow for turning newly indexed skills into SEO briefs, social drafts, comparison pages, and reusable publishing workflows.
Inspect, patch, and verify code
A workflow for software agents that inspect repositories, review pull requests, generate tests, and turn findings into shippable patches.
Alternative shortlist
Similar skills that may fit this task.
100+ AI Agent & RAG apps you can actually run — clone, customize, ship.
📚 《从零开始构建智能体》——从零开始的智能体原理与实践教程
Ready-to-run cloud templates for RAG, AI pipelines, and enterprise search with live data. 🐳Docker-friendly.⚡Always in sync with Sharepoint, Google Drive, S3, Kafka, PostgreSQL, real-time data APIs, and more.
Build AI Agents, Visually
本项目是一个面向小白开发者的大模型应用开发教程，在线阅读地址：https://datawhalechina.github.io/llm-universe/
Imported by the skill-only GitHub discovery pipeline because it matches agent skill, automation, domain workflow, RAG, document-processing, data, finance, security, or developer-tool signals. Protocol-server projects are excluded from automated imports.
Frameworks & tools
Decision snapshot
13,412 GitHub stars
Audit
Install and adoption review
Agent-proven evidence
Outcome reports after resolve, review, install, and one narrow run.
No agent outcome data yet. The first agent run can report success, setup needs, risk blocks, failure, or not-relevant through /api/agent/outcome.
Install
Free and open source. Review the report before installing into production agents.
Growth loop
Scenario-led draft for Llm Universe, ready for a manual X post.
A practical pick for source-backed research: Llm Universe: 本项目是一个面向小白开发者的大模型应用开发教程，在线阅读地址：https://datawhalechina.github.io/llm-universe/ 13.4K stars https://www.openagentskill.com/skills/datawhalechina-llm-universe?ref=x
Listing + install path for Llm Universe: https://www.openagentskill.com/skills/datawhalechina-llm-universe?ref=x Install: npx skills add datawhalechina/llm-universe
Listing source
This listing was indexed from public sources and is not marked official until a maintainer claim is approved.
Attribution links to the public repository or creator profile. Creators can claim the listing to update ownership signals.
Claim this skillOwner claim
This Community indexed listing is attributed to datawhalechina but is not marked official yet. Claim it to add a verified owner signal and make future launch, install, and audit updates easier to trust.
Creator backlink kit
Show the canonical listing, current trust and audit signals, and real Agent-Proven evidence where developers evaluate the repository.
[](https://www.openagentskill.com/skills/datawhalechina-llm-universe?ref=github&utm_source=github&utm_medium=referral&utm_campaign=creator_badge)
[](https://www.openagentskill.com/skills/datawhalechina-llm-universe?ref=github&utm_source=github&utm_medium=referral&utm_campaign=creator_badge)
[](https://www.openagentskill.com/skills/datawhalechina-llm-universe/audit)
[](https://www.openagentskill.com/skills/datawhalechina-llm-universe?ref=github&utm_source=github&utm_medium=referral&utm_campaign=creator_badge)datawhalechina✓
@datawhalechina
Share whether this skill looks useful for your agent workflow. Aggregated feedback improves rankings over time.
Review then install
Awesome Llm Apps
100+ AI Agent & RAG apps you can actually run — clone, customize, ship.
114.5K StarsHello Agents
📚 《从零开始构建智能体》——从零开始的智能体原理与实践教程
59.5K StarsLlm App
Ready-to-run cloud templates for RAG, AI pipelines, and enterprise search with live data. 🐳Docker-friendly.⚡Always in sync with Sharepoint, Google Drive, S3, Kafka, PostgreSQL, real-time data APIs, and more.
59.3K StarsFlowise
Build AI Agents, Visually
53.6K StarsReview then install
Install targets
Codex install prompt
Install the "Llm Universe" agent skill from https://github.com/datawhalechina/llm-universe. Read its SKILL.md or equivalent instructions first, install only the files needed for this workspace, and summarize any required setup before using it. Skill purpose: 本项目是一个面向小白开发者的大模型应用开发教程，在线阅读地址：https://datawhalechina.github.io/llm-universe/ After the install attempt, report the result to https://www.openagentskill.com/api/agent/outcome with POST JSON {"event_id":"install_<unique-id>","skill_slug":"datawhalechina-llm-universe","task":"Install Llm Universe","agent":"codex","outcome":"success","install_used":true}. Replace event_id with a unique value and outcome with success or failed. Report success only after the skill is installed and a minimal verification passes.Supply asset profile
CSV, SQL, notebooks, dashboards, data pipelines, BI, ETL, and spreadsheet analysis.
Scenario
RAG and knowledge
I need my agent to build a RAG workflow over documents and retrieve reliable context.
Agent fit
Claude Code + LangChain + CLI
Codex, Claude Code, Cursor, CLI, or custom agents.
Install
Ready
npx skills add datawhalechina/llm-universe
Maintenance
stable
6mo since push
Risk
Needs review
License is unclear
GitHub quality
13K
95/100 Quality · 84/100 Trust
Coverage tags
Review notes
License is unclear · Financial research output is not financial advice; require human review before any live investment decision
Agent adoption scorecard
These scores combine public repository metadata, OpenAgentSkill review signals, maintenance freshness, and install readiness. They are a shortlist signal, not a replacement for human review.
Quality
ExcellentHigh-confidence pick with strong adoption and healthy maintenance signals.
Trust
Review then installGood shortlist signal, but the agent should review audit notes, install policy, and outcome evidence before running it.
Audit
Needs reviewA machine-readable review of install readiness, security metadata, maintenance, and adoption risk.
OpenAgentSkill Trust Score v5
Use as the primary candidate after human or sandbox review.
Stars
13K GitHub stars
Repo activity
13K stars, 1.4K forks
Maintenance
6mo since push
License
Unknown
Install
npx skills add datawhalechina/llm-universe
Agent-readable metadata
Use this block or the embedded JSON to decide whether an agent should install this skill, choose an alternative, or ask for human review first.
Suited tasks
Suited agents
Install decision
Trust and risk
Outcome loop
Install command
npx skills add datawhalechina/llm-universeDo not use when
Agent safety v2
Usable candidate, but the agent should surface permission and audit notes before installation.
Require human approval before installing into a real workspace.
medium
Skill likely fetches remote pages, APIs, repositories, or external services.
medium
Skill may read or write project files, documents, generated artifacts, or local workspace state.
Agent resolve plan
The Resolve API returns the selected skill, alternatives, safety policy, audit notes, install target, and copy-paste prompt an agent can follow without scraping this page.
Open JSON
/api/agent/resolve?task=Use%20Llm%20Universe%20for%20an%20agent%20workflow&agent=codex&max_risk=medium
Resolve text
/api/agent/resolve?task=Use%20Llm%20Universe%20for%20an%20agent%20workflow&agent=codex&max_risk=medium&format=text
Install handoff
/api/skills/datawhalechina-llm-universe/install
Agent should check
Copy prompt
Task: Use Llm Universe in this workspace.
Resolve first: https://www.openagentskill.com/api/agent/resolve?task=Use%20Llm%20Universe%20for%20an%20agent%20workflow&agent=codex&max_risk=medium
Review install handoff: https://www.openagentskill.com/api/skills/datawhalechina-llm-universe/install
Install command: npx skills add datawhalechina/llm-universe
Before running it, summarize audit warnings, required permissions, and the fallback skill if install is risky.Agent handoff
Use the public install endpoint to fetch the command, safety checklist, target prompts, and canonical links for this skill.
Install handoff
/api/skills/datawhalechina-llm-universe/install
LLM text format
/api/skills/datawhalechina-llm-universe/install?format=text
Find alternatives
/api/skills/search?q=Llm%20Universe&limit=3
Agent prompt
Use Llm Universe for this task. Review https://www.openagentskill.com/api/skills/datawhalechina-llm-universe/install, then install with: npx skills add datawhalechina/llm-universeRegistry metadata
This page exposes the same decision, trust, audit, use-case, and install signals through the Registry API, so agents can rank this skill without scraping the UI.
Manifest
/api/registry/manifest/datawhalechina-llm-universe
LLM text
/api/registry/manifest/datawhalechina-llm-universe?format=text
Install alias
/api/registry/install/datawhalechina-llm-universe
Recommend
/api/registry/recommend?task=Use%20Llm%20Universe%20in%20an%20agent%20workflow&limit=3
Agent fit
RAG and knowledge
Use-case tags
Platforms
Jupyter Notebook, RAG, Claude Code, LangChain
Audit report
A machine-readable review of install readiness, security metadata, maintenance, and adoption risk.
Agent decision cockpit
Use this as a leading candidate, then validate the README and install path in your own agent stack.
Role in stack
Primary pick
Primary fit
RAG and knowledge
Trust label
Production-ready
Install path
Command ready
Use when
Evidence
review first
Implementation path
Trust profile
Good shortlist signal, but the agent should review audit notes, install policy, and outcome evidence before running it.
GitHub adoption
PASS13K GitHub stars
Stars/forks activity
PASS13K stars, 1.4K forks; issue activity unavailable in current metadata
Recent maintenance
INFO6mo since push
License clarity
CHECKUnknown
Good signals
Review before install
Recommended action
Use as the primary candidate after human or sandbox review.
Quality profile
High-confidence pick with strong adoption and healthy maintenance signals.
Workflow fit
Search private knowledge
I need my agent to build a RAG workflow over documents and retrieve reliable context.
Build and ship code
I need a coding agent that can understand a repository, edit code, and review pull requests.
Automate repeated work
I need my agent to automate a repeated workflow across tools and files.
Workflow fit
Ingest, retrieve, and cite
A workflow for document-heavy agents that ingest files, create searchable knowledge, retrieve relevant context, and answer with grounded sources.
Turn skills into distribution
A workflow for turning newly indexed skills into SEO briefs, social drafts, comparison pages, and reusable publishing workflows.
Inspect, patch, and verify code
A workflow for software agents that inspect repositories, review pull requests, generate tests, and turn findings into shippable patches.
Alternative shortlist
Similar skills that may fit this task.
100+ AI Agent & RAG apps you can actually run — clone, customize, ship.
📚 《从零开始构建智能体》——从零开始的智能体原理与实践教程
Ready-to-run cloud templates for RAG, AI pipelines, and enterprise search with live data. 🐳Docker-friendly.⚡Always in sync with Sharepoint, Google Drive, S3, Kafka, PostgreSQL, real-time data APIs, and more.
Build AI Agents, Visually
本项目是一个面向小白开发者的大模型应用开发教程，在线阅读地址：https://datawhalechina.github.io/llm-universe/
Imported by the skill-only GitHub discovery pipeline because it matches agent skill, automation, domain workflow, RAG, document-processing, data, finance, security, or developer-tool signals. Protocol-server projects are excluded from automated imports.
Frameworks & tools
Decision snapshot
13,412 GitHub stars
Audit
Install and adoption review
Agent-proven evidence
Outcome reports after resolve, review, install, and one narrow run.
No agent outcome data yet. The first agent run can report success, setup needs, risk blocks, failure, or not-relevant through /api/agent/outcome.
Install
Free and open source. Review the report before installing into production agents.
Growth loop
Scenario-led draft for Llm Universe, ready for a manual X post.
A practical pick for source-backed research: Llm Universe: 本项目是一个面向小白开发者的大模型应用开发教程，在线阅读地址：https://datawhalechina.github.io/llm-universe/ 13.4K stars https://www.openagentskill.com/skills/datawhalechina-llm-universe?ref=x
Listing + install path for Llm Universe: https://www.openagentskill.com/skills/datawhalechina-llm-universe?ref=x Install: npx skills add datawhalechina/llm-universe
Listing source
This listing was indexed from public sources and is not marked official until a maintainer claim is approved.
Attribution links to the public repository or creator profile. Creators can claim the listing to update ownership signals.
Claim this skillOwner claim
This Community indexed listing is attributed to datawhalechina but is not marked official yet. Claim it to add a verified owner signal and make future launch, install, and audit updates easier to trust.
Creator backlink kit
Show the canonical listing, current trust and audit signals, and real Agent-Proven evidence where developers evaluate the repository.
[](https://www.openagentskill.com/skills/datawhalechina-llm-universe?ref=github&utm_source=github&utm_medium=referral&utm_campaign=creator_badge)
[](https://www.openagentskill.com/skills/datawhalechina-llm-universe?ref=github&utm_source=github&utm_medium=referral&utm_campaign=creator_badge)
[](https://www.openagentskill.com/skills/datawhalechina-llm-universe/audit)
[](https://www.openagentskill.com/skills/datawhalechina-llm-universe?ref=github&utm_source=github&utm_medium=referral&utm_campaign=creator_badge)datawhalechina✓
@datawhalechina
Share whether this skill looks useful for your agent workflow. Aggregated feedback improves rankings over time.
Review then install
Awesome Llm Apps
100+ AI Agent & RAG apps you can actually run — clone, customize, ship.
114.5K StarsHello Agents
📚 《从零开始构建智能体》——从零开始的智能体原理与实践教程
59.5K StarsLlm App
Ready-to-run cloud templates for RAG, AI pipelines, and enterprise search with live data. 🐳Docker-friendly.⚡Always in sync with Sharepoint, Google Drive, S3, Kafka, PostgreSQL, real-time data APIs, and more.
59.3K StarsFlowise
Build AI Agents, Visually
53.6K StarsReview then install
Install targets
Codex install prompt
Install the "Llm Universe" agent skill from https://github.com/datawhalechina/llm-universe. Read its SKILL.md or equivalent instructions first, install only the files needed for this workspace, and summarize any required setup before using it. Skill purpose: 本项目是一个面向小白开发者的大模型应用开发教程，在线阅读地址：https://datawhalechina.github.io/llm-universe/ After the install attempt, report the result to https://www.openagentskill.com/api/agent/outcome with POST JSON {"event_id":"install_<unique-id>","skill_slug":"datawhalechina-llm-universe","task":"Install Llm Universe","agent":"codex","outcome":"success","install_used":true}. Replace event_id with a unique value and outcome with success or failed. Report success only after the skill is installed and a minimal verification passes.Supply asset profile
CSV, SQL, notebooks, dashboards, data pipelines, BI, ETL, and spreadsheet analysis.
Scenario
RAG and knowledge
I need my agent to build a RAG workflow over documents and retrieve reliable context.
Agent fit
Claude Code + LangChain + CLI
Codex, Claude Code, Cursor, CLI, or custom agents.
Install
Ready
npx skills add datawhalechina/llm-universe
Maintenance
stable
6mo since push
Risk
Needs review
License is unclear
GitHub quality
13K
95/100 Quality · 84/100 Trust
Coverage tags
Review notes
License is unclear · Financial research output is not financial advice; require human review before any live investment decision
Agent adoption scorecard
These scores combine public repository metadata, OpenAgentSkill review signals, maintenance freshness, and install readiness. They are a shortlist signal, not a replacement for human review.
Quality
ExcellentHigh-confidence pick with strong adoption and healthy maintenance signals.
Trust
Review then installGood shortlist signal, but the agent should review audit notes, install policy, and outcome evidence before running it.
Audit
Needs reviewA machine-readable review of install readiness, security metadata, maintenance, and adoption risk.
OpenAgentSkill Trust Score v5
Use as the primary candidate after human or sandbox review.
Stars
13K GitHub stars
Repo activity
13K stars, 1.4K forks
Maintenance
6mo since push
License
Unknown
Install
npx skills add datawhalechina/llm-universe
Agent-readable metadata
Use this block or the embedded JSON to decide whether an agent should install this skill, choose an alternative, or ask for human review first.
Suited tasks
Suited agents
Install decision
Trust and risk
Outcome loop
Install command
npx skills add datawhalechina/llm-universeDo not use when
Agent safety v2
Usable candidate, but the agent should surface permission and audit notes before installation.
Require human approval before installing into a real workspace.
medium
Skill likely fetches remote pages, APIs, repositories, or external services.
medium
Skill may read or write project files, documents, generated artifacts, or local workspace state.
Agent resolve plan
The Resolve API returns the selected skill, alternatives, safety policy, audit notes, install target, and copy-paste prompt an agent can follow without scraping this page.
Open JSON
/api/agent/resolve?task=Use%20Llm%20Universe%20for%20an%20agent%20workflow&agent=codex&max_risk=medium
Resolve text
/api/agent/resolve?task=Use%20Llm%20Universe%20for%20an%20agent%20workflow&agent=codex&max_risk=medium&format=text
Install handoff
/api/skills/datawhalechina-llm-universe/install
Agent should check
Copy prompt
Task: Use Llm Universe in this workspace.
Resolve first: https://www.openagentskill.com/api/agent/resolve?task=Use%20Llm%20Universe%20for%20an%20agent%20workflow&agent=codex&max_risk=medium
Review install handoff: https://www.openagentskill.com/api/skills/datawhalechina-llm-universe/install
Install command: npx skills add datawhalechina/llm-universe
Before running it, summarize audit warnings, required permissions, and the fallback skill if install is risky.Agent handoff
Use the public install endpoint to fetch the command, safety checklist, target prompts, and canonical links for this skill.
Install handoff
/api/skills/datawhalechina-llm-universe/install
LLM text format
/api/skills/datawhalechina-llm-universe/install?format=text
Find alternatives
/api/skills/search?q=Llm%20Universe&limit=3
Agent prompt
Use Llm Universe for this task. Review https://www.openagentskill.com/api/skills/datawhalechina-llm-universe/install, then install with: npx skills add datawhalechina/llm-universeRegistry metadata
This page exposes the same decision, trust, audit, use-case, and install signals through the Registry API, so agents can rank this skill without scraping the UI.
Manifest
/api/registry/manifest/datawhalechina-llm-universe
LLM text
/api/registry/manifest/datawhalechina-llm-universe?format=text
Install alias
/api/registry/install/datawhalechina-llm-universe
Recommend
/api/registry/recommend?task=Use%20Llm%20Universe%20in%20an%20agent%20workflow&limit=3
Agent fit
RAG and knowledge
Use-case tags
Platforms
Jupyter Notebook, RAG, Claude Code, LangChain
Audit report
A machine-readable review of install readiness, security metadata, maintenance, and adoption risk.
Agent decision cockpit
Use this as a leading candidate, then validate the README and install path in your own agent stack.
Role in stack
Primary pick
Primary fit
RAG and knowledge
Trust label
Production-ready
Install path
Command ready
Use when
Evidence
review first
Implementation path
Trust profile
Good shortlist signal, but the agent should review audit notes, install policy, and outcome evidence before running it.
GitHub adoption
PASS13K GitHub stars
Stars/forks activity
PASS13K stars, 1.4K forks; issue activity unavailable in current metadata
Recent maintenance
INFO6mo since push
License clarity
CHECKUnknown
Good signals
Review before install
Recommended action
Use as the primary candidate after human or sandbox review.
Quality profile
High-confidence pick with strong adoption and healthy maintenance signals.
Workflow fit
Search private knowledge
I need my agent to build a RAG workflow over documents and retrieve reliable context.
Build and ship code
I need a coding agent that can understand a repository, edit code, and review pull requests.
Automate repeated work
I need my agent to automate a repeated workflow across tools and files.
Workflow fit
Ingest, retrieve, and cite
A workflow for document-heavy agents that ingest files, create searchable knowledge, retrieve relevant context, and answer with grounded sources.
Turn skills into distribution
A workflow for turning newly indexed skills into SEO briefs, social drafts, comparison pages, and reusable publishing workflows.
Inspect, patch, and verify code
A workflow for software agents that inspect repositories, review pull requests, generate tests, and turn findings into shippable patches.
Alternative shortlist
Similar skills that may fit this task.
100+ AI Agent & RAG apps you can actually run — clone, customize, ship.
📚 《从零开始构建智能体》——从零开始的智能体原理与实践教程
Ready-to-run cloud templates for RAG, AI pipelines, and enterprise search with live data. 🐳Docker-friendly.⚡Always in sync with Sharepoint, Google Drive, S3, Kafka, PostgreSQL, real-time data APIs, and more.
Build AI Agents, Visually
本项目是一个面向小白开发者的大模型应用开发教程，在线阅读地址：https://datawhalechina.github.io/llm-universe/
Imported by the skill-only GitHub discovery pipeline because it matches agent skill, automation, domain workflow, RAG, document-processing, data, finance, security, or developer-tool signals. Protocol-server projects are excluded from automated imports.
Frameworks & tools
Decision snapshot
13,412 GitHub stars
Audit
Install and adoption review
Agent-proven evidence
Outcome reports after resolve, review, install, and one narrow run.
No agent outcome data yet. The first agent run can report success, setup needs, risk blocks, failure, or not-relevant through /api/agent/outcome.
Install
Free and open source. Review the report before installing into production agents.
Growth loop
Scenario-led draft for Llm Universe, ready for a manual X post.
A practical pick for source-backed research: Llm Universe: 本项目是一个面向小白开发者的大模型应用开发教程，在线阅读地址：https://datawhalechina.github.io/llm-universe/ 13.4K stars https://www.openagentskill.com/skills/datawhalechina-llm-universe?ref=x
Listing + install path for Llm Universe: https://www.openagentskill.com/skills/datawhalechina-llm-universe?ref=x Install: npx skills add datawhalechina/llm-universe
Listing source
This listing was indexed from public sources and is not marked official until a maintainer claim is approved.
Attribution links to the public repository or creator profile. Creators can claim the listing to update ownership signals.
Claim this skillOwner claim
This Community indexed listing is attributed to datawhalechina but is not marked official yet. Claim it to add a verified owner signal and make future launch, install, and audit updates easier to trust.
Creator backlink kit
Show the canonical listing, current trust and audit signals, and real Agent-Proven evidence where developers evaluate the repository.
[](https://www.openagentskill.com/skills/datawhalechina-llm-universe?ref=github&utm_source=github&utm_medium=referral&utm_campaign=creator_badge)
[](https://www.openagentskill.com/skills/datawhalechina-llm-universe?ref=github&utm_source=github&utm_medium=referral&utm_campaign=creator_badge)
[](https://www.openagentskill.com/skills/datawhalechina-llm-universe/audit)
[](https://www.openagentskill.com/skills/datawhalechina-llm-universe?ref=github&utm_source=github&utm_medium=referral&utm_campaign=creator_badge)datawhalechina✓
@datawhalechina
Share whether this skill looks useful for your agent workflow. Aggregated feedback improves rankings over time.
Review then install
Awesome Llm Apps
100+ AI Agent & RAG apps you can actually run — clone, customize, ship.
114.5K StarsHello Agents
📚 《从零开始构建智能体》——从零开始的智能体原理与实践教程
59.5K StarsLlm App
Ready-to-run cloud templates for RAG, AI pipelines, and enterprise search with live data. 🐳Docker-friendly.⚡Always in sync with Sharepoint, Google Drive, S3, Kafka, PostgreSQL, real-time data APIs, and more.
59.3K StarsFlowise
Build AI Agents, Visually
53.6K StarsReview then install
Install targets
Codex install prompt
Install the "Llm Universe" agent skill from https://github.com/datawhalechina/llm-universe. Read its SKILL.md or equivalent instructions first, install only the files needed for this workspace, and summarize any required setup before using it. Skill purpose: 本项目是一个面向小白开发者的大模型应用开发教程，在线阅读地址：https://datawhalechina.github.io/llm-universe/ After the install attempt, report the result to https://www.openagentskill.com/api/agent/outcome with POST JSON {"event_id":"install_<unique-id>","skill_slug":"datawhalechina-llm-universe","task":"Install Llm Universe","agent":"codex","outcome":"success","install_used":true}. Replace event_id with a unique value and outcome with success or failed. Report success only after the skill is installed and a minimal verification passes.Supply asset profile
CSV, SQL, notebooks, dashboards, data pipelines, BI, ETL, and spreadsheet analysis.
Scenario
RAG and knowledge
I need my agent to build a RAG workflow over documents and retrieve reliable context.
Agent fit
Claude Code + LangChain + CLI
Codex, Claude Code, Cursor, CLI, or custom agents.
Install
Ready
npx skills add datawhalechina/llm-universe
Maintenance
stable
6mo since push
Risk
Needs review
License is unclear
GitHub quality
13K
95/100 Quality · 84/100 Trust
Coverage tags
Review notes
License is unclear · Financial research output is not financial advice; require human review before any live investment decision
Agent adoption scorecard
These scores combine public repository metadata, OpenAgentSkill review signals, maintenance freshness, and install readiness. They are a shortlist signal, not a replacement for human review.
Quality
ExcellentHigh-confidence pick with strong adoption and healthy maintenance signals.
Trust
Review then installGood shortlist signal, but the agent should review audit notes, install policy, and outcome evidence before running it.
Audit
Needs reviewA machine-readable review of install readiness, security metadata, maintenance, and adoption risk.
OpenAgentSkill Trust Score v5
Use as the primary candidate after human or sandbox review.
Stars
13K GitHub stars
Repo activity
13K stars, 1.4K forks
Maintenance
6mo since push
License
Unknown
Install
npx skills add datawhalechina/llm-universe
Agent-readable metadata
Use this block or the embedded JSON to decide whether an agent should install this skill, choose an alternative, or ask for human review first.
Suited tasks
Suited agents
Install decision
Trust and risk
Outcome loop
Install command
npx skills add datawhalechina/llm-universeDo not use when
Agent safety v2
Usable candidate, but the agent should surface permission and audit notes before installation.
Require human approval before installing into a real workspace.
medium
Skill likely fetches remote pages, APIs, repositories, or external services.
medium
Skill may read or write project files, documents, generated artifacts, or local workspace state.
Agent resolve plan
The Resolve API returns the selected skill, alternatives, safety policy, audit notes, install target, and copy-paste prompt an agent can follow without scraping this page.
Open JSON
/api/agent/resolve?task=Use%20Llm%20Universe%20for%20an%20agent%20workflow&agent=codex&max_risk=medium
Resolve text
/api/agent/resolve?task=Use%20Llm%20Universe%20for%20an%20agent%20workflow&agent=codex&max_risk=medium&format=text
Install handoff
/api/skills/datawhalechina-llm-universe/install
Agent should check
Copy prompt
Task: Use Llm Universe in this workspace.
Resolve first: https://www.openagentskill.com/api/agent/resolve?task=Use%20Llm%20Universe%20for%20an%20agent%20workflow&agent=codex&max_risk=medium
Review install handoff: https://www.openagentskill.com/api/skills/datawhalechina-llm-universe/install
Install command: npx skills add datawhalechina/llm-universe
Before running it, summarize audit warnings, required permissions, and the fallback skill if install is risky.Agent handoff
Use the public install endpoint to fetch the command, safety checklist, target prompts, and canonical links for this skill.
Install handoff
/api/skills/datawhalechina-llm-universe/install
LLM text format
/api/skills/datawhalechina-llm-universe/install?format=text
Find alternatives
/api/skills/search?q=Llm%20Universe&limit=3
Agent prompt
Use Llm Universe for this task. Review https://www.openagentskill.com/api/skills/datawhalechina-llm-universe/install, then install with: npx skills add datawhalechina/llm-universeRegistry metadata
This page exposes the same decision, trust, audit, use-case, and install signals through the Registry API, so agents can rank this skill without scraping the UI.
Manifest
/api/registry/manifest/datawhalechina-llm-universe
LLM text
/api/registry/manifest/datawhalechina-llm-universe?format=text
Install alias
/api/registry/install/datawhalechina-llm-universe
Recommend
/api/registry/recommend?task=Use%20Llm%20Universe%20in%20an%20agent%20workflow&limit=3
Agent fit
RAG and knowledge
Use-case tags
Platforms
Jupyter Notebook, RAG, Claude Code, LangChain
Audit report
A machine-readable review of install readiness, security metadata, maintenance, and adoption risk.
Agent decision cockpit
Use this as a leading candidate, then validate the README and install path in your own agent stack.
Role in stack
Primary pick
Primary fit
RAG and knowledge
Trust label
Production-ready
Install path
Command ready
Use when
Evidence
review first
Implementation path
Trust profile
Good shortlist signal, but the agent should review audit notes, install policy, and outcome evidence before running it.
GitHub adoption
PASS13K GitHub stars
Stars/forks activity
PASS13K stars, 1.4K forks; issue activity unavailable in current metadata
Recent maintenance
INFO6mo since push
License clarity
CHECKUnknown
Good signals
Review before install
Recommended action
Use as the primary candidate after human or sandbox review.
Quality profile
High-confidence pick with strong adoption and healthy maintenance signals.
Workflow fit
Search private knowledge
I need my agent to build a RAG workflow over documents and retrieve reliable context.
Build and ship code
I need a coding agent that can understand a repository, edit code, and review pull requests.
Automate repeated work
I need my agent to automate a repeated workflow across tools and files.
Workflow fit
Ingest, retrieve, and cite
A workflow for document-heavy agents that ingest files, create searchable knowledge, retrieve relevant context, and answer with grounded sources.
Turn skills into distribution
A workflow for turning newly indexed skills into SEO briefs, social drafts, comparison pages, and reusable publishing workflows.
Inspect, patch, and verify code
A workflow for software agents that inspect repositories, review pull requests, generate tests, and turn findings into shippable patches.
Alternative shortlist
Similar skills that may fit this task.
100+ AI Agent & RAG apps you can actually run — clone, customize, ship.
📚 《从零开始构建智能体》——从零开始的智能体原理与实践教程
Ready-to-run cloud templates for RAG, AI pipelines, and enterprise search with live data. 🐳Docker-friendly.⚡Always in sync with Sharepoint, Google Drive, S3, Kafka, PostgreSQL, real-time data APIs, and more.
Build AI Agents, Visually
本项目是一个面向小白开发者的大模型应用开发教程，在线阅读地址：https://datawhalechina.github.io/llm-universe/
Imported by the skill-only GitHub discovery pipeline because it matches agent skill, automation, domain workflow, RAG, document-processing, data, finance, security, or developer-tool signals. Protocol-server projects are excluded from automated imports.
Frameworks & tools
Decision snapshot
13,412 GitHub stars
Audit
Install and adoption review
Agent-proven evidence
Outcome reports after resolve, review, install, and one narrow run.
No agent outcome data yet. The first agent run can report success, setup needs, risk blocks, failure, or not-relevant through /api/agent/outcome.
Install
Free and open source. Review the report before installing into production agents.
Growth loop
Scenario-led draft for Llm Universe, ready for a manual X post.
A practical pick for source-backed research: Llm Universe: 本项目是一个面向小白开发者的大模型应用开发教程，在线阅读地址：https://datawhalechina.github.io/llm-universe/ 13.4K stars https://www.openagentskill.com/skills/datawhalechina-llm-universe?ref=x
Listing + install path for Llm Universe: https://www.openagentskill.com/skills/datawhalechina-llm-universe?ref=x Install: npx skills add datawhalechina/llm-universe
Listing source
This listing was indexed from public sources and is not marked official until a maintainer claim is approved.
Attribution links to the public repository or creator profile. Creators can claim the listing to update ownership signals.
Claim this skillOwner claim
This Community indexed listing is attributed to datawhalechina but is not marked official yet. Claim it to add a verified owner signal and make future launch, install, and audit updates easier to trust.
Creator backlink kit
Show the canonical listing, current trust and audit signals, and real Agent-Proven evidence where developers evaluate the repository.
[](https://www.openagentskill.com/skills/datawhalechina-llm-universe?ref=github&utm_source=github&utm_medium=referral&utm_campaign=creator_badge)
[](https://www.openagentskill.com/skills/datawhalechina-llm-universe?ref=github&utm_source=github&utm_medium=referral&utm_campaign=creator_badge)
[](https://www.openagentskill.com/skills/datawhalechina-llm-universe/audit)
[](https://www.openagentskill.com/skills/datawhalechina-llm-universe?ref=github&utm_source=github&utm_medium=referral&utm_campaign=creator_badge)datawhalechina✓
@datawhalechina
Share whether this skill looks useful for your agent workflow. Aggregated feedback improves rankings over time.
Review then install
Awesome Llm Apps
100+ AI Agent & RAG apps you can actually run — clone, customize, ship.
114.5K StarsHello Agents
📚 《从零开始构建智能体》——从零开始的智能体原理与实践教程
59.5K StarsLlm App
Ready-to-run cloud templates for RAG, AI pipelines, and enterprise search with live data. 🐳Docker-friendly.⚡Always in sync with Sharepoint, Google Drive, S3, Kafka, PostgreSQL, real-time data APIs, and more.
59.3K StarsFlowise
Build AI Agents, Visually
53.6K Starsstandard package or runtime install path
Permission surface
filesystem or document access
Agent outcomes
No agent outcome data yet
Docs
Usable metadata, review docs
Risk summary
Install readiness
standard package or runtime install path
Permission surface
filesystem or document access
Agent outcomes
No agent outcome data yet
Docs
Usable metadata, review docs
Risk summary
Install readiness
standard package or runtime install path
Permission surface
filesystem or document access
Agent outcomes
No agent outcome data yet
Docs
Usable metadata, review docs
Risk summary
Install readiness
standard package or runtime install path
Permission surface
filesystem or document access
Agent outcomes
No agent outcome data yet
Docs
Usable metadata, review docs
Risk summary
Install readiness