DreamOmni2
This project is the official implementation of 'DreamOmni2: Multimodal Instruction-based Editing and Generation (CVPR2026 Highlight)''
Supply asset profile
Research and knowledge work
Deep research, source comparison, literature review, RAG, knowledge search, and reports.
Scenario
RAG and knowledge
I need my agent to build a RAG workflow over documents and retrieve reliable context.
Agent fit
Claude Code + CLI + Codex
Codex, Claude Code, Cursor, CLI, or custom agents.
Install
Ready
npx skills add JIA-Lab-research/DreamOmni2
Maintenance
active
2mo since push
Risk
Safe to try
No major risk signals from available metadata
GitHub quality
2.0K
98/100 quality · 93/100 trust
Coverage tags
Review notes
No major risk signals from available metadata
Agent adoption scorecard
Trust, audit, and install readiness at a glance
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
Production candidateStrong OpenAgentSkill Trust Score across adoption, recent maintenance, license clarity, documentation, dependency/runtime risk, install safety, permission surface, and install availability.
Audit
Safe to tryInstall readiness, security metadata, maintenance, and adoption risk.
Trust Score v3
Agent install candidate
Shortlist for production use, then run a normal repository and dependency review.
Stars
2.0K GitHub stars
Repo activity
2.0K stars, 175 forks
Maintenance
2mo since push
License
Apache-2.0
Install
npx skills add JIA-Lab-research/DreamOmni2
Install safety
standard package or runtime install path
Permission surface
filesystem or document access
Docs
Strong README/SKILL.md context
Risk summary
Low metadata risk
- No major trust warnings detected from available metadata
Install readiness
Install path available
- Install path is available
- Repository evidence is available
- License is declared
- 2mo since push
Agent-readable metadata
Machine-readable decision data for this skill.
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
- RAG and knowledge workflows
- Claude Code teams
- teams that value GitHub adoption signals
- Chunk documents
- Create embeddings
Suited agents
Trust and risk
- Trust score
- 93/100
- Risk level
- Safe to try
- Auto install
- allow
Do not use when
- teams that need a vendor-supported SLA
- high-compliance environments without internal security review
- No OpenAgentSkill engagement data yet
- No major trust warnings detected from available metadata
Agent safety v2
85/100 · Safe to install with normal review
Strong metadata, audit, install, and review signals. Suitable for agent shortlists after normal workspace review.
Allow agent install in a sandbox or low-risk workspace, then promote after one successful narrow task.
medium
Network access
Skill likely fetches remote pages, APIs, repositories, or external services.
medium
Filesystem access
Skill may read or write project files, documents, generated artifacts, or local workspace state.
Install targets
Install this skill in your agent workflow
Copy the registry command or an agent-specific install prompt for Codex, Claude Code, and Cursor.
OpenAgentSkill CLI
Use the registry command when your workflow supports the OpenAgentSkill installer.
$ npx skills add JIA-Lab-research/DreamOmni2Agent resolve plan
Let an agent verify fit before installing.
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.
Resolve JSON
/api/agent/resolve?task=Use%20DreamOmni2%20for%20an%20agent%20workflow&agent=codex&max_risk=medium
Resolve text
/api/agent/resolve?task=Use%20DreamOmni2%20for%20an%20agent%20workflow&agent=codex&max_risk=medium&format=text
Install handoff
/api/skills/jia-lab-research-dreamomni2/install
Agent should check
- Task fit and alternatives from Resolve API.
- Audit score, trust score, and safety policy warnings.
- Install target compatibility for Codex, Claude Code, Cursor, or CLI.
Copy prompt
Task: Use DreamOmni2 in this workspace.
Resolve first: https://www.openagentskill.com/api/agent/resolve?task=Use%20DreamOmni2%20for%20an%20agent%20workflow&agent=codex&max_risk=medium
Review install handoff: https://www.openagentskill.com/api/skills/jia-lab-research-dreamomni2/install
Install command: npx skills add JIA-Lab-research/DreamOmni2
Before running it, summarize audit warnings, required permissions, and the fallback skill if install is risky.Agent handoff
Give an agent the install path, not another directory page.
Use the public install endpoint to fetch the command, safety checklist, target prompts, and canonical links for this skill.
Install handoff
/api/skills/jia-lab-research-dreamomni2/install
LLM text format
/api/skills/jia-lab-research-dreamomni2/install?format=text
Find alternatives
/api/skills/search?q=DreamOmni2&limit=3
Agent prompt
Use DreamOmni2 for this task. Review https://www.openagentskill.com/api/skills/jia-lab-research-dreamomni2/install, then install with: npx skills add JIA-Lab-research/DreamOmni2Registry metadata
Agent-readable profile for automatic skill selection.
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/jia-lab-research-dreamomni2
LLM text
/api/registry/manifest/jia-lab-research-dreamomni2?format=text
Install alias
/api/registry/install/jia-lab-research-dreamomni2
Recommend
/api/registry/recommend?task=Use%20DreamOmni2%20in%20an%20agent%20workflow&limit=3
Agent fit
RAG and knowledge
Use-case tags
Platforms
Python, Image Generation, Claude Code
Audit report
Safe to try · 93/100
Review install readiness, maintenance, trust, quality, and metadata warnings before adding this skill to an agent workflow.
Agent decision cockpit
Primary pick for RAG and knowledge
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
- RAG and knowledge workflows
- Claude Code teams
- teams that value GitHub adoption signals
Evidence
- 2,027 GitHub stars
- recent repository activity
- install command or GitHub repo available
- 98/100 quality profile
Review first
- No OpenAgentSkill engagement data yet
Implementation path
- 1Install it in a sandbox agent and run one RAG and knowledge task end to end.
- 2Compare output quality, latency, and failure behavior against at least one alternative.
- 3Promote it into production only after reviewing repository permissions, license, and maintenance signals.
Trust profile
Production candidate
Strong OpenAgentSkill Trust Score across adoption, recent maintenance, license clarity, documentation, dependency/runtime risk, install safety, permission surface, and install availability.
GitHub adoption
PASS2.0K GitHub stars
Stars/forks activity
INFO2.0K stars, 175 forks; issue activity unavailable in current metadata
Recent maintenance
PASS2mo since push
License clarity
PASSApache-2.0
Good signals
- Manually verified listing
- AI review approved
- Install path is available
- Repository evidence is available
- Recently maintained repository
- Meaningful GitHub adoption signal
- Install command has no obvious high-risk pattern
Review before install
No major trust warnings detected from available metadata.
Recommended action
Shortlist for production use, then run a normal repository and dependency review.
Quality profile
Excellent candidate for agent workflows
High-confidence pick with strong adoption and healthy maintenance signals.
Workflow fit
Use this skill in these scenarios
Search private knowledge
RAG and knowledge
I need my agent to build a RAG workflow over documents and retrieve reliable context.
Manage repositories
GitHub automation
I need my agent to triage GitHub issues, review pull requests, and summarize repository changes.
Process rich media
Multimodal media
I need my agent to process images, video, or audio and extract useful information.
Stack fit
Add it to a complete workflow
Ingest, retrieve, and cite
RAG knowledge base
A stack for document-heavy agents that ingest files, create searchable knowledge, retrieve relevant context, and answer with grounded sources.
Turn skills into distribution
Content growth agent
A stack for turning newly indexed skills into SEO briefs, social drafts, comparison pages, and reusable publishing workflows.
Inspect, patch, and verify code
Coding review agent
A stack for software agents that inspect repositories, review pull requests, generate tests, and turn findings into shippable patches.
Alternative shortlist
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Overview
This project is the official implementation of 'DreamOmni2: Multimodal Instruction-based Editing and Generation (CVPR2026 Highlight)''
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.
Platform Compatibility
Technical Details
- Version
- 1.0.0
- License
- Apache-2.0
- Last Updated
- 6/16/2026
- Published
- 6/16/2026
Frameworks & Tools
Decision snapshot
Primary pick
2,027 GitHub stars
Audit Snapshot
Install and adoption review
- Security
- 89/100
- Maintenance
- 88/100
- Install
- 92/100
Growth loop
Share this skill
Scenario-led draft for DreamOmni2, with the OpenAgentSkill Update theme and canonical URL.
OpenAgentSkill Update Today: DreamOmni2 Use it when you want an agent to turn market noise into source-backed research, ranked candidates, an... 2.0K stars - media-automation Link: https://www.openagentskill.com/skills/jia-lab-research-dreamomni2?ref=x #AIAgents #OpenAgentSkill
Optional reply with install command
Link for DreamOmni2: https://www.openagentskill.com/skills/jia-lab-research-dreamomni2?ref=x Install: npx skills add JIA-Lab-research/DreamOmni2
Listing source
Community indexed
This listing was indexed from public sources and is not marked official until a maintainer claim is approved.
- Creator
- JIA-Lab-research
- Indexed by
- OpenAgentSkill community index
Attribution links to the public repository or creator profile. Creators can claim the listing to update ownership signals.
Claim this skillOwner claim
Claim this skill listing
This community indexed listing is attributed to JIA-Lab-research 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.
README badge
Add this badge to your GitHub README to show the listing, trust score, and install handoff.
[](https://www.openagentskill.com/skills/jia-lab-research-dreamomni2)Author
JIA-Lab-research✓
@jia-lab-research
Platform Fit
Health Signals
- GitHub stars
- 2.0K
- Quality score
- 62/100
- Last GitHub push
- Apr 11, 2026
- Framework hints
- 2
- OpenAgentSkill views
- 0
- Install copies
- 0
- Outbound clicks
- 0
Community Signal
Share whether this skill looks useful for your agent workflow. Aggregated feedback improves rankings over time.
Trust & Safety
Production candidate
- GitHub adoption2.0K GitHub starsPASS
- Stars/forks activity2.0K stars, 175 forks; issue activity unavailable in current metadataINFO
- Recent maintenance2mo since pushPASS
- License clarityApache-2.0PASS
- README/SKILL.md completenessMetadata includes enough usage and workflow contextPASS
- Dependency/runtime riskno major dependency risk hints in public metadataPASS
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