Requirements
- Target platform
- OpenClaw
- Install method
- Manual import
- Extraction
- Extract archive
- Prerequisites
- OpenClaw
- Primary doc
- SKILL.md
Run multi-agent Dream Cascade (hierarchical 3-tier synthesis) or Dream Swarm (parallel multi-domain search) workflows via the dr.eamer.dev orchestration API....
Run multi-agent Dream Cascade (hierarchical 3-tier synthesis) or Dream Swarm (parallel multi-domain search) workflows via the dr.eamer.dev orchestration API....
Hand the extracted package to your coding agent with a concrete install brief instead of figuring it out manually.
I downloaded a skill package from Yavira. Read SKILL.md from the extracted folder and install it by following the included instructions. Tell me what you changed and call out any manual steps you could not complete.
I downloaded an updated skill package from Yavira. Read SKILL.md from the extracted folder, compare it with my current installation, and upgrade it while preserving any custom configuration unless the package docs explicitly say otherwise. Summarize what changed and any follow-up checks I should run.
Run multi-agent workflows through https://api.dr.eamer.dev.
export DREAMER_API_KEY=your_key_here
POST https://api.dr.eamer.dev/v1/orchestrate/swarm Body: { "query": "What are the most effective treatments for Type 2 diabetes?", "sources": ["pubmed", "semantic_scholar", "wikipedia"], "num_agents": 5 } Runs multiple agents simultaneously across data sources and synthesizes results.
POST https://api.dr.eamer.dev/v1/orchestrate/cascade Body: { "task": "Analyze the current state of quantum computing hardware", "num_agents": 8, "provider": "anthropic" } Three-tier workflow: Belter agents gather raw data โ Drummer agents synthesize domains โ Camina produces executive summary.
Both endpoints return: { "result": "Synthesized answer...", "sources": [...], "agent_count": 5, "duration_ms": 12450 }
Complex research questions requiring multiple perspectives Cross-domain synthesis that would take multiple sequential queries Long-horizon analysis where parallelism saves time
Simple single-source queries (use dreamer-data instead) You need fine-grained control over individual agent behavior Latency is critical (orchestration takes 10-60 seconds)
Code helpers, APIs, CLIs, browser automation, testing, and developer operations.
Largest current source with strong distribution and engagement signals.