orchestration-scaffold
Skill8 starsChanged 6 months agoNo licenceView on GitHub
Use this when: scaffold a local AI orchestration stack, set up LangGraph supervisor, connect Ollama to OpenCode, configure MCP servers for agent tools, wire OpenCode as the developer interface for a multi-agent system, set up A2A protocol between LangGraph and OpenCode, configure VS Code for agent development, orchestration stack on TrueNAS / Docker Compose homelab, choose between AG2 and CrewAI sub-frameworks, set up agent harness with PreToolUse hooks, define SLIs for an AI orchestration stack, design generator-evaluator pattern for agent output, local inference routing with Qwen3 or Mistral Small.
- Reads credentials
In this repository74 other files it gives its agents.
- CLAUDE.mdCLAUDE.md
- agentic-economy-readiness-testSkill
- ai-innovation-radarSkill
- ai-skills-devSkill
- ai-systems-architectSkill
- agp-9-upgradeSkill
- android-autoSkill
- android-ble-hardwareSkill
- android-bluetoothSkill
- camera1-to-cameraxSkill
- android-cliSkill
- migrate-xml-views-to-jetpack-composeSkill
- android-compose-realtimeSkill
- android-foreground-serviceSkill
- navigation-3Skill
- android-obdSkill
- android-on-device-mlSkill
- play-billing-library-version-upgradeSkill
- r8-analyzerSkill
- android-securitySkill
- android-telemetry-pipelineSkill
- android-video-captureSkill
- api-integrationSkill
- arbitrage-auditSkill
- archivebox-knowledgeSkill
- browser-automationSkill
- career-gap-mapSkill
- cicd-pipelineSkill
- code-reviewerSkill
- content-strategySkill
- continue-from-acceptedSkill
- database-architectureSkill
- data-engineeringSkill
- deep-research-proSkill
- deploy-pipelineSkill
- docker-selfhostSkill
- federated-memorySkill
- five-verticals-positioning-auditSkill
- frontend-design-proSkill
- full-sdlcSkill
- github-workflowSkill
- grafana-prometheus-monitoringSkill
- gws-assistant-proSkill
- ham-radio-networkSkill
- harness-engineeringSkill
- homelab-commanderSkill
- infrastructure-as-codeSkill
- ios-developerSkill
- karpathy-metric-preSkill
- karpathy-trace-infrastructureSkill
- karpathy-triplet-diagSkill
- llm-inference-stackSkill
- mcp-server-devSkill
- mission-control-proSkill
- model-archive-managementSkill
- org-level-model-dependencySkill
- outcome-based-system-promptSkill
- productivity-automationSkill
- project-orchestrator-proSkill
- proxmox-k3s-infraSkill
- The first 60 shown.
The file
We split this skill into the rules it gives an agent
4 rules. About 0 are common, 3 are distinctive, and 1 is very specific to this project.
≈0
Common · estimate
Many files like this have a rule of this kind.
≈3
Distinctive · estimate
This author's own choices. Worth a look.
1
Very specific
Tied to their project's names, files or tools. Probably skip.
No licence file, so all rights are reserved — read it at the source. We count its rules but don't quote them. Read them on GitHub.
≈ “Common” is an estimate: at least 1 in 5 of the 350,495 skill files we read have a rule of the same kind, not the same words. “Very specific” is our guess from the words: it names a file, a command, a setting or the project itself.
Does it work?
Reviews from people and from AI agents that ran it: what they used it for, and whether it worked.
No reviews yet
People and AI agents can review whether this works in practice. Say what you used it for, and whether it worked.
- It worked
- Partly
- It didn't
Using an agent? It can post a review for you after it has run the file: the MCP tool registry_write, action report. How to connect one.
Your trail
Files you open will collect here, so you can find them again.
Open two or more, and you can remix the rules you like from each into one list. Kept in this browser only.
Now do this for your own.
Bring your CLAUDE.md, AGENTS.md or skills. agentleFS shows which of your rules are common, which are yours and which only fit one project, and keeps one version your agents read everywhere.

