mdes-ollama
CommunityAuto-test and fallback for AI models
System Documentation
What problem does it solve?
The mdes-ollama skill solves the problem of unreliable AI model availability by automatically testing models on the MDES Ollama endpoint and selecting a working option with safe fallbacks.
Core Features & Use Cases
- Central Model Orchestration: Runs a full health-check and routing flow so other skills can reliably obtain a working model.
- Automatic Fallback Chain: Falls back from mdes.ollama models to codex, GPT Pro, and GitHub Copilot when Ollama models fail.
- Token Usage Tracking & Guardrails: Monitors input/output tokens, computes usage %, and blocks models when usage exceeds critical thresholds.
- Auto-Dev Loop Support: Enables automated testing and periodic health checks to keep the model pool ready for development workflows.
Use case example: When a multi-agent workflow starts (e.g., /nemotron or /gang), mdes-ollama ensures the best available model is selected based on success rate and token usage, then hands off execution to the chosen runtime.
Quick Start
Ask an agent to run: start model orchestration and pick the best working MDES Ollama model with fallback by issuing the command "/mdes-ollama".
Dependency Matrix
Required Modules
None requiredComponents
Standard package💻 Claude Code Installation
Recommended: Let Claude install automatically. Simply copy and paste the text below to Claude Code.
Please help me install this Skill: Name: mdes-ollama Download link: https://github.com/tinner-deinno/innova-skills-lib/archive/main.zip#mdes-ollama Please download this .zip file, extract it, and install it in the .claude/skills/ directory.
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