Compare models available through the HuggingFace router with chat-ui configuration, research missing models, and write short English descriptions of their architecture and capabilities. Add entries to both production and development configuration files and commit the changes.
Add descriptions for new models from the HuggingFace router to chat-ui configuration. Use when new models are released on the router and need descriptions added to prod.yaml and dev.yaml. Triggers on requests like "add new model descriptions", "update models from router", "sync models", or when explicitly invoking /add-model-descriptions.
Review the instructions the agent will receive before you install.
Add descriptions for new models available in the HuggingFace router to chat-ui's prod.yaml and dev.yaml.
Fetch models from router
WebFetch https://router.huggingface.co/v1/models
Extract all model IDs from the response.
Read current configuration
chart/env/prod.yamlMODELS JSON array in envVarsIdentify missing models Compare router models with prod.yaml. Missing = in router but not in prod.yaml.
Research each missing model For each missing model, search the web for its specifications:
Write descriptions Match existing style:
Examples:
"Flagship GLM MoE for coding, reasoning, and agentic tool use.""MoE agent model with multilingual coding and fast outputs.""Vision-language Qwen for documents, GUI agents, and visual reasoning.""Mobile agent for multilingual Android device automation."Update both files Add new models at the TOP of the MODELS array in:
chart/env/prod.yamlchart/env/dev.yamlFormat:
{ "id": "org/model-name", "description": "Description here." }
Commit changes
git add chart/env/prod.yaml chart/env/dev.yaml
git commit -m "feat: add descriptions for N new models from router"
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Create an Architecture Decision Record, a document for recording important design choices, with the next sequential number. It generates a Markdown template, registers the record in AgentDB, and links related decisions found through search.
Build a searchable index and relationship graph from ADRs, records of architectural decisions. Import two supported document formats, refresh existing metadata without duplicate relationships, and review summaries of statuses, missing references, and inconsistencies.
Rebuild the index of ADRs, records of architectural decisions, after files or relationship lines are deleted. It clears stored records and relationships, indexes the files still present, and checks that the final record count matches.
Review code changes against accepted Architecture Decision Records, documents that capture agreed design choices. Report violations, outdated references, compliant changes, and areas without ADR coverage, then suggest code fixes or a new decision record where appropriate.
Check saved architecture decision records (ADRs) for broken references, circular replacement relationships, and inconsistent statuses. Use the results to verify imported records or stop a CI check when selected integrity rules fail.
Coordinate multiple AI agents by adjusting their communication structure and task assignments as workloads change. The skill describes performance monitoring, switching coordination patterns, forecasting agent capacity, and validating changes with rollback when performance worsens.