From replicate
Runs AI models on Replicate via predictions, webhooks, and streaming. Fetches model schemas, validates inputs, polls for results, and handles output URLs.
How this skill is triggered — by the user, by Claude, or both
Slash command
/replicate:run-modelsThe summary Claude sees in its skill listing — used to decide when to auto-load this skill
- Reference: <https://replicate.com/docs/llms.txt>
https://replicate.com/{owner}/{model}/llms.txtAccept: text/markdown when requesting docs pages for Markdown responses.Prefer: wait header when creating a prediction for a blocking synchronous response. Only recommended for very fast models. Max 60 seconds.POST /v1/predictions endpoint, as it supports both official and community models.minimum, maximum, enum values). Don't generate values that violate them.starting -> processing -> succeeded / failed / canceled.owner/name format. Community models require owner/name:version_id.POST /v1/predictions endpoint handles both.webhook to an HTTPS URL when creating a prediction. Replicate POSTs the full prediction object when it completes.webhook_events_filter: start, output, logs, completed.Webhook-ID, Webhook-Timestamp, and Webhook-Signature headers. Get the signing secret from GET /v1/webhooks/default/secret.lifetime to auto-cancel predictions that run too long (e.g. 30s, 5m, 1h). Measured from creation time.stream URL in the response. Use SSE to receive incremental output.npx claudepluginhub replicate/skills --plugin prompt-imagesAutomates Replicate AI model operations: run predictions, upload files, inspect model schemas, list versions, and manage prediction history via Composio MCP integration.
Packages and builds custom AI models with Cog for deployment on Replicate. Covers cog.yaml, predict.py, GPU/CUDA setup, and Docker image creation.
Generates JSON workflow files for chaining AI models together. Useful for building multi-step AI inference pipelines requiring model orchestration.