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SKILL verified Apache-2.0 Self-run

Run Models

skill-replicate-skills-run-models · by replicate

Run AI models on Replicate via predictions, webhooks, and streaming.

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Install

$ agentstack add skill-replicate-skills-run-models

✓ scanned · ✓ verified — works with Claude Code, Cursor, and more.

Security review

✓ Passed

No issues found. Passed automated security review. · v0.1.0 How review works →

  • Prompt-injection patterns
  • Secret / credential exfiltration
  • Dangerous shell & filesystem operations
  • Untrusted network calls
  • Known-malicious package signatures

What it can access

  • Network access No
  • Filesystem access No
  • Shell / process execution No
  • Environment & secrets No
  • Dynamic code execution No

From automated source analysis of v0.1.0. “Used” means the capability is present in the source — more access means more to trust, not that it’s unsafe.

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About

Docs

  • Reference:
  • OpenAPI schema:
  • MCP server:
  • Per-model docs: https://replicate.com/{owner}/{model}/llms.txt
  • Set Accept: text/markdown when requesting docs pages for Markdown responses.

Workflow

  1. Choose the right model - Search with the API or ask the user.
  2. Get model metadata - Fetch input and output schema via API.
  3. Create prediction - POST to /v1/predictions.
  4. Poll for results - GET prediction until status is "succeeded".
  5. Return output - Usually URLs to generated content.

Three ways to get output

  1. Create a prediction, store its id from the response, and poll until completion.
  2. Set a Prefer: wait header when creating a prediction for a blocking synchronous response. Only recommended for very fast models. Max 60 seconds.
  3. Set an HTTPS webhook URL when creating a prediction, and Replicate will POST to that URL when the prediction completes.

Guidelines

  • Use the POST /v1/predictions endpoint, as it supports both official and community models.
  • Every model has its own OpenAPI schema. Always fetch and check model schemas to make sure you're setting valid inputs. Even popular models change their schemas.
  • Validate input parameters against schema constraints (minimum, maximum, enum values). Don't generate values that violate them.
  • When unsure about a parameter value, use the model's default example or omit the optional parameter.
  • Don't set optional inputs unless you have a reason to. Stick to the required inputs and let the model's defaults do the work.
  • Use HTTPS URLs for file inputs whenever possible. You can also send base64-encoded files, but they should be avoided.
  • Fire off multiple predictions concurrently. Don't wait for one to finish before starting the next.
  • Output file URLs expire after 1 hour, so back them up if you need to keep them, using a service like Cloudflare R2.
  • Webhooks are a good mechanism for receiving and storing prediction output.

Predictions

  • A prediction goes through these states: starting -> processing -> succeeded / failed / canceled.
  • Official models use owner/name format. Community models require owner/name:version_id.
  • The POST /v1/predictions endpoint handles both.

Webhooks

  • Set webhook to an HTTPS URL when creating a prediction. Replicate POSTs the full prediction object when it completes.
  • Filter events with webhook_events_filter: start, output, logs, completed.
  • Validate webhook signatures using the Webhook-ID, Webhook-Timestamp, and Webhook-Signature headers. Get the signing secret from GET /v1/webhooks/default/secret.

Prediction lifetime

  • Set lifetime to auto-cancel predictions that run too long (e.g. 30s, 5m, 1h). Measured from creation time.

Streaming

  • Language models that support streaming include a stream URL in the response. Use SSE to receive incremental output.

File handling

  • Prefer HTTPS URLs for file inputs. Output URLs from one prediction can be passed directly as file inputs to the next model.
  • Output file URLs expire after 1 hour. Download and store them immediately if you need to keep them.

Multi-model workflows

  • Chain models by passing output URLs as file inputs to the next model.
  • Start all independent predictions in parallel, then collect results.
  • Output URLs are valid for 1 hour, which is enough for pipeline steps.

Source & license

This open-source skill is cataloged on AgentStack and links to its original source — we do not rehost the code.

Install and usage instructions live in the source repository linked above.

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Versions

  • v0.1.0 Imported from the upstream source.