Search for assets in the Picsha AI platform using vector or standard keyword search. Note: If your agent instance is sandboxed to a specific user via environment variables, this search will ONLY return assets owned by that specific user. You are securely retrieving their contextual assets.

Retrieve detailed metadata and AI analysis results for a specific asset

Manually trigger AI re-analysis on an existing asset to detect faces, objects, etc.

Utilize Claude Sonnet via Amazon Bedrock to summarize documents on demand

Generate a dynamic delivery URL for an asset with transformation parameters (e.g. width, height, format, smart crop)

Upload a local file directly to the Picsha AI platform. This acts as a proxy, fetching a pre-signed S3 URL and executing the PUT request automatically. If your agent is running with user sandboxing, this file will automatically be securely bound to that user's identity. Note: Uploading immediately triggers the asynchronous 'picsha-ai-ingest' pipeline which will extract metadata, generate thumbnails, and run AI analysis (faces, tags, bedrcock summaries). Therefore, the returned asset will initially be in a 'pending' state. You should use the 'get_asset' tool a few seconds after uploading to retrieve the final AI-processed results.

List recently added assets in the Picsha platform. IMPORTANT: When replying to the user, ALWAYS format this as a clean Markdown table with columns for ID, Original Name, Status, and Date.

Update an asset's tags or custom metadata. Prefix a tag with a hyphen (e.g. '-discard') to remove it, or specify normally to add it.

Permanently delete an asset from the database, search indexes, and physical storage.

Approve or reject a moderated asset pending manual review.

Create a new Digital Asset Management (DAM) group/collection (folder) to organize assets.

Link a source/parent asset to a target/child asset (e.g. variations, derived formats, social crops) with a custom relationship description.

Ingest a public web asset directly into the Picsha AI platform by downloading and putting it through the ingestion pipeline.

Use this tool ONLY when you need to log a feature request, report a documentation gap, or escalate an issue to the engineering team. This will actually send an email to support@picsha.ai.