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@04110d9
by microsoftmicrosoft/skills3.1k stars
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Build, deploy, evaluate, optimize, fine-tune, and manage Microsoft Foundry agents, models, and resources end to end. USE FOR: foundry, azd ai agent, azd provision/deploy, hosted agent scaffold/develop/run/deploy/troubleshoot, prompt agent create, create agent, update agent, add tool to agent, invoke agent, agent.yaml, agent insights, pull agent insights, evaluate agent, batch eval, continuous eval, continuous monitoring, agent CI/CD, optimize prompt, improve prompt, prompt optimizer, optimize agent instructions, Agent Optimizer scaffold, dataset curation from traces, deploy model, model fine-tuning (SFT/DPO/RFT), Foundry project, RBAC, role assignment, permissions, quota, capacity, region, deployment failure, AI Services, create Foundry resource, knowledge index, customize deployment, onboard, availability, training-data, grader, distillation, large file upload. DO NOT USE FOR: Azure Functions, App Service, general Azure deploy (use azure-deploy), general Azure prep (use azure-prepare).

Use this Skill: https://skilld.dev/gh/microsoft/skills/microsoft-foundry

This session only. Nothing lands on disk.

foundry-agentcreatereferencestoolsprompt-agenttool-file-search.md

≈675 tokens on demand. Your agent reads this file only when SKILL.md points to it.

File Search Tool

Enables agents to search through uploaded files using semantic and keyword search from vector stores. Supports a wide range of file formats including PDF, Markdown, Word, and more.

⚠️ Important: Before creating an agent with file search, you must read the official documentation linked in the References section to understand prerequisites, supported file types, and vector store setup.

Prerequisites

  • A basic or standard agent environment
  • A vector store must be created before the agent — the file_search tool requires vector_store_ids
  • Files must be uploaded to the vector store before the agent can search them

Key Concepts

Concept Description
Vector Store A container that indexes uploaded files for semantic search. Must be created first.
vector_store_ids Required parameter on the file_search tool — references the vector store(s) to search.
File upload Files are uploaded to the project, then attached to a vector store for indexing.

Setup Workflow

1. Create a vector store (REST API: POST /vector_stores)
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2. (Optional) Upload files and attach to vector store
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3. Create agent with file_search tool referencing the vector_store_ids
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4. Agent can now search files in the vector store

⚠️ Warning: Creating an agent with file_search without providing vector_store_ids will fail with a 400 BadRequest error: required: Required properties ["vector_store_ids"] are not present.

REST API Notes

When creating vector stores via az rest:

Parameter Value
Endpoint https://<resource>.services.ai.azure.com/api/projects/<project>/vector_stores
API version v1
Auth resource https://ai.azure.com

Troubleshooting

Error Cause Fix
vector_store_ids not present Agent created without vector store Create a vector store first, then pass its ID
401 Unauthorized Wrong auth resource for REST API Use --resource "https://ai.azure.com" with az rest
Bad API version Using ARM-style API version Use api-version=v1 for the data-plane vector store API
No search results Vector store is empty Upload files to the vector store before querying

References

Source: SKILL.md on GitHub

2 warnings3d4 checks · Risk SAFE
  • Gen Agent Trust Hub3d

    This skill provides a comprehensive environment for managing the end-to-end lifecycle of AI agents, models, and infrastructure on Microsoft Foundry. It includes sub-skills for deployment, evaluation, fine-tuning, and troubleshooting. The skill utilizes dynamic code execution and shell command wrappers, which are used within the context of local development and cloud orchestration. All external resources and dependencies originate from trusted organizations and well-known services.

  • Socket3d

    2 alerts: gptSecurity, gptAnomaly

  • Snyk3d

    Risk: LOW · No issues

  • Runlayer7mo

    36/36 files flagged

Signed by skilld at 04110d9. This ties the file your Agent reads to that commit on GitHub. It does not review the instructions.

Last checked against GitHub yesterday.

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metadata
{
  "author": "Microsoft",
  "version": "1.2.26"
}

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