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foundry-agent-sync

Create and synchronize prompt-based AI agents directly within Azure AI Foundry via REST API, from a local JSON manifest. Unlike scaffolding skills t…

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技能内容

Foundry Agent Sync

Overview

Create and synchronize prompt-based AI agents directly within Azure AI Foundry via the Agent Service REST API. This skill registers agents in the Foundry service itself — making them immediately available for invocation, evaluation, and management through the Foundry portal or API. Each agent is created or updated idempotently via a named POST call, using definitions from a local JSON manifest file.

> Key distinction: This skill creates agents inside AI Foundry (server-side). It does not scaffold local agent code or container images — for that, use the microsoft-foundry skill's create sub-skill.

Prerequisites

The user must have:

  1. An Azure AI Foundry project with a deployed model (e.g. gpt-5-4)
  2. Azure CLI (az) authenticated with access to the Foundry project
  3. The Azure AI User role (or higher) on the Foundry project resource

Collect these values before proceeding:

| Value | How to get it |

|---|---|

| Foundry project endpoint | Azure Portal → AI Foundry project → Overview → Endpoint, or az resource show |

| Subscription ID | az account show --query id -o tsv |

| Model deployment name | The model name deployed in the Foundry project (e.g. gpt-5-4) |

Manifest Format

The manifest is a JSON array where each entry defines one agent. Look for it at common paths: infra/foundry-agents.json, foundry-agents.json, or .foundry/agents.json. If none exists, scaffold one.

[
  {
    "useCaseId": "alert-triage",
    "description": "Short description of what this agent does.",
    "baseInstruction": "You are an assistant that... <system prompt for the agent>"
  }
]

Field Reference

| Field | Required | Description |

|---|---|---|

| useCaseId | Yes | Kebab-case identifier; used to build the agent name ({prefix}-{useCaseId}) |

| description | Yes | Human-readable description stored as agent metadata |

| baseInstruction | Yes | System prompt / base instructions for the agent |

Sync Script

PowerShell (interactive / CI)

Create or locate the sync script. The canonical path is infra/scripts/sync-foundry-agents.ps1 but adapt to the repo layout.

param(
  [Parameter(Mandatory)]
  [string]$SubscriptionId,

  [Parameter(Mandatory)]
  [string]$ProjectEndpoint,

  [string]$ManifestPath = (Join-Path $PSScriptRoot '..\foundry-agents.json'),
  [string]$ModelName = 'gpt-5-4',
  [string]$AgentNamePrefix = 'myproject',
  [string]$ApiVersion = '2025-11-15-preview'
)

$ErrorActionPreference = 'Stop'

# Optional: append a common instruction suffix to every agent
$commonSuffix = ''

az account set --subscription $SubscriptionId | Out-Null
$accessToken = az account get-access-token --resource https://ai.azure.com/ --query accessToken -o tsv
if (-not $accessToken) { throw 'Failed to acquire Foundry access token.' }

$definitions = Get-Content -Raw -Path $ManifestPath | ConvertFrom-Json
$headers = @{ Authorization = "Bearer $accessToken" }
$results = @()

foreach ($def in $definitions) {
  $agentName = "$AgentNamePrefix-$($def.useCaseId)"
  $instructions = if ($commonSuffix) { "$($def.baseInstruction)`n`n$commonSuffix" } else { $def.baseInstruction }
  $body = @{
    definition  = @{ kind = 'prompt'; model = $ModelName; instructions = $instructions }
    description = $def.description
    metadata    = @{ useCaseId = $def.useCaseId; managedBy = 'foundry-agent-sync' }
  } | ConvertTo-Json -Depth 8

  $uri = "$($ProjectEndpoint.TrimEnd('/'))/agents/$agentName`?api-version=$ApiVersion"
  $resp = Invoke-RestMethod -Method Post -Uri $uri -Headers $headers -ContentType 'application/json' -Body $body
  $version = $resp.version ?? $resp.latest_version ?? $resp.id ?? 'unknown'
  Write-Host "Synced $agentName ($version)"
  $results += [pscustomobject]@{ name = $agentName; version = $version }
}

$results | Format-Table -AutoSize

Bash (Bicep deployment script / CI)

For automated deployment via Microsoft.Resources/deploymentScripts, use a bash script that:

  1. Authenticates with a managed identity: az login --identity --username "$CLIENT_ID"
  2. Acquires a Foundry token: az account get-access-token --resource https://ai.azure.com/
  3. Iterates definitions from the FOUNDRY_AGENT_DEFINITIONS environment variable (JSON string)
  4. POSTs each agent to {endpoint}/agents/{name}?api-version=2025-11-15-preview

Bicep Integration (optional)

To run the sync automatically during infrastructure deployment:

  1. Load the manifest at compile time:
   var agentDefinitions = loadJsonContent('foundry-agents.json')
  1. Create a User-Assigned Managed Identity with the Azure AI User role on the Foundry project.
  1. Create a Microsoft.Resources/deploymentScripts resource (kind AzureCLI) that:
  • Uses the managed identity
  • Loads the bash sync script via loadTextContent
  • Passes the project endpoint, definitions, and model as environment variables

Gate behind a deployFoundryAgents parameter so teams can opt in/out.

Workflow

Step 1 — Locate or scaffold the manifest

Search the repo for foundry-agents.json. If it doesn't exist, ask the user what agents they need and create the manifest.

Step 2 — Locate or scaffold the sync script

Search for sync-foundry-agents.ps1 or foundry-agent-sync.sh. If missing, create the PowerShell script using the template above, adapting:

  • $AgentNamePrefix to match the project name
  • $ModelName to the user's deployed model
  • $ManifestPath to the actual manifest location

Step 3 — Collect parameters

Ask the user for:

  • Foundry project endpoint
  • Subscription ID
  • Model deployment name (default: gpt-5-4)
  • Agent name prefix (default: repo name in kebab-case)

Step 4 — Run the sync

Execute the PowerShell script with the collected parameters:

.\infra\scripts\sync-foundry-agents.ps1 `
  -SubscriptionId '<sub-id>' `
  -ProjectEndpoint '<endpoint>' `
  -ModelName '<model>' `
  -AgentNamePrefix '<prefix>'

Step 5 — Verify

Confirm synced agents by listing them:

$token = az account get-access-token --resource https://ai.azure.com/ --query accessToken -o tsv
$endpoint = '<project-endpoint>'
Invoke-RestMethod -Uri "$endpoint/agents?api-version=2025-11-15-preview" `
  -Headers @{ Authorization = "Bearer $token" }

REST API Reference

| Operation | Method | URL |

|---|---|---|

| Create/update agent | POST | {projectEndpoint}/agents/{agentName}?api-version=2025-11-15-preview |

| List agents | GET | {projectEndpoint}/agents?api-version=2025-11-15-preview |

| Get agent | GET | {projectEndpoint}/agents/{agentName}?api-version=2025-11-15-preview |

| Delete agent | DELETE | {projectEndpoint}/agents/{agentName}?api-version=2025-11-15-preview |

Create/Update Payload

{
  "definition": {
    "kind": "prompt",
    "model": "<deployed-model-name>",
    "instructions": "<system prompt>"
  },
  "description": "<agent description>",
  "metadata": {
    "useCaseId": "<use-case-id>",
    "managedBy": "foundry-agent-sync"
  }
}

Troubleshooting

| Symptom | Cause | Fix |

|---|---|---|

| 401 Unauthorized | Token expired or wrong audience | Re-run az account get-access-token --resource https://ai.azure.com/ |

| 403 Forbidden | Missing Azure AI User role | Assign the role on the Foundry project scope |

| 404 Not Found | Wrong project endpoint | Verify endpoint includes /api/projects/{projectName} |

| Model not found | Model not deployed in project | Deploy the model in AI Foundry portal first |

| Empty definitions | Manifest path wrong | Check -ManifestPath points to the JSON file |

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