Jira Team Tracking AI Agent

The workflow JSON

Copy or download the full n8n JSON below. Paste it into a new n8n workflow, add your credentials, activate. Full import guide →

{
  "name": "Jira Team Tracking AI Agent",
  "nodes": [
    {
      "parameters": {
        "promptType": "define",
        "text": "={{ $json.chatInput }}",
        "options": {
          "systemMessage": "You are a Jira progress assistant that manages team epics and generates inventory cost reports. Follow these steps strictly:\n\n1. **Team Identification**:\n   - Extract the team name from the user's message (e.g., \"Team Phoenix\").\n   - If no team is specified, use the default filter:  \n     `\"In-Progress Epic Inventory Cost\"`.\n\n2. **Filter Retrieval**:\n   - Fetch all Jira filters.\n   - If a team is identified, find the corresponding filter (e.g., `\"Team Phoenix Epic Inventory\"`).\n\n3. **JQL Execution**:\n   - Extract the `jql` from the filter's response.\n   - Search issues with filter\n\n4. **Report Generation**:\n   - Calculate inventory cost per epic based on aggregate time spent in seconds and convert it to hrs\n   - Format the response as:  \n     ```markdown\n     ## [Team: {Team Name}] Inventory Cost Report\n     | Epic | Progress | Time Spent (hrs) | Cost |\n     ```\n   - If data is missing, state:  \n     `\u26a0\ufe0f Cannot calculate cost for {Epic}: missing time spent`.\n\n5. **Error Handling**:\n   - If no filter exists, respond:  \n     `No filter found for team \"{Team Name}\". Using default filter.`\n   - If no issues match, say:  \n     `No active epics found for {Team Name}.`"
        }
      },
      "type": "@n8n/n8n-nodes-langchain.agent",
      "typeVersion": 1.8,
      "position": [
        -1140,
        -900
      ],
      "id": "6e42db1e-72f0-45bc-af3f-9aed2eafa275",
      "name": "AI Agent"
    },
    {
      "parameters": {
        "model": {
          "__rl": true,
          "value": "o3-mini",
          "mode": "list",
          "cachedResultName": "o3-mini"
        },
        "options": {}
      },
      "type": "@n8n/n8n-nodes-langchain.lmChatOpenAi",
      "typeVersion": 1.2,
      "position": [
        -1240,
        -680
      ],
      "id": "73387bff-10b3-400b-aae0-077b3db946f9",
      "name": "OpenAI Chat Model",
      "credentials": {
        "openAiApi": {
          "name": "<your credential>"
        }
      }
    },
    {
      "parameters": {
        "options": {}
      },
      "type": "@n8n/n8n-nodes-langchain.chatTrigger",
      "typeVersion": 1.1,
      "position": [
        -1440,
        -900
      ],
      "id": "e409fdbf-ba68-4998-84c1-2ff02ca8da9f",
      "name": "When chat message received"
    },
    {
      "parameters": {
        "toolDescription": "Get all Epics by JQL from filter",
        "url": "https://onetw.atlassian.net/rest/api/2/search",
        "authentication": "genericCredentialType",
        "genericAuthType": "httpBasicAuth",
        "sendQuery": true,
        "parametersQuery": {
          "values": [
            {
              "name": "jql"
            }
          ]
        }
      },
      "type": "@n8n/n8n-nodes-langchain.toolHttpRequest",
      "typeVersion": 1.1,
      "position": [
        -940,
        -680
      ],
      "id": "ec783078-8f5a-450b-88e1-236fcdd65e11",
      "name": "List Issues by Filter",
      "credentials": {
        "httpBasicAuth": {
          "name": "<your credential>"
        }
      }
    },
    {
      "parameters": {
        "toolDescription": "Get JIRA filters defined in GameLab (GL) project",
        "url": "https://onetw.atlassian.net/rest/api/3/filter/11545",
        "authentication": "genericCredentialType",
        "genericAuthType": "httpBasicAuth"
      },
      "type": "@n8n/n8n-nodes-langchain.toolHttpRequest",
      "typeVersion": 1.1,
      "position": [
        -720,
        -680
      ],
      "id": "e6189a22-f3e0-4d4e-9cf7-a117f8f5f196",
      "name": "Get Jira Filters",
      "credentials": {
        "httpBasicAuth": {
          "name": "<your credential>"
        }
      }
    }
  ],
  "connections": {
    "OpenAI Chat Model": {
      "ai_languageModel": [
        [
          {
            "node": "AI Agent",
            "type": "ai_languageModel",
            "index": 0
          }
        ]
      ]
    },
    "When chat message received": {
      "main": [
        [
          {
            "node": "AI Agent",
            "type": "main",
            "index": 0
          }
        ]
      ]
    },
    "List Issues by Filter": {
      "ai_tool": [
        [
          {
            "node": "AI Agent",
            "type": "ai_tool",
            "index": 0
          }
        ]
      ]
    },
    "Get Jira Filters": {
      "ai_tool": [
        [
          {
            "node": "AI Agent",
            "type": "ai_tool",
            "index": 0
          }
        ]
      ]
    }
  },
  "active": false,
  "settings": {
    "executionOrder": "v1"
  },
  "versionId": "aa64859e-7b8c-42bb-939a-2b94de0021b4",
  "meta": {
    "templateCredsSetupCompleted": true
  },
  "id": "mhAcC0DPACI7jaY5",
  "tags": []
}

Credentials you'll need

Each integration node will prompt for credentials when you import. We strip credential IDs before publishing — you'll add your own.

• httpBasicAuth
• openAiApi

About this workflow

Jira Team Tracking AI Agent. Uses agent, lmChatOpenAi, chatTrigger, toolHttpRequest. Chat trigger; 5 nodes.

Source: https://gitlab.com/starixvn/l1_n8n_workflow/-/blob/dev/jira/Jira_Team_Tracking_AI_Agent.json — original creator credit. Request a take-down →

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