Revue Jira
Ceci est unEngineering, Product, AIworkflow d'automatisation du domainecontenant 13 nœuds.Utilise principalement des nœuds comme If, Set, Jira, Summarize, GoogleDocs, combinant la technologie d'intelligence artificielle pour une automatisation intelligente. Générer des rapports de leçons tirées à partir d'épics Jira avec AI et Google Docs
- •Clé API OpenAI
Nœuds utilisés (13)
{
"id": "U1xUqDLvBYYSU6EU",
"meta": {
"instanceId": "8d54a4232b4618928ac9df0152e207cb858f5f9ffa6f3ba2d31d941bdcaec9d7",
"templateCredsSetupCompleted": true
},
"name": "Jira Retrospective",
"tags": [],
"nodes": [
{
"id": "b91c4727-8c63-4bf3-8101-6282aa6f592c",
"name": "Jira Get All Issues",
"type": "n8n-nodes-base.jira",
"position": [
60,
60
],
"parameters": {
"options": {},
"operation": "getAll"
},
"credentials": {
"jiraSoftwareCloudApi": {
"id": "AqnrDWxoCa8luriP",
"name": "Jira SW Cloud account"
}
},
"typeVersion": 1
},
{
"id": "4cf0689c-2a1f-4a90-81f4-d3483c63fc96",
"name": "Jira Get All Comments",
"type": "n8n-nodes-base.jira",
"position": [
280,
60
],
"parameters": {
"options": {},
"issueKey": "={{ $json.key }}",
"resource": "issueComment",
"operation": "getAll"
},
"credentials": {
"jiraSoftwareCloudApi": {
"id": "AqnrDWxoCa8luriP",
"name": "Jira SW Cloud account"
}
},
"typeVersion": 1
},
{
"id": "26803742-1a94-4969-878b-2f757aced4f8",
"name": "Agent IA",
"type": "@n8n/n8n-nodes-langchain.agent",
"position": [
940,
60
],
"parameters": {
"text": "=comments = {{ $json.concatenated_Comment }}\ndescription = {{ $json.Description }}\ntitle = {{ $json.Title }}\nstatus = {{ $json.EpicStatus }}\nepic_name = {{ $json.EpicName }}\n",
"options": {
"systemMessage": "=You are an AI assistant specialized in creating comprehensive Agile retrospective documents. Your task is to analyze the provided information about a completed task and generate an insightful **Lessons Learned** report formatted in **clean Markdown**, optimized for seamless conversion to Google Docs.\n\n---\n\n### 📥 Input Format\nYou will receive structured input containing:\n* `epic_name`: The broader initiative or project category\n* `title`: The specific task or user story name\n* `description`: A concise explanation of what the task involved\n\n---\n\n### 📤 Output Instructions\nGenerate a detailed **Lessons Learned** report using the following **Markdown** structure:\n\n# LESSONS LEARNED REPORT\n\n**Epic:** {epic_name} \n**Date:** {{$today.format('yyyy-MM-dd')}}} \n**Task:** {title} \n**Description:** {description}\n\n## Key Findings\n\n* Clear, specific insight about a technical challenge encountered\n* Process-related discovery that impacted delivery\n* Team dynamics observation or workflow improvement identified\n* {Add more if needed}\n\n## Comments & Observations\n\n{Write 2–3 paragraphs with:}\n\n* Specific examples from task execution\n* Feedback or quotes from team members (if available)\n* Comparisons to prior approaches\n* Unexpected challenges or positive surprises\n\n## Actionable Recommendations\n\n1. Specific, implementable action to address a finding\n2. Concrete suggestion for process improvement\n3. Recommendation for knowledge sharing or team development\n4. {Add more as needed}\n\n## Metrics & Impact\n\n{When possible, include:}\n\n* Time saved or efficiency gained\n* Quality improvements\n* User/customer feedback\n* Cost implications\n\n## Tags\n\n`#lessons-learned` `#{normalized_epic_name}` `#{relevant_technology}` `#{improvement_area}`\n\n---\n\n### 📝 Guidelines\n\n1. **Be specific** – use real details, not vague statements\n2. **Stay relevant** – stick to the task and its broader context\n3. **Focus on learning** – prioritize transferable insights\n4. **Balance** – include both wins and challenges\n5. **Actionability** – make every suggestion doable\n6. **Concise yet clear** – avoid fluff; write for impact\n7. **Formatting Guidelines for Google Docs compatibility:**\n * Use only asterisks (*) for bullet points, never hyphens (-)\n * Add two spaces after each line in lists for proper line breaks\n * Always leave a blank line before and after headings\n * Avoid using underscores (_) in text; use hyphens (-) instead\n * For emphasis, use consistently **bold** for important points and *italics* for supplementary information\n * When mentioning code or technical terms, use `single backticks`, never triple backticks\n * Use a pipe-separated format for tables as shown in the template\n * Keep paragraphs short (3-5 sentences) for better readability\n8. **Metadata Handling:** Include the epic name and task title exactly as provided in the input, without modification\n9. **Date Format:** Use YYYY-MM-DD format for the date for consistent sorting and display\n10. **Tags:** Keep tags lowercase, with hyphens instead of spaces, and relevant to the content\n\n---"
},
"promptType": "define"
},
"typeVersion": 1.9
},
{
"id": "29e37c80-68a4-490a-8952-2dcf974ff8d3",
"name": "Modèle de chat OpenAI",
"type": "@n8n/n8n-nodes-langchain.lmChatOpenAi",
"position": [
920,
280
],
"parameters": {
"model": {
"__rl": true,
"mode": "list",
"value": "gpt-4o-mini"
},
"options": {}
},
"credentials": {
"openAiApi": {
"id": "f3KRKVUp9GyRxd6U",
"name": "OpenAi account"
}
},
"typeVersion": 1.2
},
{
"id": "da5e365b-cc69-4bdd-bd58-e5b2ecb17387",
"name": "Edit Fields",
"type": "n8n-nodes-base.set",
"position": [
500,
60
],
"parameters": {
"options": {},
"assignments": {
"assignments": [
{
"id": "84fcaf69-4234-46be-9fa7-15026c60fed4",
"name": "EpicName",
"type": "string",
"value": "={{ $('Jira Get All Issues').item.json.fields.parent.fields.summary }}"
},
{
"id": "a7890a6b-1d0d-4486-908e-d3db571b89af",
"name": "EpicStatus",
"type": "string",
"value": "={{ $('Jira Get All Issues').item.json.fields.parent.fields.status.statusCategory.name }}"
},
{
"id": "c2c58d73-17a8-47b5-beb6-8295905cd8c2",
"name": "Title",
"type": "string",
"value": "={{ $('Jira Get All Issues').item.json.fields.summary }}"
},
{
"id": "baa10a35-ab3e-490f-b9ed-e661a6e9f4aa",
"name": "Description",
"type": "string",
"value": "={{ $('Jira Get All Issues').item.json.fields.description }}"
},
{
"id": "5da4ae54-07e6-41b8-bd51-054fe56beb5f",
"name": "Comment",
"type": "string",
"value": "={{ $json.body.content[0].content[0].text }}"
}
]
}
},
"typeVersion": 3.4
},
{
"id": "9718b066-e28f-41ea-97c2-559cbd894764",
"name": "Résumer",
"type": "n8n-nodes-base.summarize",
"position": [
720,
60
],
"parameters": {
"options": {},
"fieldsToSplitBy": "EpicName, EpicStatus, Title, Description",
"fieldsToSummarize": {
"values": [
{
"field": "Comment",
"separateBy": "\n",
"aggregation": "concatenate"
}
]
}
},
"typeVersion": 1.1
},
{
"id": "1d37efb7-09f1-43a7-a6c0-77d07b1f7a6b",
"name": "Google Docs",
"type": "n8n-nodes-base.googleDocs",
"position": [
1280,
60
],
"parameters": {
"simple": false,
"actionsUi": {
"actionFields": [
{
"text": "={{ $json.output }}",
"action": "insert"
}
]
},
"operation": "update",
"documentURL": "14X5gcowEprmL6ORyoo9tIrWWEB1HlhkixXUelesCLXs"
},
"credentials": {
"googleDocsOAuth2Api": {
"id": "Qe3TZG3K1euzTr3n",
"name": "Google Docs account"
}
},
"typeVersion": 2
},
{
"id": "bfab4af8-1f26-45b0-952b-1bd5f411d5f4",
"name": "Jira Trigger",
"type": "n8n-nodes-base.jiraTrigger",
"position": [
-380,
180
],
"webhookId": "3eb46690-d7b1-4a69-9a99-8adf8f843ed9",
"parameters": {
"events": [
"jira:issue_updated"
],
"additionalFields": {
"filter": ""
}
},
"credentials": {
"jiraSoftwareCloudApi": {
"id": "AqnrDWxoCa8luriP",
"name": "Jira SW Cloud account"
}
},
"typeVersion": 1.1
},
{
"id": "cc654cf3-c360-4704-a4b7-57447dbec8c6",
"name": "If",
"type": "n8n-nodes-base.if",
"position": [
-200,
180
],
"parameters": {
"options": {},
"conditions": {
"options": {
"version": 2,
"leftValue": "",
"caseSensitive": true,
"typeValidation": "strict"
},
"combinator": "and",
"conditions": [
{
"id": "a7028dd9-e262-4528-a20f-c80a26a28202",
"operator": {
"name": "filter.operator.equals",
"type": "string",
"operation": "equals"
},
"leftValue": "={{ $json.changelog.items[0].toString }}",
"rightValue": "Done"
}
]
}
},
"typeVersion": 2.2
},
{
"id": "b3ccd93e-a412-46f5-858d-ef8a2cd0efa9",
"name": "Simple Mémoire",
"type": "@n8n/n8n-nodes-langchain.memoryBufferWindow",
"position": [
1080,
280
],
"parameters": {
"sessionKey": "47",
"sessionIdType": "customKey"
},
"typeVersion": 1.3
},
{
"id": "e8379684-93ca-4118-bab5-f52a444c50e1",
"name": "Note adhésive",
"type": "n8n-nodes-base.stickyNote",
"position": [
-420,
-120
],
"parameters": {
"width": 380,
"height": 580,
"content": "## Epic Done?\nThis Node is Triggered on any issue change in Jira. However it only triggers the automation when the Epic status is changed to **Done**"
},
"typeVersion": 1
},
{
"id": "cdddcd3f-f896-4dbf-89e2-09060111cbc6",
"name": "Note adhésive1",
"type": "n8n-nodes-base.stickyNote",
"position": [
20,
-120
],
"parameters": {
"color": 5,
"width": 820,
"height": 580,
"content": "## Fetch issue Description and Comments\nOnce the Epic is Done, these nodes fetch issues and comments that fall under the Epic. For further processing the output is bundled."
},
"typeVersion": 1
},
{
"id": "c718a2e8-be7b-47b9-b7cc-9f4549a1060f",
"name": "Note adhésive2",
"type": "n8n-nodes-base.stickyNote",
"position": [
880,
-120
],
"parameters": {
"color": 3,
"width": 540,
"height": 580,
"content": "## Summarize and send to Google Docs\nThe LLM is summarizing the description / comments and generates a report with a layout defined in the System Message. Finally the output is send to Google Docs."
},
"typeVersion": 1
}
],
"active": false,
"pinData": {},
"settings": {
"executionOrder": "v1"
},
"versionId": "793ad505-261f-44ae-a197-a7c0e496dd69",
"connections": {
"cc654cf3-c360-4704-a4b7-57447dbec8c6": {
"main": [
[
{
"node": "b91c4727-8c63-4bf3-8101-6282aa6f592c",
"type": "main",
"index": 0
}
]
]
},
"AI Agent": {
"main": [
[
{
"node": "1d37efb7-09f1-43a7-a6c0-77d07b1f7a6b",
"type": "main",
"index": 0
}
]
]
},
"Summarize": {
"main": [
[
{
"node": "AI Agent",
"type": "main",
"index": 0
}
]
]
},
"da5e365b-cc69-4bdd-bd58-e5b2ecb17387": {
"main": [
[
{
"node": "Summarize",
"type": "main",
"index": 0
}
]
]
},
"bfab4af8-1f26-45b0-952b-1bd5f411d5f4": {
"main": [
[
{
"node": "cc654cf3-c360-4704-a4b7-57447dbec8c6",
"type": "main",
"index": 0
}
]
]
},
"Simple Memory": {
"ai_memory": [
[
{
"node": "AI Agent",
"type": "ai_memory",
"index": 0
}
]
]
},
"OpenAI Chat Model": {
"ai_languageModel": [
[
{
"node": "AI Agent",
"type": "ai_languageModel",
"index": 0
}
]
]
},
"b91c4727-8c63-4bf3-8101-6282aa6f592c": {
"main": [
[
{
"node": "4cf0689c-2a1f-4a90-81f4-d3483c63fc96",
"type": "main",
"index": 0
}
]
]
},
"4cf0689c-2a1f-4a90-81f4-d3483c63fc96": {
"main": [
[
{
"node": "da5e365b-cc69-4bdd-bd58-e5b2ecb17387",
"type": "main",
"index": 0
}
]
]
}
}
}Comment utiliser ce workflow ?
Copiez le code de configuration JSON ci-dessus, créez un nouveau workflow dans votre instance n8n et sélectionnez "Importer depuis le JSON", collez la configuration et modifiez les paramètres d'authentification selon vos besoins.
Dans quelles scénarios ce workflow est-il adapté ?
Intermédiaire - Ingénierie, Produit, Intelligence Artificielle
Est-ce payant ?
Ce workflow est entièrement gratuit et peut être utilisé directement. Veuillez noter que les services tiers utilisés dans le workflow (comme l'API OpenAI) peuvent nécessiter un paiement de votre part.
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