40
A2A
Qualify and score omnichannel leads with OpenAI, Gmail, and Google Sheets
n8n-workflow-19539.n8n.io
· n8n.io
Quick overview This workflow captures inbound leads from Gmail or a webhook, uses OpenAI to extract qualification signals, scores and classifies each lead, logs it to Google Sheets, and creates a personalized Gmail draft for HOT leads to review before sending. How it works 1. Triggers when a new unread email arrives in Gmail or when a POST request is received on the webhook endpoint. 2. Normalizes the incoming email/webhook payload into a consistent lead format and checks that required fields (sender email and message) are present. 3. Loads existing leads from Google Sheets and stops processing if the incoming lead matches an existing Source Record ID. 4. Uses OpenAI to extract structured lead details (for example intent, urgency, company, and missing information) from the enquiry. 5. Calculates a weighted lead score from the extracted signals, classifies the lead as HOT/WARM/LOW based on configured thresholds, and appends the lead record to Google Sheets. 6. For HOT leads, uses OpenAI
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Trust score
19/100
grade F · 9 criteria
Uptime
not measured
no direct probes in 30d
Observed inflow · 30d
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no payment wallet declared
Invocations · 7d
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F
Conformance score: 19/100
F-grade: card is reachable but fails most operational signals.
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F
Conformance score: 19/100
F-grade: card is reachable but fails most operational signals.
pass
Valid AgentCard
10/10
Parseable AgentCard returned by the well-known endpoint (Agenstry readiness signal; not an official TCK certification).
info
Live JSON-RPC
0/25
Live probe hasn't run yet.
fail
Protocol version
0/10
No protocolVersion in card.
How to earn +10 points
Declare protocolVersion
Add `"protocolVersion": "1.0"` (Major.Minor, no patch number — §3.6) to every entry in `supportedInterfaces[]`. A2A v1.0 removed the AgentCard root field.
Docs →
info
JWS signature
0/10
Card is unsigned (most published agents are).
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Uptime track record
0/15
Only 0 probes so far, need ≥5 for an uptime grade.
fail
Skill declaration
0/10
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Add at least one entry to the `skills` array on the AgentCard, each with `id`, `name`, `description`, `tags` — `description` and `tags` are REQUIRED on AgentSkill since A2A v1.0, and tags are what discovery filters match on. We canonicalise these into the global skill taxonomy on next probe.
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5/10
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Freshness + modern flags
4/5
seen in upstream source within 0d
info
Security declaration
0/5
Neither securitySchemes nor securityRequirements declared — how to authenticate is unstated.
⚠ Card drift detected. This agent's
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Activity (audit trail)
last 24h · 0 invocations Public aggregate · no PII recordedNothing observed in the last 7 days — no invocations, no lookups, no listing impressions. Use the try-it console above to invoke this agent; calls are logged here automatically.
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not measured
0 direct probes · 30d
Response
—
no direct probe retained
Skills
0
declared
Streaming
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SSE-capable
Endpoints
| Agent card | https://n8n.io/workflows/19539 |
| Provider | https://n8n.io |
| Docs | https://n8n.io/workflows/19539 |
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Raw agent card JSON
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},
"displayName": "Code",
"typeVersion": 2,
"nodeCategories": [
{
"id": 5,
"name": "Development"
},
{
"id": 9,
"name": "Core Nodes"
}
]
},
{
"id": 1123,
"icon": "fa:link",
"name": "@n8n/n8n-nodes-langchain.chainLlm",
"codex": {
"data": {
"alias": [
"LangChain"
],
"resources": {
"primaryDocumentation": [
{
"url": "https://docs.n8n.io/integrations/builtin/cluster-nodes/root-nodes/n8n-nodes-langchain.chainllm/"
}
]
},
"categories": [
"AI",
"Langchain"
],
"subcategories": {
"AI": [
"Chains",
"Root Nodes"
]
}
}
},
"group": "[\"transform\"]",
"defaults": {
"name": "Basic LLM Chain",
"color": "#909298"
},
"iconData": {
"icon": "link",
"type": "icon"
},
"displayName": "Basic LLM Chain",
"typeVersion": 2,
"nodeCategories": [
{
"id": 25,
"name": "AI"
},
{
"id": 26,
"name": "Langchain"
}
]
},
{
"id": 1153,
"icon": "file:openAiLight.svg",
"name": "@n8n/n8n-nodes-langchain.lmChatOpenAi",
"codex": {
"data": {
"resources": {
"primaryDocumentation": [
{
"url": "https://docs.n8n.io/integrations/builtin/cluster-nodes/sub-nodes/n8n-nodes-langchain.lmchatopenai/"
}
]
},
"categories": [
"AI",
"Langchain"
],
"subcategories": {
"AI": [
"Language Models",
"Root Nodes"
],
"Language Models": [
"Chat Models (Recommended)"
]
}
}
},
"group": "[\"transform\"]",
"defaults": {
"name": "OpenAI Chat Model"
},
"iconData": {
"type": "file",
"fileBuffer": "data:image/svg+xml;base64,PHN2ZyB3aWR0aD0iNDAiIGhlaWdodD0iNDAiIHZpZXdCb3g9IjAgMCA0MCA0MCIgZmlsbD0ibm9uZSIgeG1sbnM9Imh0dHA6Ly93d3cudzMub3JnLzIwMDAvc3ZnIj4KPHBhdGggZD0iTTM2Ljg2NzEgMTYuMzcxOEMzNy43NzQ2IDEzLjY0OCAzNy40NjIxIDEwLjY2NDIgMzYuMDEwOCA4LjE4NjYxQzMzLjgyODIgNC4zODY1MyAyOS40NDA3IDIuNDMxNDkgMjUuMTU1NiAzLjM1MTUxQzIzLjI0OTMgMS4yMDM5NiAyMC41MTA1IC0wLjAxNzMxNDggMTcuNjM5MiAwLjAwMDE4NTUzM0MxMy4yNTkxIC0wLjAwOTgxNDY4IDkuMzcyNzMgMi44MTAyNSA4LjAyNTIgNi45Nzc4M0M1LjIxMTM5IDcuNTU0MSAyLjc4MjU4IDkuMzE1MzggMS4zNjEzIDExLjgxMTdDLTAuODM3NDkzIDE1LjYwMTggLTAuMzM2MjMyIDIwLjM3OTQgMi42MDEzMyAyMy42Mjk0QzEuNjkzODEgMjYuMzUzMiAyLjAwNjMyIDI5LjMzNzEgMy40NTc2IDMxLjgxNDZDNS42NDAxNSAzNS42MTQ3IDEwLjAyNzcgMzcuNTY5NyAxNC4zMTI4IDM2LjY0OTdDMTYuMjE3OSAzOC43OTczIDE4Ljk1NzkgNDAuMDE4NSAyMS44MjkyIDM5Ljk5OThDMjYuMjExOCA0MC4wMTEgMzAuMDk5NCAzNy4xODg1IDMxLjQ0NjkgMzMuMDE3MUMzNC4yNjA4IDMyLjQ0MDkgMzYuNjg5NiAzMC42Nzk2IDM4LjExMDggMjguMTgzM0M0MC4zMDcxIDI0LjM5MzIgMzkuODA0NiAxOS42MTk0IDM2Ljg2ODMgMTYuMzY5M0wzNi44NjcxIDE2LjM3MThaTTIxLjgzMTcgMzcuMzg2QzIwLjA3OCAzNy4zODg1IDE4LjM3OTIgMzYuNzc0NyAxNy4wMzI5IDM1LjY1MDlDMTcuMDk0MSAzNS42MTg0IDE3LjIwMDQgMzUuNTU5NyAxNy4yNjkxIDM1LjUxNzJMMjUuMjM0MyAzMC45MTcxQzI1LjY0MTggMzAuNjg1OCAyNS44OTE4IDMwLjI1MjEgMjUuODg5MyAyOS43ODMzVjE4LjU1NDNMMjkuMjU1NyAyMC40OTgxQzI5LjI5MTkgMjAuNTE1NiAyOS4zMTU3IDIwLjU1MDYgMjkuMzIwNyAyMC41OTA2VjI5Ljg4OTZDMjkuMzE1NyAzNC4wMjQ3IDI1Ljk2NjggMzcuMzc3MiAyMS44MzE3IDM3LjM4NlpNNS43MjY0IDMwLjUwNzFDNC44NDc2MyAyOC45ODk2IDQuNTMxMzcgMjcuMjEwOCA0LjgzMjYzIDI1LjQ4NDVDNC44OTEzOCAyNS41MTk1IDQuOTk1MTMgMjUuNTgzMiA1LjA2ODg4IDI1LjYyNTdMMTMuMDM0MSAzMC4yMjU4QzEzLjQzNzggMzAuNDYyMSAxMy45Mzc4IDMwLjQ2MjEgMTQuMzQyOCAzMC4yMjU4TDI0LjA2NjggMjQuNjEwN1YyOC40OTgzQzI0LjA2OTMgMjguNTM4MyAyNC4wNTA1IDI4LjU3NyAyNC4wMTkzIDI4LjYwMkwxNS45Njc5IDMzLjI1MDlDMTIuMzgxNSAzNS4zMTU5IDcuODAxNDQgMzQuMDg4NCA1LjcyNzY1IDMwLjUwNzFINS43MjY0Wk0zLjYzMDEgMTMuMTIwNUM0LjUwNTEyIDExLjYwMDQgNS44ODY0IDEwLjQzNzkgNy41MzE0NCA5LjgzNDE1QzcuNTMxNDQgOS45MDI5IDcuNTI3NjkgMTAuMDI0MiA3LjUyNzY5IDEwLjEwOTJWMTkuMzEwNkM3LjUyNTE5IDE5Ljc3ODEgNy43NzUxOSAyMC4yMTE5IDguMTgxNDUgMjAuNDQzMUwxNy45MDU0IDI2LjA1N0wxNC41MzkxIDI4LjAwMDhDMTQuNTA1MyAyOC4wMjMzIDE0LjQ2MjggMjguMDI3IDE0LjQyNTMgMjguMDEwOEw2LjM3MjY2IDIzLjM1ODJDMi43OTM4MyAyMS4yODU2IDEuNTY2MzEgMTYuNzA2OCAzLjYyODg1IDEzLjEyMTdMMy42MzAxIDEzLjEyMDVaTTMxLjI4ODIgMTkuNTU2OUwyMS41NjQyIDEzLjk0MTdMMjQuOTMwNiAxMS45OTkyQzI0Ljk2NDMgMTEuOTc2NyAyNS4wMDY4IDExLjk3MjkgMjUuMDQ0MyAxMS45ODkyTDMzLjA5NyAxNi42MzhDMzYuNjgyMSAxOC43MDkzIDM3LjkxMDggMjMuMjk1NyAzNS44Mzk1IDI2Ljg4MDhDMzQuOTYzMyAyOC4zOTgzIDMzLjU4MzIgMjkuNTYwOCAzMS45Mzk1IDMwLjE2NThWMjAuNjg5NEMzMS45NDMyIDIwLjIyMTkgMzEuNjk0NSAxOS43ODk0IDMxLjI4OTQgMTkuNTU2OUgzMS4yODgyWk0zNC42MzgzIDE0LjUxNDJDMzQuNTc5NSAxNC40NzggMzQuNDc1OCAxNC40MTU1IDM0LjQwMiAxNC4zNzNMMjYuNDM2OCA5Ljc3Mjg5QzI2LjAzMzEgOS41MzY2NCAyNS41MzMxIDkuNTM2NjQgMjUuMTI4MSA5Ljc3Mjg5TDE1LjQwNDEgMTUuMzg4VjExLjUwMDRDMTUuNDAxNiAxMS40NjA0IDE1LjQyMDQgMTEuNDIxNyAxNS40NTE2IDExLjM5NjdMMjMuNTAzIDYuNzUxNThDMjcuMDg5NCA0LjY4Mjc5IDMxLjY3NDUgNS45MTQwNiAzMy43NDIgOS41MDE2NEMzNC42MTU4IDExLjAxNjcgMzQuOTMyIDEyLjc5MDUgMzQuNjM1OCAxNC41MTQySDM0LjYzODNaTTEzLjU3NDEgMjEuNDQzMUwxMC4yMDY1IDE5LjQ5OTRDMTAuMTcwMiAxOS40ODE5IDEwLjE0NjUgMTkuNDQ2OCAxMC4xNDE1IDE5LjQwNjhWMTAuMTA3OUMxMC4xNDQgNS45Njc4MSAxMy41MDI4IDIuNjEyNzQgMTcuNjQyOSAyLjYxNTI0QzE5LjM5NDIgMi42MTUyNCAyMS4wODkyIDMuMjMwMjUgMjIuNDM1NSA0LjM1MDI4QzIyLjM3NDMgNC4zODI3OCAyMi4yNjkzIDQuNDQxNTMgMjIuMTk5MiA0LjQ4NDAzTDE0LjIzNDEgOS4wODQxM0MxMy44MjY2IDkuMzE1MzggMTMuNTc2NiA5Ljc0Nzg5IDEzLjU3OTEgMTAuMjE2N0wxMy41NzQxIDIxLjQ0MDZWMjEuNDQzMVpNMTUuNDAyOSAxNy41MDA2TDE5LjczNDIgMTQuOTk5M0wyNC4wNjU1IDE3LjQ5OTNWMjIuNTAwN0wxOS43MzQyIDI1LjAwMDdMMTUuNDAyOSAyMi41MDA3VjE3LjUwMDZaIiBmaWxsPSIjN0Q3RDg3Ii8+Cjwvc3ZnPgo="
},
"displayName": "OpenAI Chat Model",
"typeVersion": 1,
"nodeCategories": [
{
"id": 25,
"name": "AI"
},
{
"id": 26,
"name": "Langchain"
}
]
},
{
"id": 1179,
"icon": "fa:code",
"name": "@n8n/n8n-nodes-langchain.outputParserStructured",
"codex": {
"data": {
"alias": [
"json",
"zod"
],
"resources": {
"primaryDocumentation": [
{
"url": "https://docs.n8n.io/integrations/builtin/cluster-nodes/sub-nodes/n8n-nodes-langchain.outputparserstructured/"
}
]
},
"categories": [
"AI",
"Langchain"
],
"subcategories": {
"AI": [
"Output Parsers"
]
}
}
},
"group": "[\"transform\"]",
"defaults": {
"name": "Structured Output Parser"
},
"iconData": {
"icon": "code",
"type": "icon"
},
"displayName": "Structured Output Parser",
"typeVersion": 1,
"nodeCategories": [
{
"id": 25,
"name": "AI"
},
{
"id": 26,
"name": "Langchain"
}
]
}
]
},
"detail": {
"description": "Quick overview This workflow captures inbound leads from Gmail or a webhook, uses OpenAI to extract qualification signals, scores and classifies each lead, logs it to Google Sheets, and creates a personalized Gmail draft for HOT leads to review before sending. How it works 1. Triggers when a new unread email arrives in Gmail or when a POST request is received on the webhook endpoint. 2. Normalizes the incoming email/webhook payload into a consistent lead format and checks that required fields (sender email and message) are present. 3. Loads existing leads from Google Sheets and stops processing if the incoming lead matches an existing Source Record ID. 4. Uses OpenAI to extract structured lead details (for example intent, urgency, company, and missing information) from the enquiry. 5. Calculates a weighted lead score from the extracted signals, classifies the lead as HOT/WARM/LOW based on configured thresholds, and appends the lead record to Google Sheets. 6. For HOT leads, uses OpenAI to draft a tailored reply, appends your configured signature, and creates a Gmail draft addressed to the sender (threaded for Gmail-sourced leads). Setup 1. Add Gmail credentials for the Gmail trigger and Gmail draft actions, and optionally narrow which emails qualify via the Gmail trigger search/filter settings. 2. Add Google Sheets credentials, create/copy a lead-tracking spreadsheet, and paste its URL and tab name into the workflow configuration. 3. Add an OpenAI credential and select the chat model used for analysis and response writing. 4. Update the CONFIGURE section with your business details, scoring weights/thresholds, signature, and optional booking link. 5. If using the webhook intake, copy the webhook URL and configure your form/app to send lead data as JSON to it (including at least email and message). Requirements - n8n Cloud or self-hosted n8n - OpenAI API access and available API credits - Gmail account - Google Sheets account - A Google Sheet using the required PF-001 lead database columns Customization - Business name, description and services - HOT/WARM scoring thresholds - Individual scoring weights - Maximum qualification questions - Business email signature - Optional booking link - Gmail Search filter for shared inboxes - OpenAI model selection - Webhook integration with external forms, websites or apps"
}
}