[F6] Generate Followup Artifacts
curl --request POST \
--url https://api-lr.agent.ai/v1/action/meeting_followup_generate_followup_artifacts \
--header 'Authorization: Bearer <token>' \
--header 'Content-Type: application/json' \
--data '
{
"transcript_analysis": "{{transcript_analysis}}",
"coaching_insights": "{{coaching_insights}}",
"enriched_event": "{{enriched_event}}",
"output_variable_name": "followup_artifacts",
"user_context": "{{followup_context}}",
"user_context_data": "{{user.context}}",
"fast_model": "gpt-5-mini",
"quality_model": "gpt-5",
"team_channel": "#sales-team"
}
'import requests
url = "https://api-lr.agent.ai/v1/action/meeting_followup_generate_followup_artifacts"
payload = {
"transcript_analysis": "{{transcript_analysis}}",
"coaching_insights": "{{coaching_insights}}",
"enriched_event": "{{enriched_event}}",
"output_variable_name": "followup_artifacts",
"user_context": "{{followup_context}}",
"user_context_data": "{{user.context}}",
"fast_model": "gpt-5-mini",
"quality_model": "gpt-5",
"team_channel": "#sales-team"
}
headers = {
"Authorization": "Bearer <token>",
"Content-Type": "application/json"
}
response = requests.post(url, json=payload, headers=headers)
print(response.text)const options = {
method: 'POST',
headers: {Authorization: 'Bearer <token>', 'Content-Type': 'application/json'},
body: JSON.stringify({
transcript_analysis: '{{transcript_analysis}}',
coaching_insights: '{{coaching_insights}}',
enriched_event: '{{enriched_event}}',
output_variable_name: 'followup_artifacts',
user_context: '{{followup_context}}',
user_context_data: '{{user.context}}',
fast_model: 'gpt-5-mini',
quality_model: 'gpt-5',
team_channel: '#sales-team'
})
};
fetch('https://api-lr.agent.ai/v1/action/meeting_followup_generate_followup_artifacts', options)
.then(res => res.json())
.then(res => console.log(res))
.catch(err => console.error(err));<?php
$curl = curl_init();
curl_setopt_array($curl, [
CURLOPT_URL => "https://api-lr.agent.ai/v1/action/meeting_followup_generate_followup_artifacts",
CURLOPT_RETURNTRANSFER => true,
CURLOPT_ENCODING => "",
CURLOPT_MAXREDIRS => 10,
CURLOPT_TIMEOUT => 30,
CURLOPT_HTTP_VERSION => CURL_HTTP_VERSION_1_1,
CURLOPT_CUSTOMREQUEST => "POST",
CURLOPT_POSTFIELDS => json_encode([
'transcript_analysis' => '{{transcript_analysis}}',
'coaching_insights' => '{{coaching_insights}}',
'enriched_event' => '{{enriched_event}}',
'output_variable_name' => 'followup_artifacts',
'user_context' => '{{followup_context}}',
'user_context_data' => '{{user.context}}',
'fast_model' => 'gpt-5-mini',
'quality_model' => 'gpt-5',
'team_channel' => '#sales-team'
]),
CURLOPT_HTTPHEADER => [
"Authorization: Bearer <token>",
"Content-Type: application/json"
],
]);
$response = curl_exec($curl);
$err = curl_error($curl);
curl_close($curl);
if ($err) {
echo "cURL Error #:" . $err;
} else {
echo $response;
}package main
import (
"fmt"
"strings"
"net/http"
"io"
)
func main() {
url := "https://api-lr.agent.ai/v1/action/meeting_followup_generate_followup_artifacts"
payload := strings.NewReader("{\n \"transcript_analysis\": \"{{transcript_analysis}}\",\n \"coaching_insights\": \"{{coaching_insights}}\",\n \"enriched_event\": \"{{enriched_event}}\",\n \"output_variable_name\": \"followup_artifacts\",\n \"user_context\": \"{{followup_context}}\",\n \"user_context_data\": \"{{user.context}}\",\n \"fast_model\": \"gpt-5-mini\",\n \"quality_model\": \"gpt-5\",\n \"team_channel\": \"#sales-team\"\n}")
req, _ := http.NewRequest("POST", url, payload)
req.Header.Add("Authorization", "Bearer <token>")
req.Header.Add("Content-Type", "application/json")
res, _ := http.DefaultClient.Do(req)
defer res.Body.Close()
body, _ := io.ReadAll(res.Body)
fmt.Println(string(body))
}HttpResponse<String> response = Unirest.post("https://api-lr.agent.ai/v1/action/meeting_followup_generate_followup_artifacts")
.header("Authorization", "Bearer <token>")
.header("Content-Type", "application/json")
.body("{\n \"transcript_analysis\": \"{{transcript_analysis}}\",\n \"coaching_insights\": \"{{coaching_insights}}\",\n \"enriched_event\": \"{{enriched_event}}\",\n \"output_variable_name\": \"followup_artifacts\",\n \"user_context\": \"{{followup_context}}\",\n \"user_context_data\": \"{{user.context}}\",\n \"fast_model\": \"gpt-5-mini\",\n \"quality_model\": \"gpt-5\",\n \"team_channel\": \"#sales-team\"\n}")
.asString();require 'uri'
require 'net/http'
url = URI("https://api-lr.agent.ai/v1/action/meeting_followup_generate_followup_artifacts")
http = Net::HTTP.new(url.host, url.port)
http.use_ssl = true
request = Net::HTTP::Post.new(url)
request["Authorization"] = 'Bearer <token>'
request["Content-Type"] = 'application/json'
request.body = "{\n \"transcript_analysis\": \"{{transcript_analysis}}\",\n \"coaching_insights\": \"{{coaching_insights}}\",\n \"enriched_event\": \"{{enriched_event}}\",\n \"output_variable_name\": \"followup_artifacts\",\n \"user_context\": \"{{followup_context}}\",\n \"user_context_data\": \"{{user.context}}\",\n \"fast_model\": \"gpt-5-mini\",\n \"quality_model\": \"gpt-5\",\n \"team_channel\": \"#sales-team\"\n}"
response = http.request(request)
puts response.read_body{
"status": 123,
"response": {}
}{
"status": 123,
"response": {}
}{
"status": 123,
"response": {}
}{
"status": 123,
"response": {}
}Meeting Follow-Up
[F6] Generate Followup Artifacts
Generates all followup deliverables in parallel: email draft, CRM notes, task list, and team update.
POST
/
action
/
meeting_followup_generate_followup_artifacts
[F6] Generate Followup Artifacts
curl --request POST \
--url https://api-lr.agent.ai/v1/action/meeting_followup_generate_followup_artifacts \
--header 'Authorization: Bearer <token>' \
--header 'Content-Type: application/json' \
--data '
{
"transcript_analysis": "{{transcript_analysis}}",
"coaching_insights": "{{coaching_insights}}",
"enriched_event": "{{enriched_event}}",
"output_variable_name": "followup_artifacts",
"user_context": "{{followup_context}}",
"user_context_data": "{{user.context}}",
"fast_model": "gpt-5-mini",
"quality_model": "gpt-5",
"team_channel": "#sales-team"
}
'import requests
url = "https://api-lr.agent.ai/v1/action/meeting_followup_generate_followup_artifacts"
payload = {
"transcript_analysis": "{{transcript_analysis}}",
"coaching_insights": "{{coaching_insights}}",
"enriched_event": "{{enriched_event}}",
"output_variable_name": "followup_artifacts",
"user_context": "{{followup_context}}",
"user_context_data": "{{user.context}}",
"fast_model": "gpt-5-mini",
"quality_model": "gpt-5",
"team_channel": "#sales-team"
}
headers = {
"Authorization": "Bearer <token>",
"Content-Type": "application/json"
}
response = requests.post(url, json=payload, headers=headers)
print(response.text)const options = {
method: 'POST',
headers: {Authorization: 'Bearer <token>', 'Content-Type': 'application/json'},
body: JSON.stringify({
transcript_analysis: '{{transcript_analysis}}',
coaching_insights: '{{coaching_insights}}',
enriched_event: '{{enriched_event}}',
output_variable_name: 'followup_artifacts',
user_context: '{{followup_context}}',
user_context_data: '{{user.context}}',
fast_model: 'gpt-5-mini',
quality_model: 'gpt-5',
team_channel: '#sales-team'
})
};
fetch('https://api-lr.agent.ai/v1/action/meeting_followup_generate_followup_artifacts', options)
.then(res => res.json())
.then(res => console.log(res))
.catch(err => console.error(err));<?php
$curl = curl_init();
curl_setopt_array($curl, [
CURLOPT_URL => "https://api-lr.agent.ai/v1/action/meeting_followup_generate_followup_artifacts",
CURLOPT_RETURNTRANSFER => true,
CURLOPT_ENCODING => "",
CURLOPT_MAXREDIRS => 10,
CURLOPT_TIMEOUT => 30,
CURLOPT_HTTP_VERSION => CURL_HTTP_VERSION_1_1,
CURLOPT_CUSTOMREQUEST => "POST",
CURLOPT_POSTFIELDS => json_encode([
'transcript_analysis' => '{{transcript_analysis}}',
'coaching_insights' => '{{coaching_insights}}',
'enriched_event' => '{{enriched_event}}',
'output_variable_name' => 'followup_artifacts',
'user_context' => '{{followup_context}}',
'user_context_data' => '{{user.context}}',
'fast_model' => 'gpt-5-mini',
'quality_model' => 'gpt-5',
'team_channel' => '#sales-team'
]),
CURLOPT_HTTPHEADER => [
"Authorization: Bearer <token>",
"Content-Type: application/json"
],
]);
$response = curl_exec($curl);
$err = curl_error($curl);
curl_close($curl);
if ($err) {
echo "cURL Error #:" . $err;
} else {
echo $response;
}package main
import (
"fmt"
"strings"
"net/http"
"io"
)
func main() {
url := "https://api-lr.agent.ai/v1/action/meeting_followup_generate_followup_artifacts"
payload := strings.NewReader("{\n \"transcript_analysis\": \"{{transcript_analysis}}\",\n \"coaching_insights\": \"{{coaching_insights}}\",\n \"enriched_event\": \"{{enriched_event}}\",\n \"output_variable_name\": \"followup_artifacts\",\n \"user_context\": \"{{followup_context}}\",\n \"user_context_data\": \"{{user.context}}\",\n \"fast_model\": \"gpt-5-mini\",\n \"quality_model\": \"gpt-5\",\n \"team_channel\": \"#sales-team\"\n}")
req, _ := http.NewRequest("POST", url, payload)
req.Header.Add("Authorization", "Bearer <token>")
req.Header.Add("Content-Type", "application/json")
res, _ := http.DefaultClient.Do(req)
defer res.Body.Close()
body, _ := io.ReadAll(res.Body)
fmt.Println(string(body))
}HttpResponse<String> response = Unirest.post("https://api-lr.agent.ai/v1/action/meeting_followup_generate_followup_artifacts")
.header("Authorization", "Bearer <token>")
.header("Content-Type", "application/json")
.body("{\n \"transcript_analysis\": \"{{transcript_analysis}}\",\n \"coaching_insights\": \"{{coaching_insights}}\",\n \"enriched_event\": \"{{enriched_event}}\",\n \"output_variable_name\": \"followup_artifacts\",\n \"user_context\": \"{{followup_context}}\",\n \"user_context_data\": \"{{user.context}}\",\n \"fast_model\": \"gpt-5-mini\",\n \"quality_model\": \"gpt-5\",\n \"team_channel\": \"#sales-team\"\n}")
.asString();require 'uri'
require 'net/http'
url = URI("https://api-lr.agent.ai/v1/action/meeting_followup_generate_followup_artifacts")
http = Net::HTTP.new(url.host, url.port)
http.use_ssl = true
request = Net::HTTP::Post.new(url)
request["Authorization"] = 'Bearer <token>'
request["Content-Type"] = 'application/json'
request.body = "{\n \"transcript_analysis\": \"{{transcript_analysis}}\",\n \"coaching_insights\": \"{{coaching_insights}}\",\n \"enriched_event\": \"{{enriched_event}}\",\n \"output_variable_name\": \"followup_artifacts\",\n \"user_context\": \"{{followup_context}}\",\n \"user_context_data\": \"{{user.context}}\",\n \"fast_model\": \"gpt-5-mini\",\n \"quality_model\": \"gpt-5\",\n \"team_channel\": \"#sales-team\"\n}"
response = http.request(request)
puts response.read_body{
"status": 123,
"response": {}
}{
"status": 123,
"response": {}
}{
"status": 123,
"response": {}
}{
"status": 123,
"response": {}
}Authorizations
Bearer token from your account (https://agent.ai/user/integrations#api)
Body
application/json
The analysis from Analyze Transcript action.
Insights from Generate Coaching action.
The enriched event data with meeting info.
Variable name to store all generated artifacts.
Pattern:
^[a-zA-Z][a-zA-Z0-9_]*$User context from Load Followup Context action.
Raw user.context data as fallback for user name/role.
Model for CRM notes, tasks, and team update.
Available options:
gpt-5-mini, gpt-5, gpt-4o-mini, claude-haiku-4-5 Model for follow-up email (higher quality).
Available options:
gpt-5, gpt-5-mini, claude-sonnet-4-5, gpt-4o Slack channel for team update.
⌘I

