articuler
by @hotwheelsbo
AI-powered professional networking assistant. Generate personalized cold emails and outreach playbooks to accelerate career growth and business development.
clawhub install articuler๐ About This Skill
name: articuler description: AI-powered professional networking assistant. Generate personalized cold emails and outreach playbooks to accelerate career growth and business development. homepage: https://www.articuler.ai metadata: {"clawdbot":{"emoji":"๐ค","requires":{"bins":["curl"]}}}
Articuler Skill
Craft the perfect cold email and build a structured outreach playbook โ all driven by your specific professional goal and LinkedIn profile.
What This Skill Does
1. Generate cold emails โ Write personalized outreach emails tailored to each contact's background 2. Build a playbook โ Create a structured outreach strategy with timing, talking points, and follow-up cadence
Usage
> Note: Steps 1 and 2 are required before calling any business API. Complete them in order to obtain a token.
Step 1 โ Email Check (Required)
Send a verification code to the user's email address.
curl --location --request POST 'https://api.articuler.ai/user/send-check' \
--header 'Content-Type: application/json' \
--data '{
"email": "your@email.com",
"type": 1
}'
#### Parameters
| Field | Type | Description |
| ------- | ------- | --------------------------------------------- |
| email | string | The user's email address |
| type | integer | Verification type, use 1 for standard check |
The verification code will be sent to the user's inbox. Ask the user to provide the captcha code before proceeding to Step 2.
Step 2 โ Login (Required)
Log in with the user's email, captcha code, and LinkedIn profile URL. Returns a token required for all subsequent API calls.
curl --location --request POST 'https://api.articuler.ai/user/artclaw/login' \
--header 'Content-Type: application/json' \
--data '{
"email": "your@email.com",
"captcha": "xxxxxx",
"linkedin_url": "https://www.linkedin.com/in/your-profile/"
}'
#### Parameters
| Field | Type | Description |
| -------------- | ------ | ---------------------------------------------------------------- |
| email | string | The user's email address |
| captcha | string | The verification code received in the user's inbox (from Step 1) |
| linkedin_url | string | The user's own LinkedIn profile URL |
#### Response
{
"token": "xxxxxx"
}
Save the token โ it is required for all subsequent API calls.
Step 3 โ Generate Playbook (Async)
Submit a playbook generation job for the current user and a target contact. This is an async API โ it returns a sessionId immediately. Use Step 4 to poll for the result.
curl --location --request POST 'https://api.articuler.ai/user/artclaw/playbook' \
--header 'Content-Type: application/json' \
--data '{
"token": "xxx",
"target_linkedin_url": "https://www.linkedin.com/in/your-target-profile/",
"objective": "Want to be a partner"
}'
#### Parameters
| Field | Type | Description |
| --------------------- | ------ | ------------------------------------------------------- |
| token | string | Auth token obtained from Step 2 |
| target_linkedin_url | string | The target contact's LinkedIn profile URL |
| objective | string | The goal of this outreach (e.g. "Want to be a partner") |
#### Response
{
"code": 0,
"msg": "",
"data": {
"sessionId": "31ee76d4-ab7e-4d5f-8196-f4507ef779b9",
"status": "searching"
}
}
Save the sessionId โ it is used to poll for the result in Step 4.
Step 4 โ Poll Playbook Result
Poll this endpoint repeatedly until status is "done". When done, read the playbook content from the response.
curl --location --request GET 'https://api.articuler.ai/user/artclaw/playbook/info?sess_id=xxx' \
--header 'Content-Type: application/json'
#### Parameters
| Field | Type | Description |
| --------- | ------ | ------------------------------------ |
| sess_id | string | The sessionId returned from Step 3 |
#### Polling Logic
data.status === "done"status remains "searching" after 300 seconds, inform the user that generation is taking longer than expected and ask whether to keep waiting#### Response โ In Progress
{
"code": 0,
"msg": "",
"data": {
"sessionId": "31ee76d4-ab7e-4d5f-8196-f4507ef779b9",
"status": "searching",
"objective": "Want to be a partner",
"playbook": { "subtopics": null },
"doOrNot": { "do": null, "doNot": null }
}
}
#### Response โ Completed
{
"code": 0,
"msg": "",
"data": {
"sessionId": "31ee76d4-ab7e-4d5f-8196-f4507ef779b9",
"status": "done",
"objective": "Want to be a partner",
"playbook": {
"subtopics": [
{
"subtopicName": "Absence of Personal Information for Mason Brown",
"insights": [
{
"insight": {
"title": "No Verified Personal Background or Professional Activities Available for Mason Brown",
"content": "Despite extensive search, no confirmed profiles...",
"referenceLinks": []
}
}
]
},
{
"subtopicName": "Monroe Street Partners' Strategic Differentiators",
"insights": [
{
"insight": {
"title": "Non-Traditional Private Equity Model Focused on Long-Term Value",
"content": "Monroe Street Partners (MSP), founded in ...",
"referenceLinks": [
"https://www.monroestreet-partners.com/aboutmsp",
"https://static1.squarespace.com/static/6218510..."
]
}
}
]
}
]
},
"doOrNot": {
"do": [
{
"title": "Discuss Monroe Street Partners' Unique PE Model and Financing Needs",
"contentList": [
"Leverage intelligence about MSP being ..."
]
},
{
"title": "Explore Synergies Between Mason's DCM Experience and MSP's Lower Middle-Market Focus",
"contentList": [
"Mason's background in Debt Capital Markets at PNC..."
]
},
{
"title": "Address Current Private Credit Market Trends Relevant to MSP's Strategy",
"contentList": [
"The industry context shows private credit doubling..."
]
}
],
"doNot": [
{
"title": "Avoid Pushing a Generic \"Off-the-Shelf\" Lending Solution",
"contentList": [
"Monroe Street Partners explicitly differentiates ..."
]
},
{
"title": "Refrain from Unsubstantiated Assumptions about Mason's Booth Studies or Long-Term Career Plans",
"contentList": [
"While Mason is attending Booth, his specific degree..."
]
},
{
"title": "Do Not Undervalue Mason's Role as a Summer Associate",
"contentList": [
"Although a Private Equity Summer Associate role is ..."
]
}
]
}
}
}
Present the playbook.subtopics, doOrNot.do, and doOrNot.doNot to the user in a readable format.
Step 5 โ Generate Cold Email (Async)
Submit a cold email generation job. Same async pattern as Steps 3โ4: returns a sessionId immediately, use Step 6 to poll for the result.
curl --location --request POST 'https://api.articuler.ai/user/artclaw/coldemail' \
--header 'Content-Type: application/json' \
--data '{
"token": "xxx",
"target_linkedin_url": "https://www.linkedin.com/in/your-target-profile/",
"objective": "Want to be a partner"
}'
#### Parameters
| Field | Type | Description |
| --------------------- | ------ | --------------------------------------------------------------------- |
| token | string | Auth token obtained from Step 2 |
| target_linkedin_url | string | The target contact's LinkedIn profile URL |
| objective | string | The goal of this cold email (e.g. "Explore investment opportunities") |
#### Response
{
"code": 0,
"msg": "",
"data": {
"sessionId": "2c6ae07f-bde7-4f6a-8cc6-944a99d742fd",
"status": "searching"
}
}
Save the sessionId โ it is used to poll for the result in Step 6.
Step 6 โ Poll Cold Email Result
Poll this endpoint repeatedly until status is "done". When done, read the email content from the response.
curl --location --request GET 'https://api.articuler.ai/user/artclaw/coldemail?sess_id=xxx' \
--header 'Content-Type: application/json'
#### Parameters
| Field | Type | Description |
| --------- | ------ | ------------------------------------ |
| sess_id | string | The sessionId returned from Step 5 |
#### Polling Logic
data.status === "done"status remains "searching" after 300 seconds, inform the user that generation is taking longer than expected and ask whether to keep waiting#### Response โ In Progress
{
"code": 0,
"msg": "",
"data": {
"sessionId": "2c6ae07f-bde7-4f6a-8cc6-944a99d742fd",
"status": "searching",
"objective": "Want to be a partner",
"subject": "",
"coldEmail": ""
}
}
#### Response โ Completed
{
"code": 0,
"msg": "",
"data": {
"sessionId": "2c6ae07f-bde7-4f6a-8cc6-944a99d742fd",
"status": "done",
"objective": "Want to be a partner",
"subject": "Exploring a potential partnership",
"coldEmail": "Hi [Name],\n\nI came across your work on..."
}
}
Always show the subject and coldEmail to the user for review before sending. Never auto-send.
MCP Server
Articuler provides an MCP server as an alternative to the REST API above.
Endpoint: https://www.articuler.ai/mcp
| Tool | Description |
| --------------------- | ------------------------------------------------------------------------------------ |
| generate_cold_email | Generate a personalized cold email given two LinkedIn profiles and an objective |
| generate_playbook | Generate a multi-step outreach playbook given two LinkedIn profiles and an objective |
Intent Detection
Detect the user's networking intent from their objective to set the right tone and structure:
| Intent | Keywords |
| ------------- | -------------------------- |
| fundraising | ่่ตใๆ่ตไบบใVCใpre-seed |
| hiring | ๆ่ใๅไผไบบใCTOใๅข้ |
| partnership | ๅไฝใBDใๆธ ้ใ่ตๆบ็ฝฎๆข |
| research | ไบ่งฃ่กไธใ่ฐ็ ใ่ถๅฟ |
| sales | ๅฎขๆทใไผไธ้่ดญใdemo |
Tips
objective, the more targeted the outputLinks
๐ก Examples
> Note: Steps 1 and 2 are required before calling any business API. Complete them in order to obtain a token.
Step 1 โ Email Check (Required)
Send a verification code to the user's email address.
curl --location --request POST 'https://api.articuler.ai/user/send-check' \
--header 'Content-Type: application/json' \
--data '{
"email": "your@email.com",
"type": 1
}'
#### Parameters
| Field | Type | Description |
| ------- | ------- | --------------------------------------------- |
| email | string | The user's email address |
| type | integer | Verification type, use 1 for standard check |
The verification code will be sent to the user's inbox. Ask the user to provide the captcha code before proceeding to Step 2.
Step 2 โ Login (Required)
Log in with the user's email, captcha code, and LinkedIn profile URL. Returns a token required for all subsequent API calls.
curl --location --request POST 'https://api.articuler.ai/user/artclaw/login' \
--header 'Content-Type: application/json' \
--data '{
"email": "your@email.com",
"captcha": "xxxxxx",
"linkedin_url": "https://www.linkedin.com/in/your-profile/"
}'
#### Parameters
| Field | Type | Description |
| -------------- | ------ | ---------------------------------------------------------------- |
| email | string | The user's email address |
| captcha | string | The verification code received in the user's inbox (from Step 1) |
| linkedin_url | string | The user's own LinkedIn profile URL |
#### Response
{
"token": "xxxxxx"
}
Save the token โ it is required for all subsequent API calls.
Step 3 โ Generate Playbook (Async)
Submit a playbook generation job for the current user and a target contact. This is an async API โ it returns a sessionId immediately. Use Step 4 to poll for the result.
curl --location --request POST 'https://api.articuler.ai/user/artclaw/playbook' \
--header 'Content-Type: application/json' \
--data '{
"token": "xxx",
"target_linkedin_url": "https://www.linkedin.com/in/your-target-profile/",
"objective": "Want to be a partner"
}'
#### Parameters
| Field | Type | Description |
| --------------------- | ------ | ------------------------------------------------------- |
| token | string | Auth token obtained from Step 2 |
| target_linkedin_url | string | The target contact's LinkedIn profile URL |
| objective | string | The goal of this outreach (e.g. "Want to be a partner") |
#### Response
{
"code": 0,
"msg": "",
"data": {
"sessionId": "31ee76d4-ab7e-4d5f-8196-f4507ef779b9",
"status": "searching"
}
}
Save the sessionId โ it is used to poll for the result in Step 4.
Step 4 โ Poll Playbook Result
Poll this endpoint repeatedly until status is "done". When done, read the playbook content from the response.
curl --location --request GET 'https://api.articuler.ai/user/artclaw/playbook/info?sess_id=xxx' \
--header 'Content-Type: application/json'
#### Parameters
| Field | Type | Description |
| --------- | ------ | ------------------------------------ |
| sess_id | string | The sessionId returned from Step 3 |
#### Polling Logic
data.status === "done"status remains "searching" after 300 seconds, inform the user that generation is taking longer than expected and ask whether to keep waiting#### Response โ In Progress
{
"code": 0,
"msg": "",
"data": {
"sessionId": "31ee76d4-ab7e-4d5f-8196-f4507ef779b9",
"status": "searching",
"objective": "Want to be a partner",
"playbook": { "subtopics": null },
"doOrNot": { "do": null, "doNot": null }
}
}
#### Response โ Completed
{
"code": 0,
"msg": "",
"data": {
"sessionId": "31ee76d4-ab7e-4d5f-8196-f4507ef779b9",
"status": "done",
"objective": "Want to be a partner",
"playbook": {
"subtopics": [
{
"subtopicName": "Absence of Personal Information for Mason Brown",
"insights": [
{
"insight": {
"title": "No Verified Personal Background or Professional Activities Available for Mason Brown",
"content": "Despite extensive search, no confirmed profiles...",
"referenceLinks": []
}
}
]
},
{
"subtopicName": "Monroe Street Partners' Strategic Differentiators",
"insights": [
{
"insight": {
"title": "Non-Traditional Private Equity Model Focused on Long-Term Value",
"content": "Monroe Street Partners (MSP), founded in ...",
"referenceLinks": [
"https://www.monroestreet-partners.com/aboutmsp",
"https://static1.squarespace.com/static/6218510..."
]
}
}
]
}
]
},
"doOrNot": {
"do": [
{
"title": "Discuss Monroe Street Partners' Unique PE Model and Financing Needs",
"contentList": [
"Leverage intelligence about MSP being ..."
]
},
{
"title": "Explore Synergies Between Mason's DCM Experience and MSP's Lower Middle-Market Focus",
"contentList": [
"Mason's background in Debt Capital Markets at PNC..."
]
},
{
"title": "Address Current Private Credit Market Trends Relevant to MSP's Strategy",
"contentList": [
"The industry context shows private credit doubling..."
]
}
],
"doNot": [
{
"title": "Avoid Pushing a Generic \"Off-the-Shelf\" Lending Solution",
"contentList": [
"Monroe Street Partners explicitly differentiates ..."
]
},
{
"title": "Refrain from Unsubstantiated Assumptions about Mason's Booth Studies or Long-Term Career Plans",
"contentList": [
"While Mason is attending Booth, his specific degree..."
]
},
{
"title": "Do Not Undervalue Mason's Role as a Summer Associate",
"contentList": [
"Although a Private Equity Summer Associate role is ..."
]
}
]
}
}
}
Present the playbook.subtopics, doOrNot.do, and doOrNot.doNot to the user in a readable format.
Step 5 โ Generate Cold Email (Async)
Submit a cold email generation job. Same async pattern as Steps 3โ4: returns a sessionId immediately, use Step 6 to poll for the result.
curl --location --request POST 'https://api.articuler.ai/user/artclaw/coldemail' \
--header 'Content-Type: application/json' \
--data '{
"token": "xxx",
"target_linkedin_url": "https://www.linkedin.com/in/your-target-profile/",
"objective": "Want to be a partner"
}'
#### Parameters
| Field | Type | Description |
| --------------------- | ------ | --------------------------------------------------------------------- |
| token | string | Auth token obtained from Step 2 |
| target_linkedin_url | string | The target contact's LinkedIn profile URL |
| objective | string | The goal of this cold email (e.g. "Explore investment opportunities") |
#### Response
{
"code": 0,
"msg": "",
"data": {
"sessionId": "2c6ae07f-bde7-4f6a-8cc6-944a99d742fd",
"status": "searching"
}
}
Save the sessionId โ it is used to poll for the result in Step 6.
Step 6 โ Poll Cold Email Result
Poll this endpoint repeatedly until status is "done". When done, read the email content from the response.
curl --location --request GET 'https://api.articuler.ai/user/artclaw/coldemail?sess_id=xxx' \
--header 'Content-Type: application/json'
#### Parameters
| Field | Type | Description |
| --------- | ------ | ------------------------------------ |
| sess_id | string | The sessionId returned from Step 5 |
#### Polling Logic
data.status === "done"status remains "searching" after 300 seconds, inform the user that generation is taking longer than expected and ask whether to keep waiting#### Response โ In Progress
{
"code": 0,
"msg": "",
"data": {
"sessionId": "2c6ae07f-bde7-4f6a-8cc6-944a99d742fd",
"status": "searching",
"objective": "Want to be a partner",
"subject": "",
"coldEmail": ""
}
}
#### Response โ Completed
{
"code": 0,
"msg": "",
"data": {
"sessionId": "2c6ae07f-bde7-4f6a-8cc6-944a99d742fd",
"status": "done",
"objective": "Want to be a partner",
"subject": "Exploring a potential partnership",
"coldEmail": "Hi [Name],\n\nI came across your work on..."
}
}
Always show the subject and coldEmail to the user for review before sending. Never auto-send.
๐ Tips & Best Practices
objective, the more targeted the output