> ## Documentation Index
> Fetch the complete documentation index at: https://skyvern.com/docs/llms.txt
> Use this file to discover all available pages before exploring further.
# Job Applications Pipeline
> Build an agent that parses your resume, searches job portals, extracts listings, generates tailored answers with AI, and submits applications automatically.
Automate job applications across multiple postings on any job portal.
This cookbook creates an agent that logs into a job portal, searches for relevant positions based on your resume, extracts job listings, and applies to each one with AI-generated responses tailored to the role.
***
## What you'll build
An agent that:
1. Parses your resume PDF to extract structured information
2. Logs into a job portal using saved credentials
3. Searches for relevant jobs based on your resume
4. Extracts a list of matching job postings
5. For each job: extracts details, generates tailored answers, and submits the application
***
## Prerequisites
* **Skyvern Cloud API key**: Get one at [app.skyvern.com/settings](https://app.skyvern.com/settings) → API Keys
Install the SDK:
```bash Python theme={null}
pip install skyvern
```
```bash TypeScript theme={null}
npm install @skyvern/client
```
Set your API key:
```bash theme={null}
export SKYVERN_API_KEY="your-api-key"
```
***
## Sample Job Portal
We'll use *Job Stash*, a fake job board website created for agent automation testing.
Change `job_portal_url` to use your job portal's URL.
| Field | Value |
| -------------- | ------------------------------------------------------------ |
| URL | [https://job-stash.vercel.app](https://job-stash.vercel.app) |
| Login email | [demo@manicule.dev](mailto:demo@manicule.dev) |
| Login password | helloworld |
***
## Step 1: Store credentials
Before defining the agent, store the login email and password Skyvern will use.
This makes sure your passwords are never stored in the shareable agent definition and never sent to LLMs.
Go to **Credentials** in the sidebar. Choose **Password** after clicking on **+ Add**.
Click **Create Credential**. Set the name to `Job Stash`, add login page URL, and enter the username (`demo@manicule.dev`) and password (`helloworld`). Click **Save**.
Copy the credential ID (here: `cred_504284876895871734`). You'll use this when configuring the agent.
```python Python theme={null}
import os
import asyncio
from skyvern import Skyvern
async def main():
client = Skyvern(api_key=os.getenv("SKYVERN_API_KEY"))
credential = await client.create_credential(
name="Job Portal",
credential_type="password",
credential={
"username": "demo@manicule.dev",
"password": "helloworld"
}
)
print(f"Credential ID: {credential.credential_id}")
# Save this ID for your workflow: cred_xxx
asyncio.run(main())
```
```typescript TypeScript theme={null}
import { SkyvernClient } from "@skyvern/client";
const client = new SkyvernClient({
apiKey: process.env.SKYVERN_API_KEY,
});
const credential = await client.createCredential({
name: "Job Portal",
credential_type: "password",
credential: {
username: "demo@manicule.dev",
password: "helloworld",
},
});
console.log(`Credential ID: ${credential.credential_id}`);
```
```bash cURL theme={null}
curl -X POST "https://api.skyvern.com/v1/credentials" \
-H "x-api-key: $SKYVERN_API_KEY" \
-H "Content-Type: application/json" \
-d '{
"name": "Job Portal",
"credential_type": "password",
"credential": {
"username": "demo@manicule.dev",
"password": "helloworld"
}
}'
```
***
## Step 2: Create a new agent
Go to **Agents** → **Create Agent**. Name it "Search and Apply for Jobs Workflow".
An **agent definition** is a JSON or YAML file that describes your entire agent: its metadata, parameters, and blocks. Create a file called `job-application-workflow.yaml` (or `.json`) with the following template:
```json JSON theme={null}
{
"title": "Search and Apply for Jobs Workflow",
"description": "Search for jobs on any portal, extract listings, generate tailored answers with AI, and submit applications automatically.",
"proxy_location": "RESIDENTIAL",
"workflow_definition": {
"version": 1,
"parameters": [],
"blocks": []
}
}
```
```yaml YAML theme={null}
title: Search and Apply for Jobs Workflow
description: "Search for jobs on any portal, extract listings, generate tailored answers with AI, and submit applications automatically."
proxy_location: RESIDENTIAL
workflow_definition:
version: 1
parameters: [] # <-- filled in below
blocks: [] # <-- filled in Step 3
```
We'll populate `parameters` and `blocks` in the sections that follow.
### Set parameters
Parameters are the inputs your agent accepts. Defining them upfront lets you reuse the same agent against different job portals.
On the **Start** node, add the following parameters:
| Parameter | Type | Notes |
| ---------------- | ------------- | ------------------------------------------- |
| `resume` | File URL | URL to your resume PDF |
| `credentials` | Credential ID | Select the credential you created in Step 1 |
| `job_portal_url` | String | Job portal login URL |
Replace the empty `parameters` array with the following:
```json JSON theme={null}
"parameters": [
{ "key": "resume", "parameter_type": "workflow", "workflow_parameter_type": "file_url" },
{
"key": "credentials",
"parameter_type": "workflow",
"workflow_parameter_type": "credential_id",
"default_value": "your-credential-id"
},
{
"key": "job_portal_url",
"description": "URL of the job portal",
"parameter_type": "workflow",
"workflow_parameter_type": "string"
}
]
```
```yaml YAML theme={null}
parameters:
- key: resume
parameter_type: workflow
workflow_parameter_type: file_url
- key: credentials
parameter_type: workflow
workflow_parameter_type: credential_id
default_value: your-credential-id # <-- replace this
- key: job_portal_url
description: URL of the job portal
parameter_type: workflow
workflow_parameter_type: string
```
***
## Step 3: Add agent blocks
The agent chains together several blocks to automate the full job application process:
1. **PDF Parser block**: Extracts structured data from your resume
2. **Login block**: Authenticates to the job portal using stored credentials
3. **Navigation block**: Searches for relevant jobs based on your resume
4. **Extraction block**: Extracts a list of job postings from search results
5. **For loop** (Go to URL + Extraction + Action + Extraction + Text Prompt + Navigation): Iterates over each job to extract details, generates tailored answers using an LLM, and submits the application.
In the Cloud UI, click the **+** button after the Start node to add blocks sequentially. For SDK users, add each block to the `blocks` array in your agent definition file.
### PDF Parser block
The `pdf_parser` block extracts structured information from your resume PDF. Skyvern uses AI to identify your name, contact info, work experience, education, and skills.
Add a **PDF Parser** block. Set **File URL** to the `resume` parameter.
```json JSON theme={null}
{
"block_type": "pdf_parser",
"label": "parsed_resume",
"file_url": "{{ resume }}"
}
```
```yaml YAML theme={null}
- block_type: pdf_parser
label: parsed_resume
file_url: "{{ resume }}"
```
The parsed data is accessible as `parsed_resume_output` in subsequent blocks.
### Login block
The `login` block authenticates using stored credentials. Skyvern injects the username/password directly into form fields without exposing them to the LLM.
Add a **Login** block. Configure it as follows:
* **URL**: set to the `job_portal_url` parameter
* **Credential**: Select the `credentials` parameter
* **Goal**: "Log in using the provided credentials. Handle any cookie consent popups. COMPLETE when on the account dashboard or orders page."
```json JSON theme={null}
{
"block_type": "login",
"label": "login_to_portal",
"url": "{{ job_portal_url }}",
"title": "login_to_portal",
"parameter_keys": ["credentials"],
"navigation_goal": "Log in using the provided credentials.\nHandle any cookie consent popups.\nCOMPLETE when on the account dashboard or orders page.",
"max_retries": 0,
"engine": "skyvern-1.0"
}
```
```yaml YAML theme={null}
- block_type: login
label: login_to_portal
url: "{{ job_portal_url }}"
title: login_to_portal
parameter_keys:
- credentials
navigation_goal: |
Log in using the provided credentials.
Handle any cookie consent popups.
COMPLETE when on the account dashboard or orders page.
max_retries: 0
engine: skyvern-1.0
```
### Search for jobs block
Navigate to the job search and find relevant positions based on the parsed resume.
Add a **Navigation** block. Configure it as follows:
* **URL**: Leave empty (continues from the current page after login)
* **Goal**: "Search for a relevant job based on the parsed resume." The block will automatically reference the `parsed_resume_output` from the previous step.
```json JSON theme={null}
{
"block_type": "navigation",
"label": "search_for_job",
"url": "",
"title": "search_for_job",
"engine": "skyvern-1.0",
"navigation_goal": "Search for a relevant job based on the parsed resume: {{parsed_resume_output}}",
"max_retries": 0
}
```
```yaml YAML theme={null}
- block_type: navigation
label: search_for_job
url: ""
title: search_for_job
engine: skyvern-1.0
navigation_goal: "Search for a relevant job based on the parsed resume: {{parsed_resume_output}}"
max_retries: 0
```
### Extract jobs list block
Extract job postings from the search results. The `data_schema` tells Skyvern exactly what structure to return.
Add an **Extraction** block. Configure it as follows:
* **Goal**: "Extract all visible job profiles: job page url, title, employer, location, and type (full time, part time, etc)"
* **Data Schema**: Paste the following JSON schema:
```json theme={null}
{
"jobs": {
"type": "array",
"items": {
"type": "object",
"properties": {
"job_page_url": { "type": "string", "description": "Link to the apply page for the job" },
"title": { "type": "string", "description": "Title of the role offered" },
"employer": { "type": "string", "description": "Name of the company posting the job profile" },
"location": { "type": "string", "description": "Where is the job role based. City and country," },
"type": { "type": "string", "description": "Type for employment: full-time. part-time, contractual, internship etc." }
},
"required": ["job_page_url", "title", "employer", "location"]
}
}
}
```
```json JSON theme={null}
{
"block_type": "extraction",
"label": "jobs_list_extraction",
"url": "",
"title": "jobs_list_extraction",
"data_extraction_goal": "Extract all visible job profiles: job page url, title, employer, location, and type (full time, part time, etc)",
"data_schema": {
"jobs": {
"type": "array",
"items": {
"type": "object",
"properties": {
"job_page_url": {
"type": "string",
"description": "Link to the apply page for the job"
},
"title": {
"type": "string",
"description": "Title of the role offered"
},
"employer": {
"type": "string",
"description": "Name of the company posting the job profile"
},
"location": {
"type": "string",
"description": "Where is the job role based. City and country,"
},
"type": {
"type": "string",
"description": "Type for employment: full-time. part-time, contractual, internship etc."
}
},
"required": ["job_page_url", "title", "employer", "location"]
}
}
},
"max_retries": 0,
"engine": "skyvern-1.0"
}
```
```yaml YAML theme={null}
- block_type: extraction
label: jobs_list_extraction
url: ""
title: jobs_list_extraction
data_extraction_goal: "Extract all visible job profiles: job page url, title, employer, location, and type (full time, part time, etc)"
data_schema:
jobs:
type: array
items:
type: object
properties:
job_page_url:
type: string
description: Link to the apply page for the job
title:
type: string
description: Title of the role offered
employer:
type: string
description: Name of the company posting the job profile
location:
type: string
description: Where is the job role based. City and country,
type:
type: string
description: "Type for employment: full-time. part-time, contractual, internship etc."
required:
- job_page_url
- title
- employer
- location
max_retries: 0
engine: skyvern-1.0
```
The output is accessible as `jobs_list_extraction_output.jobs` in subsequent blocks.
### Apply to jobs loop
Iterate over each job posting and complete the application. This loop contains multiple blocks that work together:
1. **goto\_url**: Navigate to the job page
2. **extraction**: Extract detailed job information
3. **action**: Click the Apply button
4. **extraction**: Extract application form questions
5. **text\_prompt**: Generate tailored answers using AI
6. **navigation**: Fill out and submit the application
Add a **For Loop** block. Set the **Loop Variable** to `jobs_list_extraction_output.jobs`. Enable **Continue on Failure** and **Next Loop on Failure**.
Inside the loop, add the following blocks in order:
Add a **Go to URL** block. Set **URL** to the `current_value.job_page_url` variable.
Add an **Extraction** block. Set **Goal** to: "Extract every detail about the job role present on the page."
Add an **Action** block. Set **Goal** to: "Find Apply button and click it. COMPLETE when the job application is visible on the screen."
Add an **Extraction** block. Set **Goal** to: "Extract every question in the job application form as a list."
Add a **Text Prompt** block. Set the **Prompt** to reference the parsed resume, job details, and extracted questions so the AI generates tailored answers for each field.
Add a **Navigation** block. Set **Goal** to: "Fill out all of the form fields using the generated answers, including optional fields. COMPLETE when the application form has been successfully submitted."
```json JSON theme={null}
{
"block_type": "for_loop",
"label": "for_each_job",
"loop_variable_reference": "{{jobs_list_extraction_output.jobs}}",
"continue_on_failure": true,
"next_loop_on_failure": true,
"complete_if_empty": true,
"loop_blocks": [
{
"block_type": "goto_url",
"label": "go_to_each_job",
"url": "{{ current_value.job_page_url }}"
},
{
"block_type": "extraction",
"label": "extract_job_detail",
"url": "",
"title": "extract_job_detail",
"data_extraction_goal": "Extract every detail about the job role present on the page",
"max_retries": 0,
"engine": "skyvern-1.0"
},
{
"block_type": "action",
"label": "click_apply",
"url": "",
"title": "click_apply",
"navigation_goal": "Find Apply button and click it.\n\nCOMPLETE when the job application is visible on the screen",
"max_retries": 0,
"engine": "skyvern-1.0"
},
{
"block_type": "extraction",
"label": "extract_questions",
"url": "",
"title": "extract_questions",
"data_extraction_goal": "Extract every question in the job application form as a list",
"max_retries": 0,
"engine": "skyvern-1.0"
},
{
"block_type": "text_prompt",
"label": "answer_form_questions",
"prompt": "Given:\nresume: {{resume}}\nparsed resume: {{parsed_resume_output}}\ninformation about the job profile: {{extract_job_detail_output}}\napplication form questions: {{extract_questions_output}}\n\nYou are applying for {{ current_value.title }} at {{ current_value.employer }}.\n\nWrite thoughtful and impressive answers to each question using the information from resume and parsed resume output."
},
{
"block_type": "navigation",
"label": "apply_to_job",
"url": "",
"title": "apply_to_job",
"engine": "skyvern-1.0",
"navigation_goal": "Given:\n{{answer_form_questions_output}}\n\nFill out all of the form fields, including the optional fields.\n\nIf you dont know the answer to an optional question, leave it blank. If you dont know the answer to a required question such as referral name put N/A or something equivalent.\n\nCOMPLETE when the application form has been successfully submitted.\n\nMore context:\nresume: {{resume}}\nperson_information: {{parsed_resume_output}}",
"max_retries": 0
}
]
}
```
```yaml YAML theme={null}
- block_type: for_loop
label: for_each_job
loop_variable_reference: "{{jobs_list_extraction_output.jobs}}"
continue_on_failure: true
next_loop_on_failure: true
complete_if_empty: true
loop_blocks:
- block_type: goto_url
label: go_to_each_job
url: "{{ current_value.job_page_url }}"
- block_type: extraction
label: extract_job_detail
url: ""
title: extract_job_detail
data_extraction_goal: Extract every detail about the job role present on the page
max_retries: 0
engine: skyvern-1.0
- block_type: action
label: click_apply
url: ""
title: click_apply
navigation_goal: |
Find Apply button and click it.
COMPLETE when the job application is visible on the screen
max_retries: 0
engine: skyvern-1.0
- block_type: extraction
label: extract_questions
url: ""
title: extract_questions
data_extraction_goal: Extract every question in the job application form as a list
max_retries: 0
engine: skyvern-1.0
- block_type: text_prompt
label: answer_form_questions
prompt: |
Given:
resume: {{resume}}
parsed resume: {{parsed_resume_output}}
information about the job profile: {{extract_job_detail_output}}
application form questions: {{extract_questions_output}}
You are applying for {{ current_value.title }} at {{ current_value.employer }}.
Write thoughtful and impressive answers to each question using the information from resume and parsed resume output.
- block_type: navigation
label: apply_to_job
url: ""
title: apply_to_job
engine: skyvern-1.0
navigation_goal: |
Given:
{{answer_form_questions_output}}
Fill out all of the form fields, including the optional fields.
If you dont know the answer to an optional question, leave it blank. If you dont know the answer to a required question such as referral name put N/A or something equivalent.
COMPLETE when the application form has been successfully submitted.
More context:
resume: {{resume}}
person_information: {{parsed_resume_output}}
max_retries: 0
```
**Key pattern:** `continue_on_failure: true` ensures that if one application fails, the agent continues to the next job. Inside the loop, `current_value` gives you the current job being processed.
***
## Complete agent definition
Here's a summary of the complete agent you've built in the visual editor:
Go to **Agents** → **Create Agent**. Name it "Search and Apply for Jobs Workflow." On the **Start** node, set **Proxy Location** to **Residential** and add the parameters: `resume`, `credentials`, and `job_portal_url`.
Add a **PDF Parser** block. Set **File URL** to the `resume` parameter.
Add a **Login** block. Set **URL** to the `job_portal_url` parameter. Select the `credentials` parameter. Set the goal: "Log in using the provided credentials. Handle any cookie consent popups. COMPLETE when on the account dashboard or orders page."
Add a **Navigation** block. Leave **URL** empty. Set the goal: "Search for a relevant job based on the parsed resume."
Add an **Extraction** block. Set the goal: "Extract all visible job profiles: job page url, title, employer, location, and type." Paste the jobs JSON schema into **Data Schema**.
Add a **For Loop** block. Set **Loop Variable** to `jobs_list_extraction_output.jobs`. Enable **Continue on Failure** and **Next Loop on Failure**. Inside the loop, add six blocks in order: **Go to URL** (job page), **Extraction** (job details), **Action** (click Apply), **Extraction** (form questions), **Text Prompt** (generate answers), **Navigation** (fill and submit the form).
Save this complete definition to `job-application-workflow.yaml` (or `.json`) before running.
```json JSON theme={null}
{
"title": "Search and Apply for Jobs Workflow",
"description": "Search for jobs on any portal, extract listings, generate tailored answers with AI, and submit applications automatically.",
"proxy_location": "RESIDENTIAL",
"workflow_definition": {
"version": 1,
"parameters": [
{ "key": "resume", "parameter_type": "workflow", "workflow_parameter_type": "file_url" },
{ "key": "credentials", "parameter_type": "workflow", "workflow_parameter_type": "credential_id", "default_value": "your-credential-id" },
{ "key": "job_portal_url", "description": "URL of the job portal", "parameter_type": "workflow", "workflow_parameter_type": "string" }
],
"blocks": [
{
"block_type": "pdf_parser",
"label": "parsed_resume",
"file_url": "{{ resume }}"
},
{
"block_type": "login",
"label": "login_to_portal",
"url": "{{ job_portal_url }}",
"title": "login_to_portal",
"parameter_keys": ["credentials"],
"navigation_goal": "Log in using the provided credentials.\nHandle any cookie consent popups.\nCOMPLETE when on the account dashboard or orders page.",
"max_retries": 0,
"engine": "skyvern-1.0"
},
{
"block_type": "navigation",
"label": "search_for_job",
"url": "",
"title": "search_for_job",
"engine": "skyvern-1.0",
"navigation_goal": "Search for a relevant job based on the parsed resume: {{parsed_resume_output}}",
"max_retries": 0
},
{
"block_type": "extraction",
"label": "jobs_list_extraction",
"url": "",
"title": "jobs_list_extraction",
"data_extraction_goal": "Extract all visible job profiles: job page url, title, employer, location, and type (full time, part time, etc)",
"data_schema": {
"jobs": {
"type": "array",
"items": {
"type": "object",
"properties": {
"job_page_url": { "type": "string", "description": "Link to the apply page for the job" },
"title": { "type": "string", "description": "Title of the role offered" },
"employer": { "type": "string", "description": "Name of the company posting the job profile" },
"location": { "type": "string", "description": "Where is the job role based. City and country," },
"type": { "type": "string", "description": "Type for employment: full-time. part-time, contractual, internship etc." }
},
"required": ["job_page_url", "title", "employer", "location"]
}
}
},
"max_retries": 0,
"engine": "skyvern-1.0"
},
{
"block_type": "for_loop",
"label": "for_each_job",
"loop_variable_reference": "{{jobs_list_extraction_output.jobs}}",
"continue_on_failure": true,
"next_loop_on_failure": true,
"complete_if_empty": true,
"loop_blocks": [
{
"block_type": "goto_url",
"label": "go_to_each_job",
"url": "{{ current_value.job_page_url }}"
},
{
"block_type": "extraction",
"label": "extract_job_detail",
"url": "",
"title": "extract_job_detail",
"data_extraction_goal": "Extract every detail about the job role present on the page",
"max_retries": 0,
"engine": "skyvern-1.0"
},
{
"block_type": "action",
"label": "click_apply",
"url": "",
"title": "click_apply",
"navigation_goal": "Find Apply button and click it.\n\nCOMPLETE when the job application is visible on the screen",
"max_retries": 0,
"engine": "skyvern-1.0"
},
{
"block_type": "extraction",
"label": "extract_questions",
"url": "",
"title": "extract_questions",
"data_extraction_goal": "Extract every question in the job application form as a list",
"max_retries": 0,
"engine": "skyvern-1.0"
},
{
"block_type": "text_prompt",
"label": "answer_form_questions",
"prompt": "Given:\nresume: {{resume}}\nparsed resume: {{parsed_resume_output}}\ninformation about the job profile: {{extract_job_detail_output}}\napplication form questions: {{extract_questions_output}}\n\nYou are applying for {{ current_value.title }} at {{ current_value.employer }}.\n\nWrite thoughtful and impressive answers to each question using the information from resume and parsed resume output."
},
{
"block_type": "navigation",
"label": "apply_to_job",
"url": "",
"title": "apply_to_job",
"engine": "skyvern-1.0",
"navigation_goal": "Given:\n{{answer_form_questions_output}}\n\nFill out all of the form fields, including the optional fields.\n\nIf you dont know the answer to an optional question, leave it blank. If you dont know the answer to a required question such as referral name put N/A or something equivalent.\n\nCOMPLETE when the application form has been successfully submitted.\n\nMore context:\nresume: {{resume}}\nperson_information: {{parsed_resume_output}}",
"max_retries": 0
}
]
}
]
}
}
```
```yaml YAML theme={null}
title: Search and Apply for Jobs Workflow
description: "Search for jobs on any portal, extract listings, generate tailored answers with AI, and submit applications automatically."
proxy_location: RESIDENTIAL
workflow_definition:
version: 1
parameters:
- key: resume
parameter_type: workflow
workflow_parameter_type: file_url
- key: credentials
parameter_type: workflow
workflow_parameter_type: credential_id
default_value: your-credential-id # <-- replace this
- key: job_portal_url
description: URL of the job portal
parameter_type: workflow
workflow_parameter_type: string
blocks:
- block_type: pdf_parser
label: parsed_resume
file_url: "{{ resume }}"
- block_type: login
label: login_to_portal
url: "{{ job_portal_url }}"
title: login_to_portal
parameter_keys:
- credentials
navigation_goal: |
Log in using the provided credentials.
Handle any cookie consent popups.
COMPLETE when on the account dashboard or orders page.
max_retries: 0
engine: skyvern-1.0
- block_type: navigation
label: search_for_job
url: ""
title: search_for_job
engine: skyvern-1.0
navigation_goal: "Search for a relevant job based on the parsed resume: {{parsed_resume_output}}"
max_retries: 0
- block_type: extraction
label: jobs_list_extraction
url: ""
title: jobs_list_extraction
data_extraction_goal: "Extract all visible job profiles: job page url, title, employer, location, and type (full time, part time, etc)"
data_schema:
jobs:
type: array
items:
type: object
properties:
job_page_url:
type: string
description: Link to the apply page for the job
title:
type: string
description: Title of the role offered
employer:
type: string
description: Name of the company posting the job profile
location:
type: string
description: Where is the job role based. City and country,
type:
type: string
description: "Type for employment: full-time. part-time, contractual, internship etc."
required:
- job_page_url
- title
- employer
- location
max_retries: 0
engine: skyvern-1.0
- block_type: for_loop
label: for_each_job
loop_variable_reference: "{{jobs_list_extraction_output.jobs}}"
continue_on_failure: true
next_loop_on_failure: true
complete_if_empty: true
loop_blocks:
- block_type: goto_url
label: go_to_each_job
url: "{{ current_value.job_page_url }}"
- block_type: extraction
label: extract_job_detail
url: ""
title: extract_job_detail
data_extraction_goal: Extract every detail about the job role present on the page
max_retries: 0
engine: skyvern-1.0
- block_type: action
label: click_apply
url: ""
title: click_apply
navigation_goal: |
Find Apply button and click it.
COMPLETE when the job application is visible on the screen
max_retries: 0
engine: skyvern-1.0
- block_type: extraction
label: extract_questions
url: ""
title: extract_questions
data_extraction_goal: Extract every question in the job application form as a list
max_retries: 0
engine: skyvern-1.0
- block_type: text_prompt
label: answer_form_questions
prompt: |
Given:
resume: {{resume}}
parsed resume: {{parsed_resume_output}}
information about the job profile: {{extract_job_detail_output}}
application form questions: {{extract_questions_output}}
You are applying for {{ current_value.title }} at {{ current_value.employer }}.
Write thoughtful and impressive answers to each question using the information from resume and parsed resume output.
- block_type: navigation
label: apply_to_job
url: ""
title: apply_to_job
engine: skyvern-1.0
navigation_goal: |
Given:
{{answer_form_questions_output}}
Fill out all of the form fields, including the optional fields.
If you dont know the answer to an optional question, leave it blank. If you dont know the answer to a required question such as referral name put N/A or something equivalent.
COMPLETE when the application form has been successfully submitted.
More context:
resume: {{resume}}
person_information: {{parsed_resume_output}}
max_retries: 0
```
***
## Step 4: Run and monitor
Create the agent from your definition file and execute it.
Click **Run** in the agent editor. Fill in the parameters:
* **resume**: URL to your resume PDF
* **job\_portal\_url**: `https://job-stash.vercel.app`
* **credentials**: Select the `Job Stash` credential
Watch the run in real time. Each block shows its status as it executes. The for loop will iterate over each job posting, and you can see the AI filling out application forms in the browser recording.
```python Python theme={null}
import os
import asyncio
from skyvern import Skyvern
async def main():
client = Skyvern(api_key=os.getenv("SKYVERN_API_KEY"))
# Create workflow from YAML file
workflow = await client.create_workflow(
yaml_definition=open("job-application-workflow.yaml").read()
)
print(f"Created workflow: {workflow.workflow_permanent_id}")
# Run the workflow
run = await client.run_workflow(
workflow_id=workflow.workflow_permanent_id,
parameters={
"resume": "https://your-resume-url.com/resume.pdf", # <-- replace this
"job_portal_url": "https://job-stash.vercel.app"
}
)
print(f"Started run: {run.run_id}")
# Poll for completion
while True:
result = await client.get_run(run.run_id)
if result.status in ["completed", "failed", "terminated"]:
break
print(f"Status: {result.status}")
await asyncio.sleep(10)
print(f"Final status: {result.status}")
if result.status == "completed":
print("Job applications submitted successfully")
asyncio.run(main())
```
```typescript TypeScript theme={null}
import { SkyvernClient } from "@skyvern/client";
import * as fs from "fs";
async function main() {
const client = new SkyvernClient({
apiKey: process.env.SKYVERN_API_KEY,
});
// Create workflow from YAML file
const workflow = await client.createWorkflow({
body: {
yaml_definition: fs.readFileSync("job-application-workflow.yaml", "utf-8"),
},
});
console.log(`Created workflow: ${workflow.workflow_permanent_id}`);
// Run the workflow
const run = await client.runWorkflow({
body: {
workflow_id: workflow.workflow_permanent_id,
parameters: {
resume: "https://your-resume-url.com/resume.pdf", // <-- replace this
job_portal_url: "https://job-stash.vercel.app",
},
},
});
console.log(`Started run: ${run.run_id}`);
// Poll for completion
while (true) {
const result = await client.getRun(run.run_id);
if (["completed", "failed", "terminated"].includes(result.status)) {
console.log(`Final status: ${result.status}`);
if (result.status === "completed") {
console.log("Job applications submitted successfully");
}
break;
}
console.log(`Status: ${result.status}`);
await new Promise((r) => setTimeout(r, 10000));
}
}
main();
```
```bash cURL theme={null}
# Create workflow
WORKFLOW=$(curl -s -X POST "https://api.skyvern.com/v1/workflows" \
-H "x-api-key: $SKYVERN_API_KEY" \
-H "Content-Type: application/json" \
-d "{\"yaml_definition\": $(cat job-application-workflow.yaml | jq -Rs .)}")
WORKFLOW_ID=$(echo "$WORKFLOW" | jq -r '.workflow_permanent_id')
echo "Created workflow: $WORKFLOW_ID"
# Run workflow (replace resume URL with your own)
RUN=$(curl -s -X POST "https://api.skyvern.com/v1/run/workflows" \
-H "x-api-key: $SKYVERN_API_KEY" \
-H "Content-Type: application/json" \
-d "{
\"workflow_id\": \"$WORKFLOW_ID\",
\"parameters\": {
\"resume\": \"https://your-resume-url.com/resume.pdf\",
\"job_portal_url\": \"https://job-stash.vercel.app\"
}
}")
RUN_ID=$(echo "$RUN" | jq -r '.run_id')
echo "Started run: $RUN_ID"
# Poll for completion
while true; do
RESULT=$(curl -s "https://api.skyvern.com/v1/runs/$RUN_ID" \
-H "x-api-key: $SKYVERN_API_KEY")
STATUS=$(echo "$RESULT" | jq -r '.status')
echo "Status: $STATUS"
if [[ "$STATUS" == "completed" || "$STATUS" == "failed" || "$STATUS" == "terminated" ]]; then
echo "Workflow finished with status: $STATUS"
break
fi
sleep 10
done
```
***
## Resources
Complete parameter reference for all block types
Securely store and use login credentials
Upload and parse files in agents
Handle failures and retries in production