# CV Optimizer (`parseforge/cv-optimizer`) Actor

Reviews any resume alongside its target job description and serves up clear guidance that hiring teams can trust. Instead of rewriting documents manually, you get verdicts, structure feedback, action items, and ready-to-use rewrites that stay faithful to the original text.

- **URL**: https://apify.com/parseforge/cv-optimizer.md
- **Developed by:** [ParseForge](https://apify.com/parseforge) (community)
- **Categories:** AI, Jobs, Other
- **Stats:** 58 total users, 7 monthly users, 100.0% runs succeeded, 1 bookmarks
- **User rating**: 5.00 out of 5 stars

## Pricing

Pay per event

This Actor is paid per event. You are not charged for the Apify platform usage, but only a fixed price for specific events.
Since this Actor supports Apify Store discounts, the price gets lower the higher subscription plan you have.

Learn more: https://docs.apify.com/platform/actors/running/actors-in-store#pay-per-event

## What's an Apify Actor?

Actors are a software tools running on the Apify platform, for all kinds of web data extraction and automation use cases.
In Batch mode, an Actor accepts a well-defined JSON input, performs an action which can take anything from a few seconds to a few hours,
and optionally produces a well-defined JSON output, datasets with results, or files in key-value store.
In Standby mode, an Actor provides a web server which can be used as a website, API, or an MCP server.
Actors are written with capital "A".

## How to integrate an Actor?

If asked about integration, you help developers integrate Actors into their projects.
You adapt to their stack and deliver integrations that are safe, well-documented, and production-ready.
The best way to integrate Actors is as follows.

In JavaScript/TypeScript projects, use official [JavaScript/TypeScript client](https://docs.apify.com/api/client/js.md):

```bash
npm install apify-client
```

In Python projects, use official [Python client library](https://docs.apify.com/api/client/python.md):

```bash
pip install apify-client
```

In shell scripts, use [Apify CLI](https://docs.apify.com/cli/docs.md):

````bash
# MacOS / Linux
curl -fsSL https://apify.com/install-cli.sh | bash
# Windows
irm https://apify.com/install-cli.ps1 | iex
```bash

In AI frameworks, you might use the [Apify MCP server](https://docs.apify.com/platform/integrations/mcp.md).

If your project is in a different language, use the [REST API](https://docs.apify.com/api/v2.md).

For usage examples, see the [API](#api) section below.

For more details, see Apify documentation as [Markdown index](https://docs.apify.com/llms.txt) and [Markdown full-text](https://docs.apify.com/llms-full.txt).


# README

![ParseForge Banner](https://raw.githubusercontent.com/ParseForge/apify-assets/main/banner.jpg)

## 📄 CV Optimizer

> 🚀 Upload your resume and a job description, get an AI-optimized version with keyword matching, tone adjustment, and a match score in seconds. No design tools needed.

> 🕒 Last updated: 2026-04-23


<table><tr>
<td style="border-left:4px solid #0F766E;padding:12px 16px;font-weight:600">Pull structured records from CV Optimizer — clean fields ready as CSV, JSON, JSONL, Excel, or XML for downstream pipelines.</td>
</tr></table>

##### Copy to your AI assistant

Copy this block into ChatGPT, Claude, Cursor, or any LLM to start using this actor.

````

parseforge/cv-optimizer on Apify. Call: ApifyClient("TOKEN").actor("parseforge/cv-optimizer").call(run\_input={...}), then client.dataset(run\["defaultDatasetId"]).list\_items().items for results. Key inputs: cvFile (array), cvText (string, default "Jordan Perez | Lima, Peru | jordan.perez@email.com | +51 99), jobTitle (string, default "Operations Manager"), jobDescription (string, default "We are looking for an Operations Manager experienced in cro), tone (string, default "professional"), formatStyle (string, default "hybrid"). Full actor spec: fetch build via GET https://api.apify.com/v2/acts/parseforge~cv-optimizer (Bearer TOKEN). Get token: https://console.apify.com/account/integrations

````

CV Optimizer analyzes your resume against a specific job posting and produces a tailored version. You can upload a PDF or DOCX file, or paste your resume text directly. Provide the target job title and description, and the AI rewrites sections to match the role's keywords, requirements, and preferred tone. Each result includes the optimized CV text, a match score, lists of matched and missing keywords, and specific improvement suggestions.

Job seekers use it to tailor resumes for each application without spending 30 minutes per version. Career coaches scale their feedback with data-driven keyword analysis. Recruitment agencies batch-optimize candidate profiles before client submissions. If you want to know exactly which keywords a job posting expects and how well your resume covers them, this actor gives you that answer in seconds.

| Target | Resume optimization (AI-powered) |
|--------|-------------------------------|
| Use Cases | Resume tailoring, keyword gap analysis, ATS optimization, batch resume processing |

---

### 📋 What it does

- 📄 **Flexible input.** Upload a PDF/DOCX resume or paste text directly.
- 🎯 **Job-specific matching.** Aligns your CV with the exact keywords and requirements from a job posting.
- 📊 **Match scoring.** Quantitative percentage showing how well your resume fits the role.
- 📝 **Tone control.** Choose professional, friendly, executive, or creative tone for the output.
- 💡 **Actionable suggestions.** Specific recommendations on what to add, remove, or rephrase.

Each result includes the full optimized CV text, a match score, matched keywords, missing keywords, and a list of improvement suggestions you can act on immediately.

> 💡 **Why it matters:** Tailoring a resume for each job application takes 30 to 60 minutes manually. This actor handles keyword alignment, tone adjustment, and formatting in seconds.

---

### 🎬 Full Demo

_🚧 Coming soon: a 3-minute walkthrough showing how to go from sign-up to a downloaded dataset._

---

### ⚙️ Input

<table>
<thead>
<tr><th>Input</th><th>Type</th><th>Default</th><th>Behavior</th></tr>
</thead>
<tbody>
<tr><td>cvFile</td><td>file upload</td><td>-</td><td>Upload a PDF or DOCX resume. Use this or cvText, not both.</td></tr>
<tr><td>cvText</td><td>string</td><td>-</td><td>Paste resume text directly when you cannot upload a file.</td></tr>
<tr><td>jobTitle</td><td>string</td><td>-</td><td>Target job title (e.g. "Operations Manager"). Required.</td></tr>
<tr><td>jobDescription</td><td>string</td><td>-</td><td>Full job posting text for keyword matching. Required.</td></tr>
<tr><td>tone</td><td>string</td><td>"professional"</td><td>Output tone: professional, friendly, executive, or creative.</td></tr>
<tr><td>formatStyle</td><td>string</td><td>"hybrid"</td><td>Resume structure: chronological, functional, or hybrid.</td></tr>
<tr><td>keywords</td><td>array</td><td>-</td><td>Optional keywords or phrases to emphasize in the optimized CV.</td></tr>
<tr><td>creativityLevel</td><td>string</td><td>"balanced"</td><td>How closely to stick to the original: precise, balanced, or creative.</td></tr>
</tbody>
</table>

**Example: optimize for an Operations Manager role.**

```json
{
  "cvText": "Jordan Perez | Lima, Peru | jordan.perez@email.com. Operations analyst with 3 years coordinating cross-functional projects...",
  "jobTitle": "Operations Manager",
  "jobDescription": "We are looking for an Operations Manager experienced in cross-functional leadership, process optimization, and delivering measurable cost reductions.",
  "tone": "professional",
  "keywords": ["process optimization", "cross-functional leadership", "cost reduction"]
}
````

**Example: creative rewrite for a marketing role.**

```json
{
  "cvText": "Sarah Lee | NYC | sarah@email.com. Marketing coordinator with 4 years in digital campaigns...",
  "jobTitle": "Senior Marketing Manager",
  "jobDescription": "Lead brand strategy, manage paid media budgets, oversee content creation, and drive customer acquisition.",
  "tone": "creative",
  "creativityLevel": "creative",
  "formatStyle": "functional"
}
```

> ⚠️ **Good to Know:** For best results, paste the full job description including requirements, qualifications, and preferred skills. The AI uses every detail to identify which keywords and phrases to emphasize in your CV.

***

### 📊 Output

Each record contains **6+ fields**. Download as CSV, Excel, JSON, or XML.

#### 🧾 Schema

| Field | Type | Example |
|---|---|---|
| 📄 optimizedCv | string | `"Jordan Perez\nOperations Manager..."` |
| 📊 matchScore | number | `78` |
| 🎯 keywordsMatched | array | `["Python", "AWS"]` |
| 🎯 keywordsMissing | array | `["microservices", "CI/CD"]` |
| 💡 suggestions | array | `["Add microservices to skills section"]` |
| 🕒 processedAt | string | `"2026-04-17T00:00:00.000Z"` |

#### 📦 Sample records

<details>
<summary><strong>📄 Operations Manager optimization (78% match)</strong></summary>

```json
{
  "optimizedCv": "Jordan Perez\nOperations Manager | Process Optimization, Cross-Functional Leadership\n\nProfessional Summary:\nOperations leader with 3+ years driving cross-functional initiatives, process mapping, and KPI dashboard implementation that cut cycle times by 18%...",
  "matchScore": 78,
  "keywordsMatched": ["cross-functional leadership", "process optimization", "KPI", "cost reduction"],
  "keywordsMissing": ["continuous improvement", "supply chain"],
  "suggestions": ["Add 'continuous improvement' to your summary", "Quantify cost reduction achievements with dollar amounts"],
  "processedAt": "2026-04-17T00:00:00.000Z"
}
```

</details>

<details>
<summary><strong>📄 Software Engineer optimization (42% match)</strong></summary>

```json
{
  "optimizedCv": "Jane Doe\nSoftware Engineer | Python, REST APIs\n\nProfessional Summary:\nSoftware developer with 2 years building web applications...",
  "matchScore": 42,
  "keywordsMatched": ["Python", "REST APIs"],
  "keywordsMissing": ["Kubernetes", "CI/CD", "microservices", "AWS", "Terraform"],
  "suggestions": ["Your CV lacks 5 key terms from the job posting", "Add a Technical Skills section listing cloud platforms", "Include CI/CD pipeline experience"],
  "processedAt": "2026-04-17T00:00:05.000Z"
}
```

</details>

<details>
<summary><strong>📄 DevOps Engineer optimization (95% match)</strong></summary>

```json
{
  "optimizedCv": "Alex Chen\nDevOps Engineer | Terraform, Docker, AWS, Kubernetes\n\nProfessional Summary:\nDevOps engineer with 6 years automating infrastructure...",
  "matchScore": 95,
  "keywordsMatched": ["Terraform", "Docker", "AWS", "Kubernetes", "CI/CD", "Linux", "monitoring"],
  "keywordsMissing": [],
  "suggestions": ["Minor tone adjustment for executive audience"],
  "processedAt": "2026-04-17T00:00:10.000Z"
}
```

</details>

***

### ✨ Why choose this Actor

| | Capability |
|---|---|
| 🎯 | **Job-specific optimization.** Aligns your CV with the exact requirements from a job posting. |
| 🔍 | **Keyword gap analysis.** Shows which terms you have and which ones are missing. |
| 📊 | **Quantitative match score.** Know your fit percentage before you apply. |
| 📝 | **Four tone options.** Professional, friendly, executive, or creative output. |
| 🎚️ | **Creativity control.** Choose how closely the AI sticks to your original text. |
| ⚡ | **Seconds, not hours.** Results arrive in seconds instead of 30-60 minutes of manual editing. |
| 📄 | **File or text input.** Upload PDF/DOCX or paste text directly. |

> Studies show that tailored resumes are 2-3x more likely to pass ATS screening systems. Automated keyword matching ensures your CV speaks the same language as the job posting.

***

### 📈 How it compares to alternatives

| Approach | Cost | Coverage | Refresh | Setup |
|---|---|---|---|---|
| **⭐ CV Optimizer** *(this Actor)* | $5 free credit, then pay-per-use | Per-posting optimization | **On demand** | ⚡ 2 min |
| Manual resume tailoring | Free (your time) | One resume at a time | 30-60 min per job | N/A |
| Professional resume services | $50-300 per resume | One version | Days turnaround | Per resume |
| Resume builder tools | $10-30/month | Template-based | Minutes | Learning curve |

Choose this actor when you need per-posting resume optimization with keyword analysis and match scoring, delivered in seconds.

***

### 🚀 How to use

1. 📝 **Sign up.** [Create a free account with $5 credit](https://console.apify.com/sign-up?fpr=vmoqkp) (takes 2 minutes).
2. 🌐 **Open the Actor.** Go to the CV Optimizer page on the Apify Store.
3. 🎯 **Set input.** Upload your resume or paste text. Add the job title and description.
4. 🚀 **Run it.** Click **Start** and let the AI optimize your resume.
5. 📥 **Download.** Grab your optimized CV and suggestions from the **Dataset** tab.

> ⏱️ Total time from signup to optimized resume: **3-5 minutes.** No coding required.

***

### 💼 Business use cases

<table>
<tr>
<td width="50%" valign="top">

#### 🎓 Job Seekers

- Tailor your resume for each application in seconds
- Identify missing keywords before you submit
- Get a match score to gauge your fit
- Optimize tone for different industries and levels

</td>
<td width="50%" valign="top">

#### 🏢 Recruitment and HR

- Batch-optimize candidate resumes for open roles
- Standardize resume formatting across applicants
- Score candidate fit against job descriptions
- Build ATS-friendly resume versions at scale

</td>
</tr>
<tr>
<td width="50%" valign="top">

#### 📊 Career Coaching

- Provide data-driven resume feedback to clients
- Show exactly which keywords to add or remove
- Quantify resume-job fit with match scores
- Scale your coaching practice with automated optimization

</td>
<td width="50%" valign="top">

#### 🏢 Staffing Agencies

- Tailor candidate profiles for client submissions
- Match resumes to multiple job descriptions quickly
- Standardize presentation across all candidates
- Reduce time-to-submit for open requisitions

</td>
</tr>
</table>

***

***

### 🌟 Beyond business use cases

Data like this powers more than commercial workflows. The same structured records support research, education, civic projects, and personal initiatives.

<table>
<tr>
<td width="50%">

#### 🎓 Research and academia

- Empirical datasets for papers, thesis work, and coursework
- Longitudinal studies tracking changes across snapshots
- Reproducible research with cited, versioned data pulls
- Classroom exercises on data analysis and ethical scraping

</td>
<td width="50%">

#### 🎨 Personal and creative

- Side projects, portfolio demos, and indie app launches
- Data visualizations, dashboards, and infographics
- Content research for bloggers, YouTubers, and podcasters
- Hobbyist collections and personal trackers

</td>
</tr>
<tr>
<td width="50%">

#### 🤝 Non-profit and civic

- Transparency reporting and accountability projects
- Advocacy campaigns backed by public-interest data
- Community-run databases for local issues
- Investigative journalism on public records

</td>
<td width="50%">

#### 🧪 Experimentation

- Prototype AI and machine-learning pipelines with real data
- Validate product-market hypotheses before engineering spend
- Train small domain-specific models on niche corpora
- Test dashboard concepts with live input

</td>
</tr>
</table>

### 🤖 Ask an AI assistant about this scraper

Open a ready-to-send prompt about this ParseForge actor in the AI of your choice:

- 💬 [**ChatGPT**](https://chat.openai.com/?q=How%20do%20I%20use%20the%20CV%20Optimizer%20by%20ParseForge%20on%20Apify%3F%20Show%20me%20input%20examples%2C%20output%20fields%2C%20common%20use%20cases%2C%20and%20how%20to%20integrate%20it%20into%20a%20workflow.)
- 🧠 [**Claude**](https://claude.ai/new?q=How%20do%20I%20use%20the%20CV%20Optimizer%20by%20ParseForge%20on%20Apify%3F%20Show%20me%20input%20examples%2C%20output%20fields%2C%20common%20use%20cases%2C%20and%20how%20to%20integrate%20it%20into%20a%20workflow.)
- 🔍 [**Perplexity**](https://perplexity.ai/search?q=How%20do%20I%20use%20the%20CV%20Optimizer%20by%20ParseForge%20on%20Apify%3F%20Show%20me%20input%20examples%2C%20output%20fields%2C%20common%20use%20cases%2C%20and%20how%20to%20integrate%20it%20into%20a%20workflow.)
- 🅒 [**Copilot**](https://copilot.microsoft.com/?q=How%20do%20I%20use%20the%20CV%20Optimizer%20by%20ParseForge%20on%20Apify%3F%20Show%20me%20input%20examples%2C%20output%20fields%2C%20common%20use%20cases%2C%20and%20how%20to%20integrate%20it%20into%20a%20workflow.)

### ❓ Frequently Asked Questions

<details>
<summary><b>💳 Do I need a paid Apify plan to run this actor?</b></summary>

No. You can start right now on the free Apify plan, which includes **$5 in free monthly credit**. That is enough to run this actor several times and explore the output before committing to anything. Paid plans unlock higher limits, more concurrent runs, and larger datasets. [Create a free Apify account here](https://console.apify.com/sign-up?fpr=vmoqkp) to get started.

</details>

<details>
<summary><b>🚨 What happens if my run fails or returns no results?</b></summary>

Failed runs are not charged. If the source site changes, proxies get rate-limited, or a specific input matches nothing, re-run the actor or open our [contact form](https://tally.so/r/BzdKgA) and we will investigate. You can also check the run log in the Apify console to see why the run stopped.

</details>

<details>
<summary><b>📏 How many items can I scrape per run?</b></summary>

Free users are limited to **10 items per run** so you can preview the output and confirm the actor works for your use case. Paid users can raise maxItems up to **1,000,000** per run. [Upgrade here](https://console.apify.com/sign-up?fpr=vmoqkp) if you need full scale.

</details>

<details>
<summary><b>🕒 How fresh is the data?</b></summary>

Every run fetches live data at the moment of execution. There is no cache or delay: the records you get reflect what the source returned at that moment. Schedule the actor to maintain a rolling snapshot of the data you need.

</details>

<details>
<summary><b>🧑‍💻 Can I call this actor from my own code?</b></summary>

Yes. Apify exposes every actor as a REST endpoint and ships first-class SDKs for [Node.js](https://docs.apify.com/sdk/js) and [Python](https://docs.apify.com/sdk/python). You can start a run, read the dataset, and handle webhooks from your own app in a few lines. All you need is your Apify API token.

</details>

<details>
<summary><b>📤 How do I export the data?</b></summary>

Every Apify dataset can be downloaded in one click from the console as CSV, JSON, JSONL, Excel, HTML, XML, or RSS. You can also pull results programmatically via the [Apify API](https://docs.apify.com/api/v2) or stream them into BigQuery, S3, and other destinations through built-in integrations.

</details>

<details>
<summary><b>📅 Can I schedule the actor to run automatically?</b></summary>

Yes. Use the Apify scheduler to run the actor on any cadence, from hourly to monthly. Results are saved to your dataset and can be delivered to webhooks, email, Slack, cloud storage, or automation tools such as Zapier and Make.

***

</details>

### 🔌 Automating CV Optimizer

Control the optimizer programmatically for batch processing and pipeline integrations:

- 🟢 **Node.js.** Install the apify-client NPM package.
- 🐍 **Python.** Use the apify-client PyPI package.
- 📚 See the [Apify API documentation](https://docs.apify.com/api/v2) for full details.

The [Apify Schedules feature](https://docs.apify.com/platform/schedules) lets you trigger this Actor on any cron interval. Useful for agencies that process new candidate resumes on a daily basis.

### 🔌 Integrate with any app

CV Optimizer connects to any cloud service via [Apify integrations](https://apify.com/integrations):

- [**Make**](https://docs.apify.com/platform/integrations/make) - Automate multi-step workflows
- [**Zapier**](https://docs.apify.com/platform/integrations/zapier) - Connect with 5,000+ apps
- [**Slack**](https://docs.apify.com/platform/integrations/slack) - Get run notifications
- [**Airbyte**](https://docs.apify.com/platform/integrations/airbyte) - Pipe data into your warehouse
- [**GitHub**](https://docs.apify.com/platform/integrations/github) - Trigger runs from commits
- [**Google Drive**](https://docs.apify.com/platform/integrations/drive) - Export datasets straight to Sheets

You can also use webhooks to trigger downstream actions when a run finishes.

***

### 🔗 Recommended Actors

- [**💼 Monster Scraper**](https://apify.com/parseforge/monster-scraper) - Extract job listings from Monster.com
- [**🏢 Glassdoor Scraper**](https://apify.com/parseforge/glassdoor-scraper) - Collect company reviews and salary data
- [**💼 Indeed Scraper**](https://apify.com/parseforge/indeed-scraper) - Scrape job postings from Indeed
- [**📋 Lead Formatter**](https://apify.com/parseforge/lead-formatter) - Format and enrich lead data
- [**🤗 Hugging Face Model Scraper**](https://apify.com/parseforge/hugging-face-model-scraper) - Collect AI model metadata

> 💡 **Pro Tip:** browse the complete [ParseForge collection](https://apify.com/parseforge) for more data scrapers and tools.

***

**🆘 Need Help?** [**Open our contact form**](https://tally.so/r/BzdKgA) to request a new scraper, propose a custom data project, or report an issue.

***

> **⚠️ Disclaimer:** this Actor is an independent tool and is not affiliated with, endorsed by, or sponsored by any employer or job board. All trademarks mentioned are the property of their respective owners.

# Actor input Schema

## `cvFile` (type: `array`):

Upload a PDF or DOCX resume. Choose this option OR paste the resume text below, not both.

## `cvText` (type: `string`):

Optional. Paste the full resume text when you cannot upload a file. Leave this blank if you provide a resume file.

## `jobTitle` (type: `string`):

Target role (e.g., Operations Manager).

## `jobDescription` (type: `string`):

Paste the job description or bullet points describing the role expectations.

## `tone` (type: `string`):

Optional tone guidance for the optimized CV.

## `formatStyle` (type: `string`):

Optionally request a specific resume structure.

## `keywords` (type: `array`):

Optional keywords or phrases to highlight throughout the optimized CV.

## `creativityLevel` (type: `string`):

Choose how closely the AI should stick to the original resume. “Precise” keeps edits minimal, while “Creative” allows bolder rewrites.

## Actor input object example

```json
{
  "cvText": "Jordan Perez | Lima, Peru | jordan.perez@email.com | +51 999 999 999. Operations analyst with 3 years coordinating cross-functional projects, mapping processes, and implementing KPI dashboards that cut cycle times by 18%. Led inventory reconciliation across 12 retail stores (23% fewer discrepancies) and aligned IT, finance, and warehouse teams on order fulfillment SLAs. BBA, Universidad del Pacífico (2019).",
  "jobTitle": "Operations Manager",
  "jobDescription": "We are looking for an Operations Manager experienced in cross-functional leadership, process optimization, and delivering measurable cost reductions. The role coordinates initiatives across teams, implements KPIs, and drives continuous improvement.",
  "tone": "professional",
  "formatStyle": "hybrid",
  "keywords": [
    "process optimization",
    "cross-functional leadership",
    "cost reduction"
  ],
  "creativityLevel": "balanced"
}
```

# Actor output Schema

## `results` (type: `string`):

Complete dataset with all CV optimization results including match verdicts, structure feedback, recommendations, suggested edits, and confidence scores

## `overview` (type: `string`):

Overview view of optimization results with key fields displayed in a table format

# API

You can run this Actor programmatically using our API. Below are code examples in JavaScript, Python, and CLI, as well as the OpenAPI specification and MCP server setup.

## JavaScript example

```javascript
import { ApifyClient } from 'apify-client';

// Initialize the ApifyClient with your Apify API token
// Replace the '<YOUR_API_TOKEN>' with your token
const client = new ApifyClient({
    token: '<YOUR_API_TOKEN>',
});

// Prepare Actor input
const input = {
    "cvText": "Jordan Perez | Lima, Peru | jordan.perez@email.com | +51 999 999 999. Operations analyst with 3 years coordinating cross-functional projects, mapping processes, and implementing KPI dashboards that cut cycle times by 18%. Led inventory reconciliation across 12 retail stores (23% fewer discrepancies) and aligned IT, finance, and warehouse teams on order fulfillment SLAs. BBA, Universidad del Pacífico (2019).",
    "jobTitle": "Operations Manager",
    "jobDescription": "We are looking for an Operations Manager experienced in cross-functional leadership, process optimization, and delivering measurable cost reductions. The role coordinates initiatives across teams, implements KPIs, and drives continuous improvement.",
    "tone": "professional",
    "formatStyle": "hybrid",
    "keywords": [
        "process optimization",
        "cross-functional leadership",
        "cost reduction"
    ],
    "creativityLevel": "balanced"
};

// Run the Actor and wait for it to finish
const run = await client.actor("parseforge/cv-optimizer").call(input);

// Fetch and print Actor results from the run's dataset (if any)
console.log('Results from dataset');
console.log(`💾 Check your data here: https://console.apify.com/storage/datasets/${run.defaultDatasetId}`);
const { items } = await client.dataset(run.defaultDatasetId).listItems();
items.forEach((item) => {
    console.dir(item);
});

// 📚 Want to learn more 📖? Go to → https://docs.apify.com/api/client/js/docs

```

## Python example

```python
from apify_client import ApifyClient

# Initialize the ApifyClient with your Apify API token
# Replace '<YOUR_API_TOKEN>' with your token.
client = ApifyClient("<YOUR_API_TOKEN>")

# Prepare the Actor input
run_input = {
    "cvText": "Jordan Perez | Lima, Peru | jordan.perez@email.com | +51 999 999 999. Operations analyst with 3 years coordinating cross-functional projects, mapping processes, and implementing KPI dashboards that cut cycle times by 18%. Led inventory reconciliation across 12 retail stores (23% fewer discrepancies) and aligned IT, finance, and warehouse teams on order fulfillment SLAs. BBA, Universidad del Pacífico (2019).",
    "jobTitle": "Operations Manager",
    "jobDescription": "We are looking for an Operations Manager experienced in cross-functional leadership, process optimization, and delivering measurable cost reductions. The role coordinates initiatives across teams, implements KPIs, and drives continuous improvement.",
    "tone": "professional",
    "formatStyle": "hybrid",
    "keywords": [
        "process optimization",
        "cross-functional leadership",
        "cost reduction",
    ],
    "creativityLevel": "balanced",
}

# Run the Actor and wait for it to finish
run = client.actor("parseforge/cv-optimizer").call(run_input=run_input)

# Fetch and print Actor results from the run's dataset (if there are any)
print("💾 Check your data here: https://console.apify.com/storage/datasets/" + run["defaultDatasetId"])
for item in client.dataset(run["defaultDatasetId"]).iterate_items():
    print(item)

# 📚 Want to learn more 📖? Go to → https://docs.apify.com/api/client/python/docs/quick-start

```

## CLI example

```bash
echo '{
  "cvText": "Jordan Perez | Lima, Peru | jordan.perez@email.com | +51 999 999 999. Operations analyst with 3 years coordinating cross-functional projects, mapping processes, and implementing KPI dashboards that cut cycle times by 18%. Led inventory reconciliation across 12 retail stores (23% fewer discrepancies) and aligned IT, finance, and warehouse teams on order fulfillment SLAs. BBA, Universidad del Pacífico (2019).",
  "jobTitle": "Operations Manager",
  "jobDescription": "We are looking for an Operations Manager experienced in cross-functional leadership, process optimization, and delivering measurable cost reductions. The role coordinates initiatives across teams, implements KPIs, and drives continuous improvement.",
  "tone": "professional",
  "formatStyle": "hybrid",
  "keywords": [
    "process optimization",
    "cross-functional leadership",
    "cost reduction"
  ],
  "creativityLevel": "balanced"
}' |
apify call parseforge/cv-optimizer --silent --output-dataset

```

## MCP server setup

```json
{
    "mcpServers": {
        "apify": {
            "command": "npx",
            "args": [
                "mcp-remote",
                "https://mcp.apify.com/?tools=parseforge/cv-optimizer",
                "--header",
                "Authorization: Bearer <YOUR_API_TOKEN>"
            ]
        }
    }
}

```

## OpenAPI specification

```json
{
    "openapi": "3.0.1",
    "info": {
        "title": "CV Optimizer",
        "description": "Reviews any resume alongside its target job description and serves up clear guidance that hiring teams can trust. Instead of rewriting documents manually, you get verdicts, structure feedback, action items, and ready-to-use rewrites that stay faithful to the original text.",
        "version": "1.0",
        "x-build-id": "mDxsQE5MOKsM6uRb1"
    },
    "servers": [
        {
            "url": "https://api.apify.com/v2"
        }
    ],
    "paths": {
        "/acts/parseforge~cv-optimizer/run-sync-get-dataset-items": {
            "post": {
                "operationId": "run-sync-get-dataset-items-parseforge-cv-optimizer",
                "x-openai-isConsequential": false,
                "summary": "Executes an Actor, waits for its completion, and returns Actor's dataset items in response.",
                "tags": [
                    "Run Actor"
                ],
                "requestBody": {
                    "required": true,
                    "content": {
                        "application/json": {
                            "schema": {
                                "$ref": "#/components/schemas/inputSchema"
                            }
                        }
                    }
                },
                "parameters": [
                    {
                        "name": "token",
                        "in": "query",
                        "required": true,
                        "schema": {
                            "type": "string"
                        },
                        "description": "Enter your Apify token here"
                    }
                ],
                "responses": {
                    "200": {
                        "description": "OK"
                    }
                }
            }
        },
        "/acts/parseforge~cv-optimizer/runs": {
            "post": {
                "operationId": "runs-sync-parseforge-cv-optimizer",
                "x-openai-isConsequential": false,
                "summary": "Executes an Actor and returns information about the initiated run in response.",
                "tags": [
                    "Run Actor"
                ],
                "requestBody": {
                    "required": true,
                    "content": {
                        "application/json": {
                            "schema": {
                                "$ref": "#/components/schemas/inputSchema"
                            }
                        }
                    }
                },
                "parameters": [
                    {
                        "name": "token",
                        "in": "query",
                        "required": true,
                        "schema": {
                            "type": "string"
                        },
                        "description": "Enter your Apify token here"
                    }
                ],
                "responses": {
                    "200": {
                        "description": "OK",
                        "content": {
                            "application/json": {
                                "schema": {
                                    "$ref": "#/components/schemas/runsResponseSchema"
                                }
                            }
                        }
                    }
                }
            }
        },
        "/acts/parseforge~cv-optimizer/run-sync": {
            "post": {
                "operationId": "run-sync-parseforge-cv-optimizer",
                "x-openai-isConsequential": false,
                "summary": "Executes an Actor, waits for completion, and returns the OUTPUT from Key-value store in response.",
                "tags": [
                    "Run Actor"
                ],
                "requestBody": {
                    "required": true,
                    "content": {
                        "application/json": {
                            "schema": {
                                "$ref": "#/components/schemas/inputSchema"
                            }
                        }
                    }
                },
                "parameters": [
                    {
                        "name": "token",
                        "in": "query",
                        "required": true,
                        "schema": {
                            "type": "string"
                        },
                        "description": "Enter your Apify token here"
                    }
                ],
                "responses": {
                    "200": {
                        "description": "OK"
                    }
                }
            }
        }
    },
    "components": {
        "schemas": {
            "inputSchema": {
                "type": "object",
                "required": [
                    "jobTitle",
                    "jobDescription"
                ],
                "properties": {
                    "cvFile": {
                        "title": "Resume file",
                        "type": "array",
                        "description": "Upload a PDF or DOCX resume. Choose this option OR paste the resume text below, not both.",
                        "items": {
                            "type": "string"
                        }
                    },
                    "cvText": {
                        "title": "Resume text",
                        "type": "string",
                        "description": "Optional. Paste the full resume text when you cannot upload a file. Leave this blank if you provide a resume file."
                    },
                    "jobTitle": {
                        "title": "Job title",
                        "type": "string",
                        "description": "Target role (e.g., Operations Manager)."
                    },
                    "jobDescription": {
                        "title": "Job requirements / description",
                        "type": "string",
                        "description": "Paste the job description or bullet points describing the role expectations."
                    },
                    "tone": {
                        "title": "Preferred tone",
                        "enum": [
                            "professional",
                            "friendly",
                            "executive",
                            "creative"
                        ],
                        "type": "string",
                        "description": "Optional tone guidance for the optimized CV.",
                        "default": "professional"
                    },
                    "formatStyle": {
                        "title": "Format style",
                        "enum": [
                            "chronological",
                            "functional",
                            "hybrid"
                        ],
                        "type": "string",
                        "description": "Optionally request a specific resume structure.",
                        "default": "hybrid"
                    },
                    "keywords": {
                        "title": "Keywords to emphasize",
                        "type": "array",
                        "description": "Optional keywords or phrases to highlight throughout the optimized CV.",
                        "items": {
                            "type": "string"
                        }
                    },
                    "creativityLevel": {
                        "title": "Creativity level",
                        "enum": [
                            "precise",
                            "balanced",
                            "creative"
                        ],
                        "type": "string",
                        "description": "Choose how closely the AI should stick to the original resume. “Precise” keeps edits minimal, while “Creative” allows bolder rewrites.",
                        "default": "balanced"
                    }
                }
            },
            "runsResponseSchema": {
                "type": "object",
                "properties": {
                    "data": {
                        "type": "object",
                        "properties": {
                            "id": {
                                "type": "string"
                            },
                            "actId": {
                                "type": "string"
                            },
                            "userId": {
                                "type": "string"
                            },
                            "startedAt": {
                                "type": "string",
                                "format": "date-time",
                                "example": "2025-01-08T00:00:00.000Z"
                            },
                            "finishedAt": {
                                "type": "string",
                                "format": "date-time",
                                "example": "2025-01-08T00:00:00.000Z"
                            },
                            "status": {
                                "type": "string",
                                "example": "READY"
                            },
                            "meta": {
                                "type": "object",
                                "properties": {
                                    "origin": {
                                        "type": "string",
                                        "example": "API"
                                    },
                                    "userAgent": {
                                        "type": "string"
                                    }
                                }
                            },
                            "stats": {
                                "type": "object",
                                "properties": {
                                    "inputBodyLen": {
                                        "type": "integer",
                                        "example": 2000
                                    },
                                    "rebootCount": {
                                        "type": "integer",
                                        "example": 0
                                    },
                                    "restartCount": {
                                        "type": "integer",
                                        "example": 0
                                    },
                                    "resurrectCount": {
                                        "type": "integer",
                                        "example": 0
                                    },
                                    "computeUnits": {
                                        "type": "integer",
                                        "example": 0
                                    }
                                }
                            },
                            "options": {
                                "type": "object",
                                "properties": {
                                    "build": {
                                        "type": "string",
                                        "example": "latest"
                                    },
                                    "timeoutSecs": {
                                        "type": "integer",
                                        "example": 300
                                    },
                                    "memoryMbytes": {
                                        "type": "integer",
                                        "example": 1024
                                    },
                                    "diskMbytes": {
                                        "type": "integer",
                                        "example": 2048
                                    }
                                }
                            },
                            "buildId": {
                                "type": "string"
                            },
                            "defaultKeyValueStoreId": {
                                "type": "string"
                            },
                            "defaultDatasetId": {
                                "type": "string"
                            },
                            "defaultRequestQueueId": {
                                "type": "string"
                            },
                            "buildNumber": {
                                "type": "string",
                                "example": "1.0.0"
                            },
                            "containerUrl": {
                                "type": "string"
                            },
                            "usage": {
                                "type": "object",
                                "properties": {
                                    "ACTOR_COMPUTE_UNITS": {
                                        "type": "integer",
                                        "example": 0
                                    },
                                    "DATASET_READS": {
                                        "type": "integer",
                                        "example": 0
                                    },
                                    "DATASET_WRITES": {
                                        "type": "integer",
                                        "example": 0
                                    },
                                    "KEY_VALUE_STORE_READS": {
                                        "type": "integer",
                                        "example": 0
                                    },
                                    "KEY_VALUE_STORE_WRITES": {
                                        "type": "integer",
                                        "example": 1
                                    },
                                    "KEY_VALUE_STORE_LISTS": {
                                        "type": "integer",
                                        "example": 0
                                    },
                                    "REQUEST_QUEUE_READS": {
                                        "type": "integer",
                                        "example": 0
                                    },
                                    "REQUEST_QUEUE_WRITES": {
                                        "type": "integer",
                                        "example": 0
                                    },
                                    "DATA_TRANSFER_INTERNAL_GBYTES": {
                                        "type": "integer",
                                        "example": 0
                                    },
                                    "DATA_TRANSFER_EXTERNAL_GBYTES": {
                                        "type": "integer",
                                        "example": 0
                                    },
                                    "PROXY_RESIDENTIAL_TRANSFER_GBYTES": {
                                        "type": "integer",
                                        "example": 0
                                    },
                                    "PROXY_SERPS": {
                                        "type": "integer",
                                        "example": 0
                                    }
                                }
                            },
                            "usageTotalUsd": {
                                "type": "number",
                                "example": 0.00005
                            },
                            "usageUsd": {
                                "type": "object",
                                "properties": {
                                    "ACTOR_COMPUTE_UNITS": {
                                        "type": "integer",
                                        "example": 0
                                    },
                                    "DATASET_READS": {
                                        "type": "integer",
                                        "example": 0
                                    },
                                    "DATASET_WRITES": {
                                        "type": "integer",
                                        "example": 0
                                    },
                                    "KEY_VALUE_STORE_READS": {
                                        "type": "integer",
                                        "example": 0
                                    },
                                    "KEY_VALUE_STORE_WRITES": {
                                        "type": "number",
                                        "example": 0.00005
                                    },
                                    "KEY_VALUE_STORE_LISTS": {
                                        "type": "integer",
                                        "example": 0
                                    },
                                    "REQUEST_QUEUE_READS": {
                                        "type": "integer",
                                        "example": 0
                                    },
                                    "REQUEST_QUEUE_WRITES": {
                                        "type": "integer",
                                        "example": 0
                                    },
                                    "DATA_TRANSFER_INTERNAL_GBYTES": {
                                        "type": "integer",
                                        "example": 0
                                    },
                                    "DATA_TRANSFER_EXTERNAL_GBYTES": {
                                        "type": "integer",
                                        "example": 0
                                    },
                                    "PROXY_RESIDENTIAL_TRANSFER_GBYTES": {
                                        "type": "integer",
                                        "example": 0
                                    },
                                    "PROXY_SERPS": {
                                        "type": "integer",
                                        "example": 0
                                    }
                                }
                            }
                        }
                    }
                }
            }
        }
    }
}
```
