An AI-powered diagnostic and optimization agent that translates passive experience into highly-quantified achievements designed to bypass applicant tracking systems.
Install & Download
1. ClawHub CLI
The fastest way to install a skill directly from the registry.
npx clawhub@latest install mimo-resume-optimizer
2. Manual Installation
Copy the skill folder to one of these locations
~/.openclaw/skills/ <project>/skills/ Priority: Workspace > Local > Bundled
3. Prompt Installation
Copy this prompt to OpenClaw to install it automatically.
Help me install mimo-resume-optimizer using Clawhub. If Clawhub is not installed, install it first (npm i -g clawhub).
Prefer to download?
Get the raw skill files in a ZIP archive.
What is Resume Optimizer?
The Resume Optimizer is an advanced AI agent designed to overhaul underperforming resumes and align them with modern hiring criteria. This agent specializes in converting generic, duty-focused job descriptions into metric-driven achievements using the STAR (Situation, Task, Action, Result) methodology. By leveraging this tool among your collection of Openclaw Skills, you can automatically scan target Job Descriptions, inject high-impact industry keywords, and generate ATS-compliant CVs that appeal to both automated parsers and human recruiters.
Whether you are a fresh graduate, an industry veteran, or a career changer, the Resume Optimizer ensures your experience is formatted, prioritized, and localized correctly. It balances regional requirements—such as omitting personal demographics for US resumes while adapting to European or Chinese CV standards—ensuring your application matches standard local protocols.
Resume Optimizer Use Cases
- ATS Optimization: Modifying resume layouts, fonts, and structures to bypass automated applicant tracking systems without parsing errors.
- Quantifying Achievements: Converting passive 'responsible for' bullet points into highly quantifiable statements highlighting metrics, scale, and specific business impact.
- Target Job Description Alignment: Scanning specialized job descriptions to extract required keywords and re-prioritizing resume sections to match specific target roles.
- Multilingual & Localized Job Hunting: Generating polished Chinese and English CVs adjusted to region-specific rules, such as photo and age policies.
- LinkedIn Profile Polishing: Extracting core highlights from optimized resumes to construct an engaging, searchable LinkedIn page.
How Resume Optimizer Works
- Resume Diagnosis: The agent performs a complete structural and content audit, checking parsing compatibility, keyword density, and overall impact, generating an actionable diagnostic score out of 10.
- Target Role Analysis: You provide the target Job Description, and the agent identifies must-have technical/soft skills, extracts keywords, and determines a matching strategy.
- Content & Achievement Optimization: The agent rewrites professional experience using the STAR framework, embedding key industry terms and maintaining a natural 2-3% keyword density.
- Structural Restructuring: Modules are rearranged based on seniority and strategy, placing skills first for technical roles, or putting transferable skills first for career pivots.
- ATS Verification & Formatting: Text is formatted to prevent parsing issues, utilizing standard fonts, standardized headings, and avoiding problematic elements like tables and text boxes.
- Final Output & Delivery: The agent delivers a clean, side-by-side original-versus-optimized comparison with reasoning, a final polished text version, and an optional custom cover letter.
Resume Optimizer Setup
To run this resume-optimizer agent, you can configure it via your workflow runner or execution environment compatible with Openclaw Skills.
Ensure your agent system has access to the skill definition file. You can load and call the optimizer by specifying its trigger commands in your developer setup:
# Example of initializing the skill within your local environment
openclaw install resume-optimizer
Provide the agent with your current resume in markdown or plain text, along with target Job Descriptions to initiate the step-by-step diagnostic workflow.
Resume Optimizer Data Schema & Taxonomy
The Resume Optimizer produces structured reports detailing the entire optimization pipeline. The generated report follows this diagnostic and content schema:
| Section | Description | Key Fields |
|---|---|---|
| Diagnostic Details | Scores out of 10 on structure, content, metrics, ATS, and keyword match. | StructureScore, ContentScore, MetricsScore, ATSScore, KeywordScore |
| Core Changes | Direct side-by-side comparison matrix with modification reasons. | OriginalText, OptimizedText, ReasonForChange |
| Keyword Matching | Exact statistics of target versus matched keywords and suggested additions. | MatchRatio, NewKeywords, DensityPercentage |
| Optimized Resume | The ready-to-use polished copy of the candidate's CV. | FullResumeText |
| Additional Suggestions | Complementary advice on LinkedIn updates, application timing, and cover letters. | LinkedInTips, ApplicationStrategy, CoverLetterTemplate |
Resume Optimizer Advanced Features
- STAR Method Engine: Automatically breaks down dry descriptions into distinct Situation, Task, Action, and Result outputs.
- Localized Compliance Engine: Dynamically shifts resume guidelines depending on geographical markets such as US, China, and Europe.
- ATS-Safe Guardrails: Guarantees zero compatibility issues by rejecting non-standard elements like embedded tables, complex graphics, and non-supported fonts.
- Custom Pivot Strategies: Supports different optimization modes including Match-Oriented, Potential-Oriented, and Transformation-Oriented profiles.
- Zero-Hallucination Integrity: Enforces strict verification boundaries ensuring achievements are polished and quantified without fabricating false work history.
- Complementary Resource Generation: Integrates seamlessly with other Openclaw Skills to produce tailor-made cover letters and LinkedIn-specific summaries alongside standard resume outputs.
SKILL.md
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