Requirements
- Target platform
- OpenClaw
- Install method
- Manual import
- Extraction
- Extract archive
- Prerequisites
- OpenClaw
- Primary doc
- SKILL.md
Tencent SkillHub ยท Productivity
UK Resume Analyzer & Optimizer
Professional resume analysis and optimization for UK job market. Use when user needs to (1) Analyze resume quality against a job description, (2) Get ATS com...
skill openclawclawhub Free
Professional resume analysis and optimization for UK job market. Use when user needs to (1) Analyze resume quality against a job description, (2) Get ATS com...
โฌ 0 downloads โ
0 stars Unverified but indexed
Install for OpenClaw
Quick setup
- Download the package from Yavira.
- Extract the archive and review SKILL.md first.
- Import or place the package into your OpenClaw setup.
Package facts
- Download mode
- Yavira redirect
- Package format
- ZIP package
- Source platform
- Tencent SkillHub
- What's included
- SKILL.md, scripts/analyze_resume.py, scripts/generate_optimized.py, scripts/parse_resume.py, references/ats_keywords.md, references/resume_templates.md
Validation
- Use the Yavira download entry.
- Review SKILL.md after the package is downloaded.
- Confirm the extracted package contains the expected setup assets.
Install with your agent
Agent handoff
Hand the extracted package to your coding agent with a concrete install brief instead of figuring it out manually.
- Download the package from Yavira.
- Extract it into a folder your agent can access.
- Paste one of the prompts below and point your agent at the extracted folder.
New install
I downloaded a skill package from Yavira. Read SKILL.md from the extracted folder and install it by following the included instructions. Tell me what you changed and call out any manual steps you could not complete.
Upgrade existing
I downloaded an updated skill package from Yavira. Read SKILL.md from the extracted folder, compare it with my current installation, and upgrade it while preserving any custom configuration unless the package docs explicitly say otherwise. Summarize what changed and any follow-up checks I should run.
Trust & source
Release facts
- Source
- Tencent SkillHub
- Verification
- Indexed source record
- Version
- 1.0.0
Provenance
- Publisher
- phonedog
- Source page
- View original listing
- Canonical URL
- Open canonical page
Documentation
Resume Analyzer
Analyze resumes against job descriptions and generate optimized versions with detailed annotations.
When to Use
User provides a resume file (.docx) and wants analysis User provides both resume and JD for matching analysis User wants ATS optimization suggestions User wants quantified achievements and stronger bullet points User wants an optimized version with explanations
Step 1: Load & Parse Resume
Use scripts/parse_resume.py to extract content from .docx: python scripts/parse_resume.py <input.docx> --output parsed_resume.json
Step 2: Five-Dimension Analysis
Run analysis script with JD (if provided): python scripts/analyze_resume.py parsed_resume.json [--jd job_description.txt] --output analysis_report.json The analysis covers: JD Match Score (0-100): Keyword overlap, skills alignment Quantification Score (0-100): Presence of metrics, numbers, percentages Structure Logic (0-100): Section order, readability, hierarchy Language Professionalism (0-100): Action verbs, clarity, conciseness ATS-Friendliness (0-100): Format, keywords, standard sections
Step 3: Interactive Q&A
Present the 5-dimension report and ask follow-up questions: Questions to ask (user can select or type): Which role at [Company X] had the biggest impact? What were the measurable results? Any specific project with quantifiable outcomes (revenue, users, efficiency)? Tools/technologies used that aren't mentioned? Any awards, recognition, or leadership experiences to highlight? Education details: GPA, relevant coursework, projects? Store answers in supplemental_data.json.
Step 4: Generate Optimized Version
python scripts/generate_optimized.py \ parsed_resume.json \ analysis_report.json \ supplemental_data.json \ --output optimized_resume.docx \ --backup original_backup.docx Output files: original_backup.docx: Clean copy of original optimized_resume.docx: Optimized version with Word comments explaining every change
Step 5: Summary Output
Present to user: Original vs Optimized comparison (key changes) Score improvements (Before โ After for each dimension) File locations
CAR Method for Bullet Points
Transform vague descriptions into CAR format: Context: What was the situation? Action: What did YOU specifically do? Result: What was the measurable outcome? Example transformation: โ "Responsible for managing team and improving processes" โ "Led 8-person logistics team (Context), implemented new WSSI forecasting system (Action), reducing stockouts by 35% and saving ยฃ120K annually (Result)"
ATS Optimization Rules
Use standard section headers: Experience, Education, Skills (not fancy variations) Include full keywords from JD: If JD says "Supply Chain Optimization", use exact phrase Avoid tables, headers/footers, graphics: ATS may not parse them File format: .docx preferred over PDF for ATS
Quantification Guidelines
Always seek numbers: Revenue: ยฃX, $X, % growth Scale: X team members, X regions, X SKUs Efficiency: X% faster, X% cost reduction, X hours saved Impact: X customers, X users, X% satisfaction improvement
Reference Materials
ATS Keywords: See references/ats_keywords.md for industry-specific keyword lists Resume Templates: See references/resume_templates.md for UK professional format examples Action Verbs: See references/action_verbs.md for strong starters
Output Format
The optimized resume should: Maintain user's original structure (unless severely flawed) Add quantifiable metrics where possible Use CAR format for bullet points Include all JD keywords naturally Have Word comments on EVERY change explaining the rationale Comment format in Word: Location: [Section - Bullet Point] Change: [Original โ Modified] Reason: [Why this improves the resume] Evidence: [Based on user's answer / JD requirement / Best practice]
Category context
Workflow acceleration for inboxes, docs, calendars, planning, and execution loops.
Source: Tencent SkillHub
Largest current source with strong distribution and engagement signals.
Package contents
Included in package
3 Docs3 Scripts
- SKILL.md
- references/ats_keywords.md
- references/resume_templates.md
- scripts/analyze_resume.py
- scripts/generate_optimized.py
- scripts/parse_resume.py