{ "schemaVersion": "1.0", "item": { "slug": "resume-optimizer-uk", "name": "UK Resume Analyzer & Optimizer", "source": "tencent", "type": "skill", "category": "效率提升", "sourceUrl": "https://clawhub.ai/phonedog/resume-optimizer-uk", "canonicalUrl": "https://clawhub.ai/phonedog/resume-optimizer-uk", "targetPlatform": "OpenClaw" }, "install": { "downloadMode": "redirect", "downloadUrl": "/downloads/resume-optimizer-uk", "sourceDownloadUrl": "https://wry-manatee-359.convex.site/api/v1/download?slug=resume-optimizer-uk", "sourcePlatform": "tencent", "targetPlatform": "OpenClaw", "installMethod": "Manual import", "extraction": "Extract archive", "prerequisites": [ "OpenClaw" ], "packageFormat": "ZIP package", "includedAssets": [ "SKILL.md", "scripts/analyze_resume.py", "scripts/generate_optimized.py", "scripts/parse_resume.py", "references/ats_keywords.md", "references/resume_templates.md" ], "primaryDoc": "SKILL.md", "quickSetup": [ "Download the package from Yavira.", "Extract the archive and review SKILL.md first.", "Import or place the package into your OpenClaw setup." ], "agentAssist": { "summary": "Hand the extracted package to your coding agent with a concrete install brief instead of figuring it out manually.", "steps": [ "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." ], "prompts": [ { "label": "New install", "body": "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." }, { "label": "Upgrade existing", "body": "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." } ] }, "sourceHealth": { "source": "tencent", "status": "healthy", "reason": "direct_download_ok", "recommendedAction": "download", "checkedAt": "2026-04-30T16:55:25.780Z", "expiresAt": "2026-05-07T16:55:25.780Z", "httpStatus": 200, "finalUrl": "https://wry-manatee-359.convex.site/api/v1/download?slug=network", "contentType": "application/zip", "probeMethod": "head", "details": { "probeUrl": "https://wry-manatee-359.convex.site/api/v1/download?slug=network", "contentDisposition": "attachment; filename=\"network-1.0.0.zip\"", "redirectLocation": null, "bodySnippet": null }, "scope": "source", "summary": "Source download looks usable.", "detail": "Yavira can redirect you to the upstream package for this source.", "primaryActionLabel": "Download for OpenClaw", "primaryActionHref": "/downloads/resume-optimizer-uk" }, "validation": { "installChecklist": [ "Use the Yavira download entry.", "Review SKILL.md after the package is downloaded.", "Confirm the extracted package contains the expected setup assets." ], "postInstallChecks": [ "Confirm the extracted package includes the expected docs or setup files.", "Validate the skill or prompts are available in your target agent workspace.", "Capture any manual follow-up steps the agent could not complete." ] }, "downloadPageUrl": "https://openagent3.xyz/downloads/resume-optimizer-uk", "agentPageUrl": "https://openagent3.xyz/skills/resume-optimizer-uk/agent", "manifestUrl": "https://openagent3.xyz/skills/resume-optimizer-uk/agent.json", "briefUrl": "https://openagent3.xyz/skills/resume-optimizer-uk/agent.md" }, "agentAssist": { "summary": "Hand the extracted package to your coding agent with a concrete install brief instead of figuring it out manually.", "steps": [ "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." ], "prompts": [ { "label": "New install", "body": "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." }, { "label": "Upgrade existing", "body": "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." } ] }, "documentation": { "source": "clawhub", "primaryDoc": "SKILL.md", "sections": [ { "title": "Resume Analyzer", "body": "Analyze resumes against job descriptions and generate optimized versions with detailed annotations." }, { "title": "When to Use", "body": "User provides a resume file (.docx) and wants analysis\nUser provides both resume and JD for matching analysis\nUser wants ATS optimization suggestions\nUser wants quantified achievements and stronger bullet points\nUser wants an optimized version with explanations" }, { "title": "Step 1: Load & Parse Resume", "body": "Use scripts/parse_resume.py to extract content from .docx:\n\npython scripts/parse_resume.py --output parsed_resume.json" }, { "title": "Step 2: Five-Dimension Analysis", "body": "Run analysis script with JD (if provided):\n\npython scripts/analyze_resume.py parsed_resume.json [--jd job_description.txt] --output analysis_report.json\n\nThe analysis covers:\n\nJD Match Score (0-100): Keyword overlap, skills alignment\nQuantification Score (0-100): Presence of metrics, numbers, percentages\nStructure Logic (0-100): Section order, readability, hierarchy\nLanguage Professionalism (0-100): Action verbs, clarity, conciseness\nATS-Friendliness (0-100): Format, keywords, standard sections" }, { "title": "Step 3: Interactive Q&A", "body": "Present the 5-dimension report and ask follow-up questions:\n\nQuestions to ask (user can select or type):\n\nWhich role at [Company X] had the biggest impact? What were the measurable results?\nAny specific project with quantifiable outcomes (revenue, users, efficiency)?\nTools/technologies used that aren't mentioned?\nAny awards, recognition, or leadership experiences to highlight?\nEducation details: GPA, relevant coursework, projects?\n\nStore answers in supplemental_data.json." }, { "title": "Step 4: Generate Optimized Version", "body": "python scripts/generate_optimized.py \\\n parsed_resume.json \\\n analysis_report.json \\\n supplemental_data.json \\\n --output optimized_resume.docx \\\n --backup original_backup.docx\n\nOutput files:\n\noriginal_backup.docx: Clean copy of original\noptimized_resume.docx: Optimized version with Word comments explaining every change" }, { "title": "Step 5: Summary Output", "body": "Present to user:\n\nOriginal vs Optimized comparison (key changes)\nScore improvements (Before → After for each dimension)\nFile locations" }, { "title": "CAR Method for Bullet Points", "body": "Transform vague descriptions into CAR format:\n\nContext: What was the situation?\nAction: What did YOU specifically do?\nResult: What was the measurable outcome?\n\nExample transformation:\n\n❌ \"Responsible for managing team and improving processes\"\n✅ \"Led 8-person logistics team (Context), implemented new WSSI forecasting system (Action), reducing stockouts by 35% and saving £120K annually (Result)\"" }, { "title": "ATS Optimization Rules", "body": "Use standard section headers: Experience, Education, Skills (not fancy variations)\nInclude full keywords from JD: If JD says \"Supply Chain Optimization\", use exact phrase\nAvoid tables, headers/footers, graphics: ATS may not parse them\nFile format: .docx preferred over PDF for ATS" }, { "title": "Quantification Guidelines", "body": "Always seek numbers:\n\nRevenue: £X, $X, % growth\nScale: X team members, X regions, X SKUs\nEfficiency: X% faster, X% cost reduction, X hours saved\nImpact: X customers, X users, X% satisfaction improvement" }, { "title": "Reference Materials", "body": "ATS Keywords: See references/ats_keywords.md for industry-specific keyword lists\nResume Templates: See references/resume_templates.md for UK professional format examples\nAction Verbs: See references/action_verbs.md for strong starters" }, { "title": "Output Format", "body": "The optimized resume should:\n\nMaintain user's original structure (unless severely flawed)\nAdd quantifiable metrics where possible\nUse CAR format for bullet points\nInclude all JD keywords naturally\nHave Word comments on EVERY change explaining the rationale\n\nComment format in Word:\n\nLocation: [Section - Bullet Point]\nChange: [Original → Modified]\nReason: [Why this improves the resume]\nEvidence: [Based on user's answer / JD requirement / Best practice]" } ], "body": "Resume Analyzer\n\nAnalyze resumes against job descriptions and generate optimized versions with detailed annotations.\n\nWhen to Use\nUser provides a resume file (.docx) and wants analysis\nUser provides both resume and JD for matching analysis\nUser wants ATS optimization suggestions\nUser wants quantified achievements and stronger bullet points\nUser wants an optimized version with explanations\nWorkflow\nStep 1: Load & Parse Resume\n\nUse scripts/parse_resume.py to extract content from .docx:\n\npython scripts/parse_resume.py --output parsed_resume.json\n\nStep 2: Five-Dimension Analysis\n\nRun analysis script with JD (if provided):\n\npython scripts/analyze_resume.py parsed_resume.json [--jd job_description.txt] --output analysis_report.json\n\n\nThe analysis covers:\n\nJD Match Score (0-100): Keyword overlap, skills alignment\nQuantification Score (0-100): Presence of metrics, numbers, percentages\nStructure Logic (0-100): Section order, readability, hierarchy\nLanguage Professionalism (0-100): Action verbs, clarity, conciseness\nATS-Friendliness (0-100): Format, keywords, standard sections\nStep 3: Interactive Q&A\n\nPresent the 5-dimension report and ask follow-up questions:\n\nQuestions to ask (user can select or type):\n\nWhich role at [Company X] had the biggest impact? What were the measurable results?\nAny specific project with quantifiable outcomes (revenue, users, efficiency)?\nTools/technologies used that aren't mentioned?\nAny awards, recognition, or leadership experiences to highlight?\nEducation details: GPA, relevant coursework, projects?\n\nStore answers in supplemental_data.json.\n\nStep 4: Generate Optimized Version\npython scripts/generate_optimized.py \\\n parsed_resume.json \\\n analysis_report.json \\\n supplemental_data.json \\\n --output optimized_resume.docx \\\n --backup original_backup.docx\n\n\nOutput files:\n\noriginal_backup.docx: Clean copy of original\noptimized_resume.docx: Optimized version with Word comments explaining every change\nStep 5: Summary Output\n\nPresent to user:\n\nOriginal vs Optimized comparison (key changes)\nScore improvements (Before → After for each dimension)\nFile locations\nKey Principles\nCAR Method for Bullet Points\n\nTransform vague descriptions into CAR format:\n\nContext: What was the situation?\nAction: What did YOU specifically do?\nResult: What was the measurable outcome?\n\nExample transformation:\n\n❌ \"Responsible for managing team and improving processes\"\n✅ \"Led 8-person logistics team (Context), implemented new WSSI forecasting system (Action), reducing stockouts by 35% and saving £120K annually (Result)\"\nATS Optimization Rules\nUse standard section headers: Experience, Education, Skills (not fancy variations)\nInclude full keywords from JD: If JD says \"Supply Chain Optimization\", use exact phrase\nAvoid tables, headers/footers, graphics: ATS may not parse them\nFile format: .docx preferred over PDF for ATS\nQuantification Guidelines\n\nAlways seek numbers:\n\nRevenue: £X, $X, % growth\nScale: X team members, X regions, X SKUs\nEfficiency: X% faster, X% cost reduction, X hours saved\nImpact: X customers, X users, X% satisfaction improvement\nReference Materials\nATS Keywords: See references/ats_keywords.md for industry-specific keyword lists\nResume Templates: See references/resume_templates.md for UK professional format examples\nAction Verbs: See references/action_verbs.md for strong starters\nOutput Format\n\nThe optimized resume should:\n\nMaintain user's original structure (unless severely flawed)\nAdd quantifiable metrics where possible\nUse CAR format for bullet points\nInclude all JD keywords naturally\nHave Word comments on EVERY change explaining the rationale\n\nComment format in Word:\n\nLocation: [Section - Bullet Point]\nChange: [Original → Modified]\nReason: [Why this improves the resume]\nEvidence: [Based on user's answer / JD requirement / Best practice]" }, "trust": { "sourceLabel": "tencent", "provenanceUrl": "https://clawhub.ai/phonedog/resume-optimizer-uk", "publisherUrl": "https://clawhub.ai/phonedog/resume-optimizer-uk", "owner": "phonedog", "version": "1.0.0", "license": null, "verificationStatus": "Indexed source record" }, "links": { "detailUrl": "https://openagent3.xyz/skills/resume-optimizer-uk", "downloadUrl": "https://openagent3.xyz/downloads/resume-optimizer-uk", "agentUrl": "https://openagent3.xyz/skills/resume-optimizer-uk/agent", "manifestUrl": "https://openagent3.xyz/skills/resume-optimizer-uk/agent.json", "briefUrl": "https://openagent3.xyz/skills/resume-optimizer-uk/agent.md" } }