…
and headings:…
etc. We need to start with the title as a plain heading (e.g., “Title: …\n\n”), then HTML content. So first line: Title: … then blank line, then HTML content. We must not use placeholders. Write complete actionable content. We must incorporate facts from e-book: Certifications & Education, Checklist for taxonomy maintenance, Example taxonomy excerpt, Hard Skills & Methodologies, Industry-Specific Terminology, Prompt example for AI extraction, Soft Skills & Behaviors, Tools & Software, What to include: (especially important for tech-heavy industries like fintech, healthcare IT, etc.), Balance density, Core vs. Optional keywords, Emerging skills, Map keywords to resume sections, Resume section mapping, Reuse taxonomies, Role / Industry header, Spot gaps, Synonyms and variants, /ˈprɛzənt/ … present? Actually use “client presentations” if applicable. We need to use these facts to keep content specific. So we need to mention these items in the content. We need to count words between 450-500 inclusive. Let’s aim for ~470 words. We need to produce HTML content with paragraphs and headings. Let’s draft. First, Title line: Title: AI-Powered ai Keyword Taxonomy Building for Freelance Resume Writers Then blank line. Then start HTML. We need heading(s). Perhaps an h1? Usually title is separate. We’ll use h2 for sections. We need to ensure we don’t exceed word count. Let’s draft content ~470 words. We’ll count manually. I’ll write content then count. Draft:Why a Custom Keyword Taxonomy Matters
Freelance resume writers win more contracts when they speak the exact language of hiring managers. A custom keyword taxonomy turns raw job descriptions into a structured list of terms that can be mapped to each resume section, ensuring ATS compatibility and human readability.
Step 1: Extract Core Terms with AI
Use the prompt example for AI extraction from the e‑book: “List all hard skills, soft skills, certifications, tools, and industry‑specific terminology mentioned in the following job description.” Feed the description to your preferred LLM and capture the output in a spreadsheet.
Step 2: Organize the Taxonomy
Create columns for Role / Industry header (e.g., “Product Manager – SaaS”), Hard Skills & Methodologies, Soft Skills & Behaviors, Tools & Software, Certifications & Education, and Industry‑Specific Terminology. Add a column for Synonyms and variants (e.g., “leadership” ↔ “mentorship” ↔ “team management”).
Step 3: Classify Core vs. Optional Keywords
Rank each term by frequency across multiple postings and by client input. Mark high‑frequency, non‑negotiable items as Core keywords; lower‑frequency or nice‑to‑have items go into Optional. This balance density prevents over‑stuffing one section while keeping the resume ATS‑friendly.
Step 4: Map Keywords to Resume Sections
Assign each term to the appropriate resume section: Certifications go in a Certifications section, Tools under a Technical Skills sidebar, Hard Skills in Experience bullets, Soft Skills in the Professional Summary, and Industry‑Specific Terminology throughout. Use the Resume section mapping guideline to keep consistency.
Step 5: Maintain and Reuse
Follow the Checklist for taxonomy maintenance: review quarterly, add Emerging skills such as AI, machine learning, and new cloud certifications, retire outdated terms, and incorporate feedback from client results. Save the taxonomy as a template; reuse it for future clients in the same role or industry to cut turnaround time.
Spotting Gaps and Adding Client Presentations
Compare the client’s current experience against the taxonomy to Spot gaps. If the client regularly delivers client presentations, add that phrase under Soft Skills & Behaviors (remember to use “client presentations” as the present‑tense form). This highlights a valuable, often‑overlooked competency.
For a comprehensive guide with detailed workflows, templates, and additional strategies, see my e-book: AI for Freelance Resume Writers: How to Automate Job Description Analysis and Keyword Optimization.
Now count words. We need to count words in the HTML content only? The instruction: “Write a concise 450-500 word WordPress blog post in HTML format”. Likely the whole article after Title line counts. We’ll count words in the HTML paragraphs and headings (excluding HTML tags). Let’s count manually. I’ll extract the text content: Heading1: Why a Custom Keyword Taxonomy Matters Paragraph1: Freelance resume writers win more contracts when they speak the exact language of hiring managers. A custom keyword taxonomy turns raw job descriptions into a structured list of terms that can be mapped to each resume section, ensuring ATS compatibility and human readability. Heading2: Step 1: Extract Core Terms with AI Paragraph2: Use the prompt example for AI extraction from the e‑book: “List all hard skills, soft skills, certifications, tools, and industry‑specific terminology mentioned in the following job description.” Feed the description to your preferred LLM and capture the output in a spreadsheet. Heading3: Step 2: Organize the Taxonomy Paragraph3: Create columns for Role / Industry header (e.g., “Product Manager – SaaS”), Hard Skills & Methodologies, Soft Skills & Behaviors, Tools & Software, Certifications & Education, and Industry‑Specific Terminology. Add a column for Synonyms and variants (e.g., “leadership” ↔ “mentorship” ↔ “team management”). Heading4: Step 3: Classify Core vs. Optional Keywords Paragraph4: Rank each term by frequency across multiple postings and by client input. Mark high‑frequency, non‑negotiable items as Core keywords; lower‑frequency or nice‑to‑have items go into Optional. This balance density prevents over‑stuffing one section while keeping the resume ATS‑friendly. Heading5: Step 4: Map Keywords to Resume Sections Paragraph5: Assign each term to the appropriate resume section: Certifications go in a Certifications section, Tools under a Technical Skills sidebar, Hard Skills in Experience bullets, Soft Skills in the Professional Summary, and Industry‑Specific Terminology throughout. Use the Resume section mapping guideline to keep consistency. Heading6: Step 5: Maintain and Reuse Paragraph6: Follow the Checklist for taxonomy maintenance: review quarterly, add Emerging skills such as AI, machine learning, and new cloud certifications, retire outdated terms, and incorporate feedback from client results. Save the taxonomy as a template; reuse it for future clients in the same role or industry to cut turnaround time. Heading7: Spotting Gaps and Adding Client Presentations Paragraph7: Compare the client’s current experience against the taxonomy to Spot gaps. If the client regularly delivers client presentations, add that phrase under Soft Skills & Behaviors (remember to use “client presentations” as the present‑tense form). This highlights a valuable, often‑overlooked competency. Paragraph8 (ebook promo): For a comprehensive guide with detailed workflows, templates, and additional strategies, see my e-book: AI for Freelance Resume Writers: How to Automate Job Description Analysis and Keyword Optimization. Now count words. I’ll count each paragraph. Paragraph1: “Freelance resume writers win more contracts when they speak the exact language of hiring managers. A custom keyword taxonomy turns raw job descriptions into a structured list of terms that can be mapped to each resume section, ensuring ATS compatibility and human readability.” Count words: Freelance(1) resume2 writers3 win4 more5 contracts6 when7 they8 speak9 the10 exact11 language12 of13 hiring14 managers15. A16 custom17 keyword18 taxonomy19 turns20 raw21 job22 descriptions23 into24 a25 structured26 list27 of28 terms29 that30 can31 be32 mapped33 to34 each35 resume36 section,37 ensuring38 ATS39 compatibility40 and41 human42 readability43. 43 words. Paragraph2: “Use the prompt example for AI extraction from the e‑book: “List all hard skills, soft skills, certifications, tools, and industry‑specific terminology mentioned in the following job description.” Feed the description to your preferred LLM and capture the output in a spreadsheet.” Count: Use1 the2 prompt3 example4 for5 AI6 extraction7 from8 the9 e‑book:10 “List11 all12 hard13 skills,14 soft15 skills,16 certifications,17 tools,18 and19 industry‑specific20 terminology21 mentioned22 in23 the24 following25 job26 description.”27 Feed28 the29 description30 to31 your32 preferred33 LLM34 and35 capture36 the37 output38 in39 a40 spreadsheet41. 41 words. Paragraph3: “Create columns for Role / Industry header (e.g., “Product Manager – SaaS”), Hard Skills & Methodologies, Soft Skills & Behaviors, Tools & Software, Certifications & Education, and Industry‑Specific Terminology. Add a column for Synonyms and variants (e.g., “leadership” ↔ “mentorship” ↔ “team management”).” Count: Create1 columns2 for3 Role4 /5 Industry6 header7 (e.g.,8 “Product9 Manager10 –11 SaaS”),12 Hard13 Skills14 &15 Methodologies,16 Soft17 Skills18 &19 Behaviors,20 Tools21 &22 Software,23 Certifications24 &25 Education,26 and27 Industry‑Specific28 Terminology.29 Add30 a31 column32 for33 Synonyms34 and35 variants36 (e.g.,37 “leadership”38 ↔39 “mentorship”40 ↔41 “team42 management”).43 43 words. Paragraph4: “Rank each term by frequency across multiple postings and by client input. Mark high‑frequency, non‑negotiable items as Core keywords; lower‑frequency or nice‑to‑have items go into Optional. This balance density prevents over‑stuffing one section while keeping the resume ATS‑friendly.” Count: Rank1 each2 term3 by4 frequency5 across6 multiple7 postings8 and9 by10 client11 input