226 lines
13 KiB
Markdown
226 lines
13 KiB
Markdown
# Mode: pdf — ATS-Optimized PDF Generation
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## Full pipeline
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1. Read `cv.md` as the source of truth
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2. Ask the user for the JD if it is not in context (text or URL)
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3. Extract 15-20 keywords from the JD
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4. Detect JD language → CV language (EN default)
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5. Detect company location → paper format:
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- US/Canada → `letter`
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- Rest of the world → `a4`
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6. Detect role archetype → adapt framing
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7. Build an internal recruiter-side risk map from the JD using `modes/heuristics/recruiter-side.md`: likely doubts, matching evidence, and which document section should address each doubt
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8. Rewrite Professional Summary by injecting JD keywords + exit narrative bridge ("Built and sold a business. Now applying systems thinking to [JD domain].")
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9. Select top 3-4 most relevant projects for the job
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10. Reorder experience bullets by JD relevance and by the risk map: strongest matching evidence first
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11. Build competency grid from JD requirements (6-8 keyword phrases)
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12. Inject keywords naturally into existing achievements (NEVER invent)
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13. Apply the six-second clarity gate from `modes/heuristics/recruiter-side.md`: top third must make target role, strongest fit, and proof obvious
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14. Generate full HTML from template + personalized content
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15. Read `name` from `config/profile.yml` → normalize to kebab-case lowercase (e.g. "John Doe" → "john-doe") → `{candidate}`
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16. Write HTML to `output/cv-{candidate}-{company}.html` (NOT a temp dir — the recorded HTML is what the dashboard's `D` hotkey regenerates from, so it must survive temp cleanup)
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17. Execute: `node generate-pdf.mjs output/cv-{candidate}-{company}.html output/cv-{candidate}-{company}-{YYYY-MM-DD}.pdf --format={letter|a4} --report={report number}` — `{report number}` is the NNN from the report filename/link (e.g. `008` for `reports/008-acme-….md`), not the tracker `#` column. Pass it whenever the application has (or will have) a report; it records the PDF↔report linkage in `data/pdf-index.tsv` so the dashboard can open and regenerate the exact PDF. Omit it only for one-off CVs with no tracker entry.
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18. Report: PDF path, number of pages, keyword coverage %
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## ATS Rules (clean parsing)
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- Single-column layout (no sidebars, no parallel columns)
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- Standard headers: "Professional Summary", "Work Experience", "Education", "Skills", "Certifications", "Projects"
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- No text in images/SVGs
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- No critical info in PDF headers/footers (ATS ignores them)
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- UTF-8, selectable text (not rasterized)
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- No nested tables
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- Distributed JD keywords: Summary (top 5), first bullet of each role, Skills section
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- No hidden text, keyword stuffing, or white-font tricks. Optimize for parseability plus human review.
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## Recruiter Review Gates
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- The summary should answer: "What role is this person targeting, and why this one?"
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- The first screen should show 1-2 proof points that map to the JD's highest-risk requirements.
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- Bullets should emphasize outcomes, systems, users, or business effects rather than task history.
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- Logistics such as location, work authorization, salary, and availability belong in the CV only when appropriate for the market and profile; otherwise handle them in form answers or recruiter scripts.
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## PDF Design
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- **Fonts**: Space Grotesk (headings, 600-700) + DM Sans (body, 400-500)
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- **Fonts self-hosted**: `fonts/`
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- **Header**: name in Space Grotesk 24px bold + gradient line `linear-gradient(to right, hsl(187,74%,32%), hsl(270,70%,45%))` 2px + contact row
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- **Section headers**: Space Grotesk 13px, uppercase, letter-spacing 0.05em, color cyan primary
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- **Body**: DM Sans 11px, line-height 1.5
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- **Company names**: accent purple color `hsl(270,70%,45%)`
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- **Margins**: 0.6in
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- **Background**: pure white
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## Section order (optimized "6-second recruiter scan")
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1. Header (large name, gradient, contact, portfolio link)
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2. Professional Summary (3-4 lines, keyword-dense)
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3. Core Competencies (6-8 keyword phrases in flex-grid)
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4. Work Experience (reverse chronological)
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5. Projects (top 3-4 most relevant)
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6. Education & Certifications
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7. Skills (languages + technical)
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## Keyword injection strategy (ethical, truth-based)
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Examples of legitimate reformulation:
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- JD says "RAG pipelines" and CV says "LLM workflows with retrieval" → change to "RAG pipeline design and LLM orchestration workflows"
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- JD says "MLOps" and CV says "observability, evals, error handling" → change to "MLOps and observability: evals, error handling, cost monitoring"
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- JD says "stakeholder management" and CV says "collaborated with team" → change to "stakeholder management across engineering, operations, and business"
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**NEVER add skills that the candidate does not have. Only reword real experience using the exact JD vocabulary.**
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## Template HTML
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Use the template in `cv-template.html`. Replace the `{{...}}` placeholders with personalized content:
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| Placeholder | Content |
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|-------------|-----------|
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| `{{LANG}}` | CV language code (e.g. `en`, `es`, `ja`, `ar`). Drives language-specific CSS in the template: `ja` enables a CJK font fallback so Japanese renders instead of tofu (□); `ar` enables RTL + Arabic fonts. Use the BCP-47/ISO-639 code that matches the CV language. |
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| `{{PAGE_WIDTH}}` | `8.5in` (letter) or `210mm` (A4) |
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| `{{PHOTO}}` | Opt-in profile photo (#264). When `profile.yml` has a non-empty `candidate.photo`, replace with `<img class="cv-photo" src="<path-or-data-URL>" alt="{{NAME}}">`; otherwise **remove the whole `{{PHOTO}}` line** so no markup (and no `<img>`) is emitted. Opt-in for DACH/European markets — an absent photo renders identically (pixel-for-pixel) to the photoless layout (US/UK and many-market ATS penalize photos). |
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| `{{NAME}}` | (from profile.yml) |
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| `{{PHONE}}` | (from profile.yml — include with its separator only when `profile.yml` has a non-empty `phone` value; omit both the `<a href="tel:…">` element and the following `<span class="separator">` otherwise) |
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| `{{EMAIL}}` | (from profile.yml) |
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| `{{LINKEDIN_URL}}` | [from profile.yml] |
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| `{{LINKEDIN_DISPLAY}}` | [from profile.yml] |
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| `{{PORTFOLIO_URL}}` | [from profile.yml] (or /es depending on language) |
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| `{{PORTFOLIO_DISPLAY}}` | [from profile.yml] (or /es depending on language) |
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| `{{LOCATION}}` | [from profile.yml] |
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| `{{SECTION_SUMMARY}}` | Professional Summary |
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| `{{SUMMARY_TEXT}}` | Personalized summary with keywords |
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| `{{SECTION_COMPETENCIES}}` | Core Competencies |
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| `{{COMPETENCIES}}` | `<span class="competency-tag">keyword</span>` × 6-8 |
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| `{{SECTION_EXPERIENCE}}` | Work Experience |
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| `{{EXPERIENCE}}` | HTML for each job with reordered bullets |
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| `{{SECTION_PROJECTS}}` | Projects |
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| `{{PROJECTS}}` | HTML for top 3-4 projects |
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| `{{SECTION_EDUCATION}}` | Education |
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| `{{EDUCATION}}` | Education HTML |
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| `{{SECTION_CERTIFICATIONS}}` | Certifications |
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| `{{CERTIFICATIONS}}` | Certifications HTML |
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| `{{SECTION_SKILLS}}` | Skills |
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| `{{SKILLS}}` | Skills HTML |
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### Profile photo (opt-in, market-specific)
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The `{{PHOTO}}` slot is **off by default** and intentionally market-specific:
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- **DACH / much of continental Europe** (Germany, Austria, Switzerland): a professional photo is standard and often expected. Opt in by setting `candidate.photo` in `config/profile.yml` (a local file path or a `data:` URL).
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- **US / UK / Canada / Australia and many ATS-first markets**: photos are discouraged and can trip bias-avoidance filters. Leave `candidate.photo` empty — the `{{PHOTO}}` line is dropped entirely, no `<img>` is emitted, and the CV renders **pixel-for-pixel identical** to today's photoless layout.
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When set, the photo floats into the top corner (mirrored for RTL/Arabic) and the header/summary text wraps beside it; `.cv-photo` in `cv-template.html` controls its size and framing.
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## Canva CV Generation (optional)
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If `config/profile.yml` has `cv.canva_resume_design_id` set, offer the user a choice before generating:
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- **"HTML/PDF (fast, ATS-optimized)"** — existing flow above
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- **"Canva CV (visual, design-preserving)"** — new flow below
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If the user has no `cv.canva_resume_design_id`, skip this prompt and use the HTML/PDF flow.
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### Canva workflow
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#### Step 1 — Duplicate the base design
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a. `export-design` the base design (using `cv.canva_resume_design_id`) as PDF → get download URL
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b. `import-design-from-url` using that download URL → creates a new editable design (the duplicate)
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c. Note the new `design_id` for the duplicate
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#### Step 2 — Read the design structure
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a. `get-design-content` on the new design → returns all text elements (richtexts) with their content
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b. Map text elements to CV sections by content matching:
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- Look for the candidate's name → header section
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- Look for "Summary" or "Professional Summary" → summary section
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- Look for company names from cv.md → experience sections
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- Look for degree/school names → education section
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- Look for skill keywords → skills section
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c. If mapping fails, show the user what was found and ask for guidance
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#### Step 3 — Generate tailored content
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Same content generation as the HTML flow (Steps 1-11 above):
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- Rewrite Professional Summary with JD keywords + exit narrative
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- Reorder experience bullets by JD relevance
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- Select top competencies from JD requirements
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- Inject keywords naturally (NEVER invent)
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**IMPORTANT — Character budget rule:** Each replacement text MUST be approximately the same length as the original text it replaces (within ±15% character count). If tailored content is longer, condense it. The Canva design has fixed-size text boxes — longer text causes overlapping with adjacent elements. Count the characters in each original element from Step 2 and enforce this budget when generating replacements.
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#### Step 4 — Apply edits
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a. `start-editing-transaction` on the duplicate design
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b. `perform-editing-operations` with `find_and_replace_text` for each section:
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- Replace summary text with tailored summary
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- Replace each experience bullet with reordered/rewritten bullets
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- Replace competency/skills text with JD-matched terms
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- Replace project descriptions with top relevant projects
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c. **Reflow layout after text replacement:**
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After applying all text replacements, the text boxes auto-resize but neighboring elements stay in place. This causes uneven spacing between work experience sections. Fix this:
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1. Read the updated element positions and dimensions from the `perform-editing-operations` response
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2. For each work experience section (top to bottom), calculate where the bullets text box ends: `end_y = top + height`
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3. The next section's header should start at `end_y + consistent_gap` (use the original gap from the template, typically ~30px)
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4. Use `position_element` to move the next section's date, company name, role title, and bullets elements to maintain even spacing
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5. Repeat for all work experience sections
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d. **Verify layout before commit:**
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- `get-design-thumbnail` with the transaction_id and page_index=1
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- Visually inspect the thumbnail for: text overlapping, uneven spacing, text cut off, text too small
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- If issues remain, adjust with `position_element`, `resize_element`, or `format_text`
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- Repeat until layout is clean
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e. Show the user the final preview and ask for approval
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f. `commit-editing-transaction` to save (ONLY after user approval)
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#### Step 5 — Export and download PDF
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a. `export-design` the duplicate as PDF (format: a4 or letter based on JD location)
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b. **IMMEDIATELY** download the PDF using Bash:
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```bash
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curl -sL -o "output/cv-{candidate}-{company}-canva-{YYYY-MM-DD}.pdf" "{download_url}"
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```
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The export URL is a pre-signed S3 link that expires in ~2 hours. Download it right away.
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c. Verify the download:
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```bash
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file output/cv-{candidate}-{company}-canva-{YYYY-MM-DD}.pdf
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```
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Must show "PDF document". If it shows XML or HTML, the URL expired — re-export and retry.
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d. Report: PDF path, file size, Canva design URL (for manual tweaking)
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#### Error handling
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- If `import-design-from-url` fails → fall back to HTML/PDF pipeline with message
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- If text elements can't be mapped → warn user, show what was found, ask for manual mapping
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- If `find_and_replace_text` finds no matches → try broader substring matching
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- Always provide the Canva design URL so the user can edit manually if auto-edit fails
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## Cover Letter Sub-flow
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After generating the CV PDF, offer to generate a cover letter:
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```text
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CV PDF generated: output/{path}
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Want a cover letter for this role too?
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- Say "yes" or "cover letter" to generate one now
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- Or run `/career-ops cover {slug}` later
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```
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Apply `voice-dna.md` (if present) to the cover letter — full guardrail, conversational voice included (Tier 1 + Tier 2). The CV PDF itself stays Tier 1 only (formal ATS register). See `_shared.md` → Voice DNA.
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If the user says yes, run the full cover letter flow from `modes/cover.md` in slug mode:
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1. Load the existing `## Cover Letter Draft` from the evaluation report as a starting point
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2. Run company research (Step 3 of cover.md)
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3. Present keyword list for confirmation (Step 4)
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4. Surface any gaps (Step 5)
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5. Ask the four prompts: why / problems / approach / tone (Step 6)
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6. Draft in chat, wait for approval (Steps 7-8)
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7. Generate cover letter PDF via `node generate-cover-letter.mjs` (Step 9)
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8. Report both PDF paths
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Do not auto-generate the cover letter PDF without going through the interactive steps above.
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## Post-generation
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Update tracker if the job is already registered: change PDF from ❌ to ✅.
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