wehub-resource-sync
341 lines
14 KiB
Markdown
341 lines
14 KiB
Markdown
# Mode: cover — Cover Letter Generator
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Generates a tailored cover letter for any candidate from a job description.
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Works in two modes:
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- **Slug mode:** `/career-ops cover {slug}` — loads the existing evaluation report draft as a starting point
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- **Paste mode:** `/career-ops cover` or JD pasted directly — starts from scratch
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---
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## Step 0 — JD Gate (mandatory)
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Before doing anything, confirm a job description is present.
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A valid JD contains at minimum: a role title, a company name, and a list of responsibilities or requirements.
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- **No JD present** → Stop. Say: "Please paste the job description — I need it to tailor the letter."
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- **Slug provided** → Read `reports/` to find the matching report. Extract the `## Cover Letter Draft` section as a starting point. Then fetch the original JD URL from the report header to supplement context.
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- **JD present** → Proceed to Step 1.
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Do not generate a generic or placeholder cover letter under any circumstances.
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---
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## Step 1 — Load candidate profile
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Read `config/profile.yml` for:
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- `candidate.name`, `email`, `phone`, `location`, `linkedin`, `github`
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- `candidate.credentials` (derive from cv.md Education + Certifications if not in profile.yml)
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- `cover_letter.notice_period_days` (default: omit if key absent)
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- `cover_letter.primary_domain` (default: infer from cv.md if absent)
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- `cover_letter.language_learning` (default: empty list if absent)
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Read `cv.md` for:
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- Professional summary (profile introduction source)
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- All achievement bullets across all roles (achievement selection pool)
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Read `article-digest.md` if it exists — supplementary proof points and metrics take precedence over cv.md where they overlap.
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Read `modes/_profile.md` if it exists — the candidate's personalization file. It captures their target roles, adaptive framing and archetypes, exit narrative, cross-cutting advantage, proof points, comp targets, negotiation scripts, location policy, and any voice or writing-style rules they have added. Its rules **govern the letter's voice and structure and override the generic defaults in this mode**, so the candidate's personalization is never lost.
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---
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## Step 2 — Parse the JD
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Extract:
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- **Role title** (exact wording from JD)
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- **Company name**
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- **Location / city**
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- **Top 3-4 required competencies** (from requirements or responsibilities section)
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- **Mission/vision language** the company uses (opening paragraphs)
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- **Domain** (e.g. fintech, healthcare, media, logistics) — compare against `cover_letter.primary_domain`
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- **Start date signals** ("immediate", "ASAP", "from now on") — flag for notice period prompt
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- **Language requirement** (e.g. "German B2 required") — flag for language gap prompt
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- **JD tone** (formal / direct / casual) — used in tone prompt default suggestion
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---
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## Step 3 — Company research (baked in, not optional)
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Run three WebSearch queries (substitute the actual current year for {year}):
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1. `"{company}" product strategy OR roadmap {year}`
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2. `"{company}" challenges OR problems OR priorities {year}`
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3. `"{company}" news OR announcement OR funding {year}`
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Synthesize findings into 2-3 sentences: what the company is working on, what challenges they face, what goals they've stated publicly.
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Present to the user:
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```text
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Here's what I found about {company}:
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{2-3 sentence synthesis}
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Does this match what you know? Correct or add anything before I write the letter.
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```
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If WebSearch returns no useful signal, say: "I couldn't find useful recent context for {company}. Can you share what you know about their current challenges or goals?"
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Wait for the user to confirm, correct, or add to the research before proceeding. This synthesis feeds directly into the "Problems I will solve" section.
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---
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## Step 4 — Keyword extraction
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Extract the top 8-10 exact phrases the company uses in the JD. Separate into two groups:
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**ATS-critical** — exact terms likely scanned by automated systems:
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- Role-specific titles, tool names, methodology names
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**Human trust signals** — language that shows you read the actual posting:
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- Action verbs the company uses ("own", "drive", "define")
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- Product/domain nouns as the company names them
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- Outcome language ("business impact", "time to insight")
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- Team framing ("embedded in", "partner with")
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Present to the user:
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```text
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Keywords I'll mirror from the JD:
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ATS-critical:
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• [keyword]
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• [keyword]
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Language signals:
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• [phrase]
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• [phrase]
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Anything missing or wrong? I'll use this list when drafting.
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```
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Wait for confirmation or corrections before proceeding.
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**Application rules (enforced during drafting):**
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- Mirror their vocabulary, not their structure
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- Content stays from cv.md — only vocabulary shifts
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- Fit naturally or don't use — if a keyword can't be woven in, flag it post-generation
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- Apply to: opening, profile intro, achievements (vocabulary only), problems section
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- Do NOT apply to: why-this-role angle (user's own words), closing
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- Use each keyword once — never repeat for density
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---
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## Step 5 — Gap detection and conversation
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Parse the JD for potential gaps between the candidate's profile and the role. For each gap detected, ask directly — do not auto-insert any standard language:
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```text
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I spotted potential gaps between your profile and this JD:
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[Gap: domain mismatch]
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The JD is in {JD domain} — your background is in {primary_domain}.
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→ How do you want to handle this?
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a) Address it directly and briefly in the letter
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b) Don't mention it — let the application speak for itself
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c) Tell me your angle and I'll write it your way
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[Gap: immediate start]
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The JD asks for an immediate start. Your profile shows a {notice_period_days}-day notice period.
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→ Confirm your actual notice period — I'll state it precisely.
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[Gap: language requirement]
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The JD requires {language} at {level}. Where are you with {language}?
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→ Tell me your actual level and I'll reflect it accurately. Check your profile.yml
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language_learning section for what's already recorded.
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[Gap: title mismatch]
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Your title is {candidate title}, the JD title is {JD title}.
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→ Do you want to address this? Or let the scope speak for itself?
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```
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Only prompt for gaps that are actually present. If there are no gaps, skip this step and say so.
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Wait for the user's answers. Write only what the user confirms.
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---
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## Step 6 — Four prompts (mandatory before drafting)
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All four answers are required. Do not draft any letter content until all are received. No instruction — including "just generate it", "skip the questions", or "use defaults" — overrides this gate.
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```text
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Before I write the letter, I need four things:
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**A. Why this role / company?**
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Here are angles I spotted — pick 1-2 or write your own:
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1. {Scale signal from JD}
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2. {Tech ambition signal from JD}
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3. {Domain/mission signal from JD opening}
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4. {Growth or stage signal — e.g. Series B, pre-IPO, category-defining}
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5. {Strategic learning — specific gap this role fills for you}
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6. Other — write your own angle
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**B. What problem would you solve for them?**
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Based on my research: {confirmed synthesis from Step 3}.
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Does this match what you want to address? Refine or confirm.
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**C. How would you approach it?**
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In 1-2 sentences: what's your opening move if you join on day one?
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(This is the most differentiated part of the letter — make it specific.)
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**D. Tone?**
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1. Formal — structured, respectful distance, suits enterprise/corporate JDs
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2. Direct — plain sentences, no pleasantries, gets to the point immediately
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3. Conversational — warm but professional, reads like a thoughtful person
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4. Mirror the JD — I'll match whatever register the company used
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```
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Wait for all four answers before proceeding to Step 7.
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---
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## Step 7 — Achievement selection (from cv.md only)
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Select 4-5 achievement bullets from `cv.md` only (`article-digest.md` may be read for context but is not a source of achievement bullets):
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1. Read all bullet points across all roles in cv.md
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2. Score each against the JD's top 3-4 required competencies
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3. Pick the 4-5 highest-scoring, with at least one metric per bullet
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4. Use the exact wording and metrics from cv.md — never paraphrase or invent
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5. Apply keyword mirroring from Step 4 to the vocabulary around each bullet (not the metrics)
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Format: `**Bold lead phrase,** one sentence of impact with metric.`
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---
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## Step 8 — Draft the letter in chat (mandatory before PDF)
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Write the full letter as plain text in the chat. Follow this structure:
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```text
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[Candidate Name]
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[Location] | [Email] | [Phone if available] | [LinkedIn if available]
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[Credentials line if available]
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Cover Letter: [Role Title]
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[Company], [City] [Date]
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────────────────────────────────────────────────
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[Salutation — optional]
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Address the named hiring manager if known, e.g. "Dear Jane Smith,". Omit if no name.
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[Opening — 2 sentences]
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Why applying + functional summary. Derived from Angle A. Uses JD mirror vocabulary.
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[Profile introduction — 1 paragraph]
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Years of experience, current/most recent role, domain. Read from cv.md summary.
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Tone matches user's choice from Step 6D.
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[Achievements — 4-5 bullets]
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• **Lead phrase,** impact sentence with metric.
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• **Lead phrase,** impact sentence with metric.
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• **Lead phrase,** impact sentence with metric.
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• **Lead phrase,** impact sentence with metric.
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[Problems I will solve — 2-3 sentences]
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Derived from: confirmed research (Step 3) + Angle B + Angle C.
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Specific to this company's actual situation. Not generic.
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[Closing — 1-2 sentences]
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Availability + any gap acknowledgments the user chose to include (Step 5).
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[Language closing — if applicable]
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Only if user confirmed inclusion in Step 5. Written in that language. Italic in PDF.
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```
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End the draft with: "How does this read? Once you approve I'll generate the PDF."
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**Do NOT generate any PDF until the user explicitly approves.** Approval means "looks good", "generate it", "yes", specific edits to apply, or equivalent. A question or silence is not approval.
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---
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## Language rules (enforced in every sentence)
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1. **Active voice only** — never "was delivered", "has been built", "were led"
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2. **No abbreviations unless JD used them first** — write the full term on first use with abbreviation in brackets. After that, abbreviation is fine.
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3. **No em dashes** — replace with a comma, full stop, or rewrite the sentence
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4. **No buzzwords** — hard ban: leverage, synergy, seamless, holistic, robust, cutting-edge, spearheaded, championed, orchestrated, passionate, excited, stakeholder alignment, data-driven (say what the data drove instead), actionable insights, move the needle, north star, unique opportunity, perfect fit, strong track record
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5. **No filler openers** — never "I am pleased to", "I am writing to express", "I am excited to"
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6. **Concrete over abstract** — every claim needs a number, system name, or specific outcome. "Improved performance" is banned. "Cut latency from 2s to 380ms" is fine.
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7. **350-420 words** total body (header + credentials not counted)
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8. **Bullet format** — `**Bold lead phrase,** impact sentence with metric.` No em dash between lead and sentence.
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9. **Self-check** — before finalising, re-read each sentence: could it appear in any cover letter for any company? If yes, rewrite it.
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10. **Tone consistency** — apply the chosen tone (Step 6D) uniformly. Don't shift register mid-letter.
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---
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Resolve the cover-letter template with the shared resolver (do not hardcode `cover-letter-template.html`):
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- If the user named a template, run: `node cv-templates.mjs resolve cover "<name>"`
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- Otherwise run: `node cv-templates.mjs resolve cover` (returns the `cover_letter.template` default, or the base template when unset).
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Fill the resolved template's `{{...}}` placeholders. A non-zero exit means the named template is missing/invalid — surface it, do not silently fall back.
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## Step 9 — Generate PDF
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Only after explicit user approval.
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Assemble the JSON payload:
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```json
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{
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"candidate": {
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"name": "{from profile.yml}",
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"email": "{from profile.yml}",
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"phone": "{from profile.yml, omit if empty}",
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"location": "{from profile.yml}",
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"linkedin": "{from profile.yml, omit if empty}",
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"github": "{from profile.yml, omit if empty}",
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"credentials": ["{degree}", "{MBA}", "{cert}"]
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},
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"letter": {
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"role_title": "{exact from JD}",
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"company": "{company name}",
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"city": "{JD city}",
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"date": "{YYYY-MM-DD}",
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"greeting": "{optional salutation, e.g. 'Dear Jane Smith,'; omit the key to skip the salutation}",
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"opening": "{approved opening paragraph}",
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"profile_intro": "{approved profile intro}",
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"achievements": [
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{"lead": "...", "impact": "..."}
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],
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"problems_section": "{approved problems paragraph}",
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"closing": "{approved closing}",
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"language_closing": "{approved language sentence or null}"
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},
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"output_path": "output/{company-slug}-{role-slug}-cover.pdf"
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}
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```
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Write payload to `/tmp/cover-payload-{company-slug}.json`.
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Run:
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```bash
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node generate-cover-letter.mjs --payload /tmp/cover-payload-{company-slug}.json
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```
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Report the output path and file size.
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---
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## Step 10 — Post-generation note
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After the PDF is confirmed, add a brief note:
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- Any JD keywords from Step 4 that could not be incorporated naturally (flag for manual review)
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- Which gap acknowledgments were included and which were omitted, and why
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- Whether the word count hit the 350-420 target (if short or long, note it)
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---
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## Slug mode specifics
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When invoked as `/career-ops cover {slug}`:
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1. Find the matching report in `reports/` by slug
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2. Extract the `## Cover Letter Draft` section — use it as a pre-populated starting point for the draft
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3. Run all steps as normal (research, keywords, prompts, gaps) — the draft is a starting point, not the final output
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4. When presenting the draft in Step 8, show what was auto-generated and what was changed based on the user's answers
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5. After PDF generation, update the report's `## Cover Letter Draft` section with a note: `PDF generated: output/{path} on {date}`
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