Application accelerator

Application-Accelerator

Takes the resume optimized by Resume-Optimizer-Pro and turns it into submitted applications. Routes to two paths based on the user's Claude plan. Both paths produce the same outputs: a customized resume variant, a 3-sentence cover note, a full cover letter, and an updated tracker entry for every role.

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Step 0: Collect Inputs

Before routing to a path, collect three things:

1. Optimized resume If the user just ran Resume-Optimizer-Pro in this session, the resume is already in context — use it directly. If not:

• If they paste it as text: use as-is
• If they upload a file: read /mnt/skills/public/file-reading/SKILL.md to extract it correctly before proceeding

2. Target job criteria Ask if not provided:

"What job title are you targeting, and where? (e.g., 'AI Content Strategist, remote' or 'Marketing Manager, Lucknow'). Any date range for postings (last 7 / 14 / 30 days)?"

3. Plan detection Ask directly — do not guess:

"Are you on Claude Pro or Max with Cowork access? (This determines whether I can search and apply automatically, or whether we work from job descriptions you paste in.)"

• Yes → Pro/Max with Cowork → Read references/path-b.md and follow PATH B
• No → Free plan → Read references/path-a.md and follow PATH A

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Match Scoring Engine

Used by BOTH paths. Score every job description against the resume on 5 dimensions. Be honest — inflate nothing. A 70+ score means proceed; below 70 means flag and ask the user if they still want to apply.

MATCH SCORE BREAKDOWN — [ROLE] @ [COMPANY]
──────────────────────────────────────────
Skill overlap        /30  [# of required skills from JD found in resume]
Experience alignment /20  [years + seniority level match]
Domain relevance     /20  [same or adjacent industry/vertical]
Role title fit       /15  [how close past titles are to this target]
Keyword density      /15  [JD-specific ATS keywords present in resume]
──────────────────────────────────────────
TOTAL                /100

Verdict:
90–100 → Strong match. Minimal customization needed.
70–89  → Good match. Customize summary + 2-3 bullets.
50–69  → Stretch role. Heavy customization + address gap in cover letter.
<50    → Weak match. Flag to user before proceeding.

Run this score for every job before customizing. Never skip scoring — it is the basis for what to customize and what to say in the cover letter's third paragraph.

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Resume Customization Rules

Apply these for every role, regardless of path. Customize only the SUMMARY and top 3 bullet points per role. Do not rebuild the entire resume per job — that creates inconsistency. The rest stays from the optimized resume.

Summary rewrite (3 sentences max):

1. Open with the exact job title from the JD — not the user's current title
2. Surface the 2 most relevant skills from the match score's skill overlap
3. Close with a result that maps directly to the company's stated need in the JD

Bullet customization:

• Identify which 3 bullets from the original resume are most relevant to THIS JD
• Move them to the top of the most recent role
• If a bullet uses a generic term the JD uses with a specific term, swap it: e.g., resume says "content pipeline" → JD says "editorial workflow" → swap
• Do not fabricate new bullets. Reorder and refocus, never invent.

What to show the user:

CUSTOMIZED FOR: [Role] @ [Company]
Match Score: [X]/100

SUMMARY (rewritten):
[New 3-sentence summary]

BULLETS MOVED TO TOP:
• [Most relevant bullet]
• [Second most relevant]
• [Third most relevant]

WHAT CHANGED:
• [Specific change 1 and why]
• [Specific change 2 and why]

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Cover Material Generation

Generate BOTH for every role. The user picks which to use:

Cover Note (3 sentences — for Easy Apply / Quick Apply forms)

Rules:

1. Sentence 1: Show you understand their biggest current problem (mine from JD)
2. Sentence 2: One specific, quantified proof point from the resume that maps to it
3. Sentence 3: One specific reason you want THIS company — not just any company

Tone: Direct, no preamble, no "I am writing to apply for..." opener. Start with the problem, not yourself.

Example:

"Scaling content production without losing quality is the core challenge for a team at your stage — I've solved this before by building AI-assisted pipelines that cut production time by 60% without compromising output standards. At Haizion Club, I took content output from 4 to 22 pieces per week while the team stayed the same size. Your focus on [specific company initiative from JD] is exactly the problem I want to work on next."

Full Cover Letter (under 250 words — for formal applications or email)

Follow these 4 rules exactly in order. Do not merge paragraphs or reorder:

Paragraph 1 — Their problem: One sentence only. Show you understand their biggest current challenge. Source it from the JD's language — they told you what they're struggling with. Do not open with "I am writing to apply" or "I am excited about this opportunity."

Paragraph 2 — Your proof: 2-3 specific examples from the resume that map directly to what they need. Use metrics. Use the XYZ formula: accomplished [X] measured by [Y] by doing [Z]. No vague claims. No "I am passionate about." Every sentence earns its place.

Paragraph 3 — Address the gap: Find the one obvious gap between the resume and the JD (from the match score's lowest-scoring dimension) and reframe it. Do not hide it — address it directly and explain why it is not a blocker. This is the paragraph most candidates skip and the one that most impresses hiring managers.

Paragraph 4 — Why them specifically: One sentence. A specific reason for THIS company — a product, a mission, a recent news item, something in the JD that is unique to them. Not "I admire your culture."

Tone: Confident, direct, no fluff, no buzzwords. Must not read like AI wrote it. Maximum 250 words. Count before outputting.

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Application Tracker

Maintain a running tracker for every role processed in this session. After all roles are handled, generate the tracker as a CSV file using:

node /mnt/skills/user/application-accelerator/scripts/tracker.js \
  --data /tmp/tracker_data.json \
  --output /mnt/user-data/outputs/application-tracker.csv

Build /tmp/tracker_data.json with this schema — one entry per role:

[
  {
    "number": 1,
    "company": "Company Name",
    "role": "Job Title",
    "job_url": "https://...",
    "date_posted": "YYYY-MM-DD or 'Unknown'",
    "match_score": 84,
    "status": "Draft | Submitted | Applied Manually | Pending Review",
    "customizations": "Summary rewritten + 3 bullets reordered",
    "cover_note_written": true,
    "cover_letter_written": true,
    "date_applied": "YYYY-MM-DD or blank",
    "notes": "Any role-specific notes"
  }
]

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Output Delivery

After processing all roles, present:

1. The CSV tracker file
2. A session summary in chat:

APPLICATION SESSION SUMMARY
────────────────────────────────────────
Jobs reviewed:       [N]
Qualified (70%+):    [N]
Applications sent:   [N] (PATH B) / Ready to submit: [N] (PATH A)
Average match score: [X]/100

TOP MATCH THIS SESSION:
[Role] @ [Company] — [score]/100

NEXT STEPS:
□ Fill in any [FILL IN] placeholders in resume variants before submitting
□ Follow up on submitted applications in 3 days (Skill 3 handles this)
□ Run interview prep when you land a callback (Skill 3: Interview-to-Offer-Pro)

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Reference Files

Detailed step-by-step flows live in the reference files. Read the correct one after plan detection in Step 0:

• PATH A (Free): references/path-a.md
• PATH B (Pro + Cowork): references/path-b.md