Ceevee optimize

Skill careerproof-labs/careerproof-skills/skills/ceevee-optimize

Full interactive CV optimization pipeline — upload your CV, get market positioning analysis, explore career pivot opportunities, then receive targeted section-by-section edits with trade-offs. 3-step process where YOU choose the lens and opportunities. Use this skill whenever someone asks to optimize their CV, improve their resume, reposition their career narrative, fix mixed signals in their CV, get CV edits with trade-offs, or run the positioning pipeline. Also triggers on "help me with my CV", "my resume needs work", "how does the market read my CV", or "I'm pivoting careers and need to update my resume". For a faster non-interactive review, use ceevee-quick-review instead (10 credits, single call).From its SKILL.md

Install

npx -y skills add careerproof-labs/careerproof-skills --skill ceevee-optimize

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SKILL.md

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CeeVee Optimize — CV Positioning Pipeline

Upload a CV and run the full 3-step positioning pipeline: market analysis, opportunity exploration, and targeted edits with before/after suggestions.

MCP Tools

Tool	Cost	Notes
`ceevee_upload_cv`	FREE	Upload CV (PDF/DOCX)
`ceevee_list_versions`	FREE	Find existing CVs
`ceevee_analyze_positioning`	5 credits	Step 1: Market positioning (sync 20-30s)
`ceevee_get_opportunities`	3 credits	Step 2: Career pivots (sync 20-30s)
`ceevee_confirm_lens`	5 credits	Step 3: Targeted edits (sync 20-30s)
`ceevee_explain_change`	1 credit	Optional: explain individual edits (sync)
`ceevee_get_positioning_session`	FREE	Retrieve session data later

Workflow

Step 1: Upload CV (FREE)

Ask the user for their CV file (PDF or DOCX).

Call ceevee_upload_cv with the file (base64 encoded) and optional filename.

Save the returned cv_version_id. The response includes parsed sections and word count — briefly confirm the CV was parsed correctly.

If the user already has a CV uploaded, call ceevee_list_versions to find existing versions instead.

Step 2: Market Positioning Analysis (5 credits)

Run the positioning analysis to understand how the CV reads to the market:

Call ceevee_analyze_positioning with cv_version_id.

This takes 20-30 seconds. Save the returned session_id for subsequent steps.

Present the results:

Positioning snapshot — How the market currently reads this CV
Detected narrative lens — The strongest story the CV tells (e.g., "Technical Leader", "Scale-up Builder")
Recruiter inference — What a recruiter would assume about this person
Mixed signal flags — Where the CV sends contradictory messages

Ask the user if the detected lens matches their intent, or if they want to explore alternatives.

Step 3: Career Opportunities (3 credits)

Explore career pivots and opportunities based on the CV and selected lens:

Call ceevee_get_opportunities with cv_version_id, the lens from Step 2, and session_id.

This takes 20-30 seconds.

Present 2-4 career opportunities, each with:

Opportunity title and description
Rationale (why this person is suited)
CV signals that support the pivot
Market context

Ask the user which opportunities interest them, or if they want to proceed with the original lens.

Step 4: Targeted Edits (5 credits)

Generate section-by-section CV edits with trade-off analysis:

Call ceevee_confirm_lens with:

cv_version_id
confirmed_lens — The lens the user chose (detected or custom)
session_id
Optionally include positioning_snapshot, detected_lens_full, recruiter_inference, and selected_opportunities from prior steps for richer edits
Optionally include custom_positioning if the user described their own positioning

This takes 20-30 seconds.

Important: The ceevee_confirm_lens response can be very large (50,000-100,000+ characters) because it contains full before/after text for every CV section. Do not try to display the raw response. Instead:

Parse the response to extract the edits array
For each edit, present a concise summary:
- Section being modified
- Key changes — A 1-2 sentence summary of what changed
- Trade-off — What this edit gains vs. what it sacrifices
Offer to show the full before/after text for any specific section the user wants to see in detail

This keeps the output readable while giving the user access to the full detail on demand.

Step 5: Optional — Explain Individual Edits (1 credit each)

If the user wants deeper reasoning on any specific edit:

Call ceevee_explain_change with cv_version_id and the change_id from the edits array.

Step 6: Next Steps

/ceevee-career-intel for salary data and market research
/ceevee-report for comprehensive career intelligence reports
Session persists: ceevee_get_positioning_session(session_id) retrieves all data later

Credit Cost

Step	Cost
Upload CV	FREE
Positioning analysis	5 credits
Opportunities	3 credits
Targeted edits	5 credits
Explain edit	1 credit each
Pipeline total	13 credits

Tips

The 3-step pipeline gives the user more control — they choose the lens and opportunities before edits are generated
For a faster single-call alternative, use /ceevee-quick-review (10 credits)
If the user has a specific target role, suggest /ceevee-quick-review with jd_text instead
Edits include trade-off notes — always present these so the user can make informed decisions
The session persists — call ceevee_get_positioning_session with session_id to retrieve all data later