So you wanna job...
Best First Move
Stop reading listings one by one. MeWannaJob packages the latest open job pool, opens ChatGPT with a useful fit prompt, and helps you turn your resume plus fresh listings into ranked jobs, missing skills, outreach drafts, and a 7-day plan.
Paste this into ChatGPT after uploading your resume and the CSV.
I am uploading my resume and the MeWannaJob listings CSV.
After both files are attached, rank my top 25 jobs by fit.
For each job give:
1) fit score out of 100
2) why it matches me
3) missing skills I can close in 2 weeks
4) one tailored outreach message.
Then give a 7-day apply plan with priorities.
Download, open ChatGPT, upload resume, send prompt. Use Quick Query only when you want to inspect the pool first.
Use ChatGPT for ranking, then use the dashboard when you want to verify demand by skill, company, or location.
The same one-click flow later supports DeepSeek, Gemini, Claude CLI, and Cursor Agent.
MeWannaJob keeps the ChatGPT and search experience consumer-first. Canonical API contracts, schemas, and dataset versions live on jobdatapool.com. Live transparency and pooled downloader workflows live on jobpool.live.
Consumer product: ChatGPT apply plans, mobile quick search, and desktop comparison views.
Open Consumer SearchCanonical infrastructure: API, schema contracts, versioned dataset pointers, RFC docs.
Open Canonical Data DocsTransparency surface: live visibility, pooled downloads, contributor leaderboards.
Open Transparency LayerBrowse First
Quick Query is for fast checks. Dashboard Workspace is for deeper comparisons when you are on a wider screen.
Same job pool underneath. Pick the view that matches the question.
Built for quick checks from your phone: company, role, place, skill, or industry.
Use the wider workspace when the question has branches. Each query can become its own frame so you can compare without losing context.
Mobile and desktop both sit on the cached job pool. Start with ChatGPT when you want an apply plan, then inspect the same listings yourself when you want proof.
Device-Aware Workspace
The two previews below are not separate products. They are the same job pool shaped for different attention spans: one-question search on a phone, multi-frame comparison on a laptop.
Desktop mode
Use the wide layout when the question has branches. Each query can become another frame, so a researcher or serious job seeker can compare demand instead of replacing the last answer.
Mobile mode
Use the phone layout when you are deciding what to inspect next. It favors tap targets, short commands, and a table that stays close to the input.
Same job data, same query idea, two layouts tuned for the device in front of you.
Skill Comparisons
Same source data, different demand curves. Researchers can use the pool to compare how skills cluster by industry, region, seniority, and posting freshness instead of treating all job listings as one flat market.
How much your existing stack carries over when switching industries.
A workforce researcher studying AI displacement could compare cloud infrastructure jobs against AI product and fintech operations roles. If Python and SQL stay high across all three, but LLM tooling spikes in AI product while risk and compliance spike in fintech, the pool shows which transitions are near-adjacent and which require retraining.
That turns listings into a labor-market signal: not just how many jobs exist, but which skills are becoming portability bridges between industries.
Apply Plan
This is the main conversion moment repeated for people who scroll: pick the assistant you already use, download the same listings CSV, and move from browsing to ranked next actions.
Best default path for ranking roles, explaining fit, finding gaps, and making a 7-day application plan.