I recently launched PowerVerb: resumeactionverbs.com
It’s a resume bullet rewriter focused on turning weak lines into stronger, ATS-friendly resume bullets using better action verbs for resume writing.
If you’re searching for resume action verbs, power verbs for resume, or a fast way to rewrite “Responsible for…” bullets, this tool is built for that exact use case.
Why I built a resume bullet rewriter
Most tools either over-generate or produce generic text.
I wanted a practical resume action verbs tool that is:
- fast
- cost-efficient
- less likely to hallucinate
- useful for real job applications
Core features
- Rewrite one bullet into 3 ATS-friendly versions
- Suggest better resume action verbs by role (engineering, product, marketing, sales)
- Detect weak/repetitive wording
- Save and reuse recent rewrites
- Daily free quota + paid credits/subscription
Tech stack
- Frontend: Next.js (App Router)
- DB/Auth: Supabase
- Rewrite engine: Rule engine + OpenRouter fallback
- Payments: PayPal (orders + subscriptions + webhook idempotency)
- Deploy: Vercel
- DNS/CDN: Cloudflare
Why “rule-first + AI-assisted”?
Initially, I used AI for everything. It worked, but costs and latency were unstable, and weak-verb checks were overkill for LLMs.
So I split the system:
- Deterministic rules for repetition checking + weak verb detection
- AI only for rewrite generation (with strict constraints)
This reduced token usage and made UX feel much faster.
Output quality guardrails
The rewrite prompt enforces:
- don’t invent numbers
- don’t invent responsibilities
- keep original facts
- return strict JSON schema
Then I post-process:
- dedupe variations
- enforce exactly 3 outputs
- fallback to local rule rewrite when model output is invalid
This combo dramatically improved consistency.
Credits/quota logic (important lesson)
One subtle bug I fixed: deduction order.
I originally deducted paid credits first, which felt wrong for users with daily free quota.
Now the order is:
- daily free quota
- subscription credits
- purchased credits
That single logic change removed a lot of confusion and support issues.
UX fixes that mattered more than expected
Two tiny changes improved trust a lot:
-
Copy button feedback (
Copy->Copied) -
Reuse Output auto-scrolls back to editor and shows
Loaded
Without visible feedback, users think the app is broken—even when logic works.
SEO and launch notes
I shipped:
- role-based long-tail landing pages
- sitemap + robots
- canonical + OG metadata
- favicon + structured metadata cleanup
Then submitted sitemap to Google Search Console and started testing channels like HN Show.
What I’d improve next
- JD-aware rewrite mode (align bullet to job description)
- batch rewrite mode
- better analytics mapping (GA4 event taxonomy + funnel reporting)
- export formats (DOCX/Notion/JSON)
Final thought
If you’re building an AI writing product, my biggest takeaway is:
Put deterministic logic in front of AI whenever possible.
It makes your product cheaper, faster, and easier to trust.
If you want, I can share a follow-up post with my exact event taxonomy and payment webhook idempotency setup.
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