The gap
Every new Claude user writes weak prompts at first — but the hard part isn't
fixing them, it's knowing what's wrong. The cookbook has great evaluation
recipes, but none that take a messy real-world prompt, diagnose it, and repair
it. I'd love to contribute that recipe.
What it does (before → after, in one notebook)
Input: "fix my resume idk make it good"
Output: a scored diagnosis + a rewritten, structured prompt that measurably
scores higher.
Concrete outline
- Score — Claude grades a draft against 5 best-practice dimensions
(role, context, specificity, format, structure) and returns a structured
JSON rubric with a per-dimension reason for any low score.
- Repair — a single "prompt compiler" call rewrites the draft into a
well-structured prompt, preserving the user's intent.
- Prove it worked — re-score the rewritten prompt and show the lift; run
it over a small batch to report average improvement (a real eval loop, not
a vibe check).
- Make it reusable — wrap it in a drop-in
score() / improve() helper
readers can paste into their own apps.
Why it's worth merging
- Fills a genuine gap (diagnose-and-repair, not just evaluate).
- Immediately practical — anyone building on Claude wants "make my users'
prompts better."
- Self-contained, matches your existing notebook style, easy to review.
Why I can deliver it cleanly
I already built these exact ideas into a working, open-source browser
extension — with 100+ passing tests, reproducible benchmarks, and design docs:
https://github.com/Amritha902/promptcomplete
I'll adapt the concepts into a polished, standalone notebook.
Try it live (no install): https://claude.ai/code/artifact/4d15fab9-3403-4cba-b916-a4442b0768b7
Does this fit, and is anything similar already planned? Happy to tune the
scope to whatever you'd find most useful. I can have a draft ready quickly.
The gap
Every new Claude user writes weak prompts at first — but the hard part isn't
fixing them, it's knowing what's wrong. The cookbook has great evaluation
recipes, but none that take a messy real-world prompt, diagnose it, and repair
it. I'd love to contribute that recipe.
What it does (before → after, in one notebook)
Input: "fix my resume idk make it good"
Output: a scored diagnosis + a rewritten, structured prompt that measurably
scores higher.
Concrete outline
(role, context, specificity, format, structure) and returns a structured
JSON rubric with a per-dimension reason for any low score.
well-structured prompt, preserving the user's intent.
it over a small batch to report average improvement (a real eval loop, not
a vibe check).
score()/improve()helperreaders can paste into their own apps.
Why it's worth merging
prompts better."
Why I can deliver it cleanly
I already built these exact ideas into a working, open-source browser
extension — with 100+ passing tests, reproducible benchmarks, and design docs:
https://github.com/Amritha902/promptcomplete
I'll adapt the concepts into a polished, standalone notebook.
Try it live (no install): https://claude.ai/code/artifact/4d15fab9-3403-4cba-b916-a4442b0768b7
Does this fit, and is anything similar already planned? Happy to tune the
scope to whatever you'd find most useful. I can have a draft ready quickly.