The model needs code evidence, not a vague bug description.
CodeFix
Give AI coding tools the codebase context they actually need
CodeFix produces implementation briefs with root cause, affected files, constraints, acceptance criteria, and regression cautions.
Highest leverage finding
Payment state can drift from app state
Checkout can succeed while booking and entitlement records remain incomplete after webhook retries.
app/api/stripe/webhook/route.tssupabase/policies.sqltests/checkout.spec.tsWhat better context includes
CodeFix separates symptoms from launch blockers.
Patch boundaries must name files to change and avoid.
Acceptance criteria must reflect product behavior.
What you get
A report that explains the risk and the next safe patch boundary.
Each finding has a plain-English founder summary plus technical evidence with affected files, recommended fixes, acceptance criteria, and regression cautions.
Sample findings
The output is specific enough to scope repair work.
The prompt should include the webhook route, entitlement model, and affected UI state.
The fix should not regenerate the checkout page.
Trust FAQ
Clear access boundaries before code is uploaded.
Do you support private repos?
Yes. CodeFix supports private GitHub repositories and ZIP exports. Repository access is used only to inspect the code needed for launch-readiness analysis.
Do you train models on my code?
No. Customer code is analyzed for the report and is not used for model training. Deeper proof runs through configured live analysis.
Can I delete my project?
Yes. Projects are built around delete-after-report controls and revocable access so uploaded code does not need to remain in the system longer than necessary.
What access do you need?
CodeFix needs source access or a ZIP export, plus any spec, PRD, screenshots, or notes that explain what the app should do and what is currently failing.
Launch-readiness report
Get the proof-to-ship plan before the next rebuild debate
Upload the repo and spec. Get the gaps, risks, repair scope, and repair-budget estimate before the next sprint decision.