export async function POST(request) {
try {
// TODO: replace demo response with database write
return Response.json({ ok: true, orderId: "demo-123" });
} catch (error) {}
}
AI Build Sanity Check
Run a local, read-only scan for six defined unfinished-work signals, with rule, severity, file, line, and a plain fix for every match.
What it looks for
- Configured build-marker terms such as TODO, FIXME, “not implemented,” and NotImplementedError.
- Return lines containing configured fake, mock, sample, dummy, or placeholder terms.
- Python
exceptblocks followed bypassand same-line empty JavaScriptcatchblocks. - Configured placeholder strings in supported source, config, and
.envfiles. - Return lines containing success, ok, or status near a supported route marker.
- Route-adjacent empty or throwing handler markers as advisory review prompts.
This is line- and term-based static analysis, not proof that a behavior is unfinished. The bundled Python 3 scanner is standard-library only and read-only; its findings create a review queue and do not authorize an automatic rewrite.
See four findings from one supported route
This example uses the exact route, return-term, build-marker, and same-line catch forms recognized by the packaged scanner.
- ABS001TODO matches a configured build-marker term.
- ABS002The return line contains the configured fake-data term
demo. - ABS005The return line contains
oknear a supported route marker. - ABS003The same-line empty catch matches the swallowed-error form.
Supported application files
The scanner reads .py, .js, .ts, .jsx, .tsx, .html, .json, .env, and files named .env inside the selected paths. Because .env is included, scope the run away from it if you do not want that file read.
Where it helps
- Auditing an AI-generated MVP before a client demo or production push.
- Checking a pull request for supported marker, placeholder, error, and route-return patterns.
- Reviewing whether configured fake-data terms appear on return lines in the real data path.
- Giving a non-coder a plain-English list of suspicious shortcuts to take back to the builder.
- Creating a focused first pass before deeper functional, security, authorization, and recovery testing.
How to run
Get it on Agensi and use an agent that reads SKILL.md, can run Python 3 locally, and can read the selected paths. Run python scripts/scan_ai_build_sanity.py <repo-or-folder>, then review deterministic and advisory findings before deciding what to change.
Read-only by design
The scanner reads supported source and configuration files without modifying or deleting them. It reports file, line, rule, severity, and a generic message—not the matched line or value. It does not install packages, start the app, write files, or call the network.
It is a heuristic scanner, not formal verification. A clean report does not guarantee logical correctness, security, real integrations, tenant isolation, production behavior, or recovery.
Use it inside a release decision
The proof-first AI-built app audit shows how to turn findings into evidence for completeness, real data, failure paths, authorization, production behavior, and rollback.
Questions
What does it look for?
Six defined, line-based patterns: build-marker terms, fake-data terms on return lines, specified swallowed-error forms, configured placeholders, route-adjacent canned-success returns, and advisory route-adjacent empty or throwing handlers.
Which files can it review?
.py, .js, .ts, .jsx, .tsx, .html, .json, .env, and files named .env inside the selected paths.
Will it modify my code?
No. The bundled Python 3 scanner reads supported local files and prints findings. It does not write files, install packages, start the app, or call the network.
How do I start an audit?
Use an agent that can read SKILL.md, run Python 3 locally, and read the selected paths. Run the bundled scanner on a repository, directory, or supported file, then review deterministic and advisory findings.
Does a clean report prove the app is ready to launch?
No. It is a heuristic scanner, not formal verification or a security certification. A launch decision still needs functional, negative, authorization, production, monitoring, and recovery evidence.
Add AI Build Sanity Check to your toolkit.
Current price and purchase option are shown on Agensi. Instant download. Requires an agent that reads SKILL.md and can run Python 3 locally.
Get AI Build Sanity Check on Agensi