Agent tooling
CompleteTech LLC provides an offline tool that scans code repositories to find and prepare specific places where an AI decision might be useful.
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No live-model benefit has been measured, as current validation relies entirely on synthetic data and mocked network responses. Static scans cannot detect dynamic behavior, and the supported code edits are narrow. The test runner is not a secure sandbox, and this independent project has no official affiliation with TypeSafe.
Start with a trusted project's rule that sorts messages or chooses among a few known actions. The local scan reads source files to suggest where a model judgment might help. Review those suggestions before approving any exact code change; finding no useful place is a valid result.
Use synthetic examples to inspect proposed decisions without live model calls, but do not confuse that with measured improvement. The test runner can execute code and is not a secure sandbox. Use only trusted code, and keep program-owned permission checks separate from model suggestions.