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AI project guidelines

gitpulse: terminal CLI that collects deterministic GitHub repository signals and renders them as a compact project-health report.

  • Key commands

    • bun test
    • bun run typecheck
    • ./gitpulse owner/repo (local wrapper, same entrypoint as the published CLI)
    • bun run visuals after any change to human-readable output, then inspect the artifacts
  • Key documentation

  • Hard contracts

    • Bare repository shorthand stays local-only and exact. The root command never searches GitHub for an unknown word, with or without --lucky. It fails and asks for owner/name. Remote discovery lives under gitpulse search. Zero-argument inference reads local Git remotes only and never resolves fork parents through the API. Push back on any proposal that erodes this.
    • Phase 1 stays deterministic and API-driven. No AI dependency, no subjective NLP.
    • Reserved command words (docs, web, starred, search, user, history, cache, config, completions) are commands, never shorthand.
    • Top-level docs/*.md describe the shipped implementation. Proposals and deferred ideas go under docs/next-features/.
    • No backwards compatibility. Prefer the cleaner command contract and delete the old one.
  • Iron Laws

    • Tokens are expensive, state of the art models need minimal guidance, don't repeat yourself, don't babysit, don't be over-specific.
    • AI-native project. All code is AI-generated.
    • Minimal attention when model implements without errors, we document in more detail when model struggles.
    • Do not expect the user to have read each line, don't lose him on the internals, give visibility on a higher-architectural level.
    • No journaling: code comments / documentation describe current state, they don't carry a log of their own edit history.