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Fadi88Fadi88/one-man-startup/.cursor/rules/skill-twin-check.mdc

one-man-startup / rules

Cursor rule16 starsChanged 2 days agoMITView on GitHub

Guard important business arithmetic with an independent, dependency-free reference implementation checked against the production code's real output. Use for prices, billing, quotas, scores, forecasts - any figure where a wrong answer still looks like an answer.

We split this skill-twin-check.mdc into the rules it gives an agent

3 rules. About 0 are common, 2 are distinctive, and 1 is very specific to this project.

  • ≈0

    Common · estimate

    Many files like this have a rule of this kind.

  • ≈2

    Distinctive · estimate

    This author's own choices. Worth a look.

  • 1

    Very specific

    Tied to their project's names, files or tools. Probably skip.

  • Common
  • Distinctive
  • Very specific
  1. Very specific:

    Put the twin under tools/twins/, in plain Python with no libraries that do the hard part for it (a twin that calls the same library proves …

    line 16
  2. Distinctive:

    Read constants from the production source rather than retyping them, so a changed constant cannot hide.

    line 18
  3. Distinctive:

    Use it where it pays. Most code does not need a twin.

    line 26

≈ “Common” is an estimate: at least 1 in 5 of the 6,350 Cursor rule files we read have a rule of the same kind, not the same words. “Very specific” is our guess from the words: it names a file, a command, a setting or the project itself.

Keep what fits and drop the rest. Your version, ready for your agents.
Files
skill-twin-check.mdc
---
description: "Guard important business arithmetic with an independent, dependency-free reference implementation checked against the production code's real output. Use for prices, billing, quotas, scores, forecasts - any figure where a wrong answer still looks like an answer."
alwaysApply: false
---

<!-- Generated by tools/sync_adapters.py from skills/twin-check/SKILL.md. Edit the source, not this file. -->

# Twin check

Some bugs produce a number that is wrong and looks right. Tests written by the same mind that
wrote the code tend to share its mistakes. A twin is a second implementation, written plainly,
in a different form, and compared against the real code on real inputs.

## How

- Put the twin under `tools/twins/`, in plain Python with no libraries that do the hard part for
  it (a twin that calls the same library proves the library works, not your code).
- Read constants from the production source rather than retyping them, so a changed constant
  cannot hide.
- Have the production test suite dump its outputs for a fixed set of inputs, and a check under
  `tools/checks/` compare twin and dump field by field, with a stated tolerance.
- A missing dump is a loud SKIP, never a pass.
- The twin's header lists the cases where a wrong answer would still look plausible, and the
  check covers each.

Use it where it pays. Most code does not need a twin; money and anything the founder makes
decisions from usually does.

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