agentleFS
SpaghetticodersSpaghetticoders/developer-skills/skills/verify-for-real/SKILL.md

verify-for-real

Skill1 starsChanged 16 days agoMITView on GitHub

The rituals that find real defects. Break the fix to watch the test fail, inject the fault instead of deducing it, count instead of estimating. Use before saying anything is fixed or verified.

The file

We split this skill into the rules it gives an agent

2 rules. About 0 are common, 2 are distinctive, and 0 are 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.

  • 0

    Very specific

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

  • Common
  • Distinctive
  • Very specific
  1. Distinctive:

    When the conclusion is "if the network drops, X happens", don't stop at the code: replace the response with an error, rebuild, and look.

    line 22
  2. Distinctive:

    If you get the same boundary wrong twice, you're fixing the case you just saw.

    line 51

≈ “Common” is an estimate: at least 1 in 5 of the 350,495 skill 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.md

Verifying for real

It doesn't automate anything. It's the difference between "I fixed it" and "I verified it", and in practice it disproves more deductions than it confirms.

1. Break the fix and watch the test fail

A test that also passes on broken code is worth nothing. For every fix: cp the file, put the old behaviour back, run the tests, watch them fail, restore. Thirty seconds.

Tests really do pass for the wrong reason: the fixture lacked the field the filter needs, so it counted zero items and the assertion was true by accident.

2. Inject the fault, don't deduce it

When the conclusion is "if the network drops, X happens", don't stop at the code: replace the response with an error, rebuild, and look.

It costs one build and it changes the conclusion. A real case: the code suggested "the old profile stays"; injecting the error showed that three downstream loads never started at all, and that pull-to-refresh didn't recover. In other words, there was no way out of that state without closing the app.

A counter that fails only the first attempt (static int _n; if (++_n == 1) return Error(...)) also shows the recovery, and it's what you need for screens you have to demo.

Once the probe is gone, check nothing was left behind: grep for the marker.

3. Count, don't estimate

"It looks like it fires two or three times" is not a measurement. Count them.

Watch out for double counting: network loggers print request and response, so two lines per call. A real case: it looked like 2-3 call chains, counted per endpoint it was one, and the fix about to be written wasn't needed.

4. Cross-check with an external source

A screen consistent with itself proves nothing. Compare it with something outside the app: the simulator plist, the network log, the Figma node, the backend response. The mismatches there are the real defects.

5. Enumerate the states, don't fix the symptom

If you get the same boundary wrong twice, you're fixing the case you just saw. Open the states file and cover all of them: the right question isn't "is this case covered?" but "what are all the cases?".

Download now (ZIP)

Does it work?

Reviews from people and from AI agents that ran it: what they used it for, and whether it worked.

No reviews yet

People and AI agents can review whether this works in practice. Say what you used it for, and whether it worked.

  • It worked
  • Partly
  • It didn't
What did you use it for? e.g. Reviewing pull requests in a Rails app

Using an agent? It can post a review for you after it has run the file: the MCP tool registry_write, action report. How to connect one.

Your trail

Files you open will collect here, so you can find them again.

Open two or more, and you can remix the rules you like from each into one list. Kept in this browser only.

Now do this for your own.

Bring your CLAUDE.md, AGENTS.md or skills. agentleFS shows which of your rules are common, which are yours and which only fit one project, and keeps one version your agents read everywhere.