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Verifying reasoning

Skill AdrianParedez/capability-fabric/skills/verifying-reasoning

A fast, on-demand check that catches wrong answers before they ship, surface assumptions, seek disconfirming evidence, and validate the result against the question. Use before committing to a high-stakes conclusion, an irreversible action, or a final answer. Invoked as a quality gate by decomposing-tasks, progressive-research, guarding-code-quality, and the meta-skills.From its SKILL.md

Install
npx -y skills add AdrianParedez/capability-fabric --skill verifying-reasoning

Assembled from the repository path, not quoted from the project. Check it against their README if it does not work.

One thing to look at

  • 1 stars1 stars. Stars are a popularity signal and not a quality one, but at this level it is likely that nobody has read this closely except its author, and you would be relying on your own review.

What its file declares

Copied from the file, not written here

The file declares its own license as Apache-2.0. That is the author’s claim about this one file, and it is not the same thing as the license GitHub reports for the repository, which is listed with the other numbers below.

SKILL.md

3.9 KB, 819 tokens by cl100k_base, as published. Nobody here has run it

Verifying reasoning

The costliest failure is a confident wrong answer. This skill is a cheap, deliberate pass that tries to break a conclusion before you rely on it. It has no outgoing dependencies, any skill or tier can invoke it as a gate.

Use this when

  • About to ship a final answer, commit a fix, or take an irreversible action.
  • A conclusion is load-bearing and being wrong is expensive.
  • Sources disagreed, or the reasoning chain was long.
  • Skip for low-stakes, trivially reversible steps, verification has a cost too. Match rigor to stakes.

The check (run in order, stop early if it holds)

- [ ] 1 RESTATE the claim/result and the exact question it answers
- [ ] 2 ASSUMPTIONS list what must be true for it to hold; flag the shakiest
- [ ] 3 DISCONFIRM actively look for evidence/cases it's WRONG (not more support)
- [ ] 4 TEST       if a cheap objective check exists, run it (don't reason about it)
- [ ] 5 EDGE       check boundaries: empty/zero/max/null/concurrent/error paths
- [ ] 6 ALIGN      does the result actually answer the question asked (not a near-miss)?
- [ ] 7 VERDICT    confirmed | confirmed-with-caveats | refuted | unknown -> next step

Principles

  1. Seek disconfirmation, not confirmation. Finding three more reasons you're right is worthless; finding one case where you're wrong is everything. Ask "what would make this false?" and go look for it.
  2. Prefer a test over an argument. If you can run the code, query the data, or check the doc, do that, an objective check beats any chain of reasoning. Reasoning is the fallback when no test exists.
  3. Name the assumptions. Most wrong answers are right given a false premise. Surfacing premises is where errors hide.
  4. Check edges, not just the happy path. Empty input, zero, max, null, off-by-one, concurrency, the error branch. Bugs and bad conclusions cluster at boundaries.
  5. Answer the asked question. A correct answer to a slightly different question is a wrong answer. Re-read the actual ask.
  6. Calibrate effort to stakes. A one-line sanity check for small things; the full pass for irreversible or high-impact ones. Verification is insurance, buy the right amount.
  7. State a verdict, not a vibe. Output one of: confirmed / confirmed-with-caveats / refuted / unknown, and for anything but "confirmed," the next step.

What "disconfirm" looks like

  • Code: write/Find the input that breaks it; run the actual test; check the error path.
  • Research: find a primary source that contradicts the claim; check the version/date.
  • Plan: find the step ordering that causes the dependency to fail.
  • Math/logic: plug in the boundary; check units; re-derive one step independently.

Runtime adaptation

  • Minimum: none for the reasoning pass. If a tool can run a real check, prefer it.
  • This skill is deliberately tool-light so it works identically on Claude Code, Codex, OpenClaw, Hermes, etc. It is the portable quality primitive other skills call.

Files

  • references.md, failure taxonomy, disconfirmation techniques, calibration.
  • examples.md, catching a wrong answer in code, research, and a plan.
  • templates/verification.md, the check to fill in.
  • checklists/quick-gate.md, the 60-second version for medium-stakes calls.
  • benchmarks/, error-catch-rate method.

What ships with it: 5 files

6.8 KB alongside SKILL.md

benchmarks/

checklists/

templates/

Gives 0 of the 12 instructions most quality gates skills give in 819 tokens

Counted across 1,524 of the 2,830 authors here whose files we hold, read 2026-09-06

  • Read full output and check exit codein 45 of 1524, across 40 files
  • Verify output confirms the claimin 44 of 1524, across 39 files
  • Identify the command that proves the claimin 43 of 1524, across 39 files
  • Execute the full verification commandin 36 of 1524, across 30 files
  • Produce a verification reportin 34 of 1524, across 18 files
  • Review git diff changesin 30 of 1524, across 16 files
  • Fix build failures immediatelyin 29 of 1524, across 9 files
  • Group findings by severityin 28 of 1524
  • State claim only with evidencein 27 of 1524, across 22 files
  • Verify regression tests with red-green cyclein 26 of 1524, across 22 files
  • Run the full test suitein 26 of 1524, across 25 files
  • Run test suite with coveragein 25 of 1524, across 10 files

Said here and by no other author read

  • restate the claim and the original question
  • list all assumptions required for the conclusion
  • actively seek evidence that disconfirms the conclusion
  • check edge cases and boundary conditions
  • verify the result answers the specific question asked
  • state a final verdict of confirmed or refuted

Grouped from the skills themselves: near-identical wordings counted once, and counted by distinct author, so one author publishing three of these counts once. Length counted with cl100k_base; the agent that loads this file may tokenize it differently.

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