# Derive Independently Then Compare > Derive an answer from the source corpus a second time, without reading the first derivation, then compare — before trusting a conclusion drawn from a large body of transcripts, notes, or documents about what someone wants, prefers, or constrains. Use when a claim about a person's stated intent or a parameter cannot be traced to a quote, or before that claim is reported as fact. Runs before sanity-check and devils-advocate, not instead of them — a reviewer or an opposing case inherits whatever inputs the first pass fabricated, and this is the only one of the three that re-reads the source rather than the write-up. Not ask-a-council (different positions on a shared question, not the same question re-derived from source); not determine-signals (finds what was already checked, not whether what was reported was actually found there). - Skill: `jonhill90/derive-independently-then-compare` (Agent Skill, multi-file: 3 files) - Install (CLI): `npx skillmds@latest add jonhill90/derive-independently-then-compare` - Raw SKILL.md: https://api.skillmd.com/api/skills/jonhill90/derive-independently-then-compare/raw - Safety review: pending - Works with: Claude Code, Claude.ai, OpenAI Codex - Category: Coding & Dev Tools - Author: jonhill90 (https://skillmd.com/u/jonhill90) - Updated: 2026-09-17 - Page: https://skillmd.com/skills/jonhill90/derive-independently-then-compare --- # Derive Independently, Then Compare A reviewer checks whether reasoning holds. It cannot see that the inputs were fabricated — it reads the write-up, not the source, and inherits whatever the write-up claims the source said. The only check that catches a fabricated input is one that goes back to the source itself and derives the answer again, without looking at the first answer first. ## Reach for this when - A claim about what someone wants, prefers, or requires is about to be reported as fact, and it rests on reading a large corpus — transcripts, issues, notes, a chat history — rather than on a single stated instruction. - The claim names a specific parameter, constraint, or preference and you are not sure you could produce the exact quote it came from on demand. - The corpus is large enough that "I read enough of it" is doing unverified work — the failure this skill targets gets *worse* as the corpus grows, not better, because the unread fraction rises and locking on after two or three files becomes easier to do unnoticed. Do not reach for this to test whether already-produced reasoning is internally consistent — that is `sanity-check`, and it runs *after* this one, on inputs this skill has already checked. Do not reach for this to argue against a conclusion — that is `devils-advocate`, and it also assumes the inputs are real; this skill is what earns that assumption. ## The worked example Asked whether Jon wanted a live terminal, an agent read the corpus once and reported: 1. It took **one** quote about *chat threads* being live. 2. It generalized that quote to *terminal rendering* — a different subject the quote never addressed. 3. It **invented** a parameter Jon never stated — `survives-a-web-frontend` — which had **zero hits across 1,968 typed turns**. 4. From the invented parameter it declared a "near zero-possibility conflict." 5. It reported all of this to Jon **as derived from his own words**. The reasoning from step 3 to step 4 was internally coherent — a reviewer reading only the write-up would find no fault in it. The defect was in step 1 through 3: the inputs were invented, not derived. A second, independent derivation from the same 1,968-turn corpus — one that never read the first agent's write-up — knocked down two of the three underlying claims and surfaced that the third had no source at all. Read [references/worked-example.md](references/worked-example.md) for the full derivation-by-derivation breakdown. ## Procedure 1. **Enumerate before deciding.** Before drawing any conclusion, state how much of the corpus exists and how much you have actually looked at — N and the denominator. "I read 3 of 40 transcripts" is honest; "I read 3 transcripts" is not, because it hides whether 3 was a survey or the whole population. A conclusion with no stated denominator is not a conclusion — treat it as underived and go back. 2. **Survey breadth before committing to depth.** Sample across the full space first — different time periods, different sources, different threads — before reading any one part closely. The failure this guards against is locking onto an interpretation after two or three files and never revisiting it once contradicting material shows up later in the corpus. 3. **Derive twice, independently, before comparing.** Produce a first derivation from the source. Then produce a second derivation from the *same source*, by an agent or pass that has not read the first derivation's answer or write-up — only the raw corpus. If the second pass can see the first pass's conclusion before it finishes its own, it is review wearing a different name, not independent derivation, and it will inherit the first pass's fabrications instead of catching them. 4. **Cite or drop.** Every claimed parameter, preference, or constraint must carry the quote it came from — source and locator, not a paraphrase. If you cannot produce the quote, the claim is an invention, not a finding: drop it, or mark it explicitly as unsupported rather than reporting it as derived. This is the cheapest guard in this skill and alone would have caught the worked example's fabrication. 5. **Compare, and treat every disagreement as a finding.** Line the two derivations up claim by claim. Where they agree, that is weak evidence — two passes over the same corpus converging is expected even when both are shallow. Where they disagree, that is strong evidence something is wrong: one derivation cited a quote the other didn't find, one invented a parameter the other's pass through the same material never touched. Do not average disagreements away or split the difference — chase each one down to which derivation the quote actually supports, and report the disagreement itself as a result, not just its resolution. ## What this is not - **Not `devils-advocate`.** That skill attacks a *conclusion*, assuming it is wrong and building the strongest opposing case. This skill attacks the *inputs* the conclusion was built on, and it must run first — there is no point building or opposing a case whose premise is fabricated. - **Not `sanity-check`.** That skill dispatches a reviewer against reasoning that has already been produced, checking whether it holds together. It reads the write-up, so it inherits whatever inputs the write-up claims — exactly the gap this skill exists to close before a sanity-check pass would be trustworthy. - **Not `ask-a-council`.** A council assigns several reviewers *different positions* on a shared question because the candidate failure modes differ in kind. This skill asks the *same* question of the *same* source twice, independently, and checks whether the two derivations agree — not different lenses, the same lens applied twice blind. - **Not `determine-signals`.** That skill finds what has already been checked, so a question isn't re-asked when it's already answered somewhere. This skill doesn't ask whether something was checked — it verifies that what was *reported* as found in the source was actually in the source. ## Where this came from A measured instance: an agent asked whether Jon wanted a live terminal fabricated a parameter (`survives-a-web-frontend`, zero hits across 1,968 typed turns) and reported it as derived from Jon's own words. An independent re-derivation from the same corpus — run blind to the first agent's write-up — knocked down two of the three underlying claims and surfaced that the third had no source at all. A review of the write-up alone would not have caught this: the reasoning was coherent, only the inputs were invented. See [references/worked-example.md](references/worked-example.md).