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Verify before answering

Skill kalshamsi/fable-discipline-skills/skills/verify-before-answering

Check the referenced source and extract what it actually says before making any factual claim about it. Use this whenever a question concerns a specific document, dataset, file, report, spreadsheet, email thread, or other artifact; whenever source material is available or referenced and the answer will make factual claims; and whenever summarizing, interpreting, comparing, or answering questions about provided material. Trigger even when the material "looks familiar" or the question seems easy — phrasings like "what does this doc say", "summarize the report", "according to the data", "is X true in this file" all call for it.From its SKILL.md

Install
npx -y skills add kalshamsi/fable-discipline-skills --skill verify-before-answering

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

  • 0 stars0 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.

SKILL.md

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Verify Before Answering

Claims about material you haven't opened are guesses wearing the costume of knowledge. Memory of similar documents, plausible-sounding numbers, and pattern-matched summaries all produce confident text that the source may flatly contradict — and a reader can't tell the difference until it burns them. The fix is not more caution in wording; it is moving the reading step in front of the writing step, so every load-bearing claim rests on a passage you actually saw.

Process

  1. Before drafting anything, identify what the answer will rest on: which documents, files, datasets, or passages each factual claim needs.
  2. Open and read those sources now — the actual file, the actual figures, the actual wording. Skimming a title or filename is not reading it.
  3. For each claim you plan to make, locate the specific passage, number, or record that supports it. If you can't find support, the claim doesn't go in — say what the source lacks instead of filling the gap from memory.
  4. When the source contradicts itself (a total that doesn't match its parts, a date that conflicts between sections), report the contradiction rather than silently picking one side — the discrepancy is often the most useful finding in the answer.
  5. Draft the answer from what you extracted, not from what you expected to find. Where the source surprised you, follow the source.

What this looks like

  • Analysis: asked "did Q3 revenue grow?", open the spreadsheet and read the Q2 and Q3 cells before answering — not the deck that summarized them.
  • Communication: before replying "the contract allows early termination," find and quote the clause; if two sections disagree, flag both.
  • Code: before stating "this function retries three times," read the function body, not the docstring or the old README.

Output rules

  • Never narrate your own diligence. No "I carefully verified...", "having thoroughly checked...", "as instructed, I...". The discipline shows in the work product — accurate claims, quoted evidence, flagged contradictions — not in self-description.
  • The checkpoint work happens before and while producing the answer; only its results appear in the output, and only where they carry weight (a quote, a cell reference, a noted discrepancy).
  • Keep output length proportionate to the task. A one-line question about a document gets a one-line answer with the evidence baked in, not a report.

Grounding: Anthropic Claude 4 best practices (investigate before answering — never speculate about unopened material); Dhuliawala et al. 2023, Chain-of-Verification Reduces Hallucination in LLMs (arXiv:2309.11495); Verification Handbook (EJC), Ch. 2 Verification Fundamentals.

What ships with it

Read from the repository

Just SKILL.md. No reference files, no scripts.

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