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Writing With Evidence

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Support claims with specifics, data, and examples so writing is credible and concrete instead of vague assertion. Use when writing makes claims that need backing, or reads as generic and unconvincing.

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  • Added September 5, 2026
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Scanned September 5, 2026

npx -y skills add Amey-Thakur/AI-SKILLS --skill writing-with-evidence --agent claude-code

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SKILL.md
---
name: writing-with-evidence
description: Support claims with specifics, data, and examples so writing is credible and concrete instead of vague assertion. Use when writing makes claims that need backing, or reads as generic and unconvincing.
---

# Writing with evidence

Assertion tells; evidence shows. "Our approach is faster" is a claim the
reader must take on faith; "it cut the median response from 2.1s to 600ms"
is a fact they can weigh. Specific, verifiable support is what separates
persuasive, credible writing from generic filler.

## Method

1. **Replace adjectives with evidence.** Every "significant", "powerful",
   "seamless", "robust" is a claim dressed as a fact. Cut it and show the
   thing: the number, the example, the before-and-after. If you cannot
   substantiate the adjective, the reader should not believe it, and you
   should not write it (see the AI-tell words to avoid in adjust-tone,
   proofread).
2. **Prefer the specific to the general.** "Many users struggled" is weak;
   "of 50 new users, 34 could not find the export button" is strong. Real
   numbers, named examples, and concrete detail carry weight that vague
   quantifiers ("often", "most", "a lot") cannot.
3. **Choose evidence that fits the claim's weight.** A big claim needs
   strong evidence (data, multiple examples, a source); a small one needs
   only an illustration. Match the support to what you are asking the
   reader to believe, and do not over-claim past what your evidence shows.
4. **Show your sources where it matters.** For factual or contested
   claims, cite where the number or fact came from, so the reader can
   trust it and check it (see fact-checking, source-evaluation). Unsourced
   statistics read as invented, because often they are.
5. **Use examples to make the abstract concrete.** A principle followed by
   "for example..." lands where the principle alone slides past. One
   well-chosen, specific example teaches more than three sentences of
   generalization (see clear-writing's concrete-nouns rule).
6. **Be honest about the evidence's limits.** Note the sample size, the
   caveat, the case where it does not hold. Acknowledged limits build
   credibility; hidden ones destroy it when found. Overstated evidence is
   worse than modest evidence honestly framed (see persuasive-writing's
   concede-what-is-true).

## Boundaries

- Evidence must be real: fabricated numbers, invented quotes, or
  cherry-picked data are the fastest way to lose trust permanently, and AI
  writing is prone to confident invention, so verify before asserting
  (see fact-checking).
- Not every sentence needs a citation; over-hedged, over-sourced prose is
  its own failure. Support the load-bearing claims; state the obvious
  plainly.
- Evidence supports a point; it does not replace one. A pile of facts
  without a thesis is a data dump, not writing (see structure-and-flow,
  data-to-insights).

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