# Protocols, checklists & worked examples

## The claim-inventory triage (per piece, ~5 min)
List every factual claim → mark LOAD-BEARING (headline stat, causal claim, quote, anything about health/money)
vs COLOR → load-bearing gets the full chain; color gets a sanity glance. A piece with >5 load-bearing claims
is probably two pieces.

## The citation-verification protocol (per AI-supplied or inherited citation)
1. EXISTS: search title + authors independently (not just the given link) ✓
2. HONEST LINK: open it — does the DOI/URL resolve to THIS paper, not an unrelated one? ✓
3. SAYS IT: find the claim in the source (not just the abstract's vibe) ✓
4. CURRENT: date, supersession, retraction check ✓
5. LOG IT: claim -> source -> date -> link ✓
Fail any step -> replace or cut. Never ship "verified-ish."

## The zombie-stat autopsy (when a stat is "everywhere")
Who is the NAMED study? What was the method/sample? Does the number mean what the post implies? If the trail
circles blogs without landing on a study: it's a zombie — replace with a verifiable stat, an owned
observation, or an honest question.

## The source log (lives with the calendar)
| Claim | Source (primary) | Date | Link | Verified by/on |
Reused stats re-check the date; corrections update one row, not an archaeology dig.

## Attribution patterns per surface
Text post: "per [source, year]" in-line, link in comments/caption per platform norm · Quote card /
infographic: source + date IN the design · Video: verbal attribution + on-screen credit · Carousel: sources
slide at the end. Never bury the source so deep the claim floats free.

## Worked example A — "Blunt indie founder" (the AI-citation catch)
"drafted a post with an ai research assistant. it gave me four studies with links. checked them: one real, one
real-but-says-the-opposite, one DOI that opens a paper about soil bacteria, one doesn't exist. shipped the
post with the one real study and an owned observation. took 15 minutes. the alternative was being the guy
whose pinned post cites soil bacteria." — the protocol run, identifier hijacking caught.

## Worked example B — "Warm bookkeeping studio" (the zombie replaced)
"We nearly opened with that famous 'we check our phones 150 times a day' line — but the trail never reached an
actual study, just blogs quoting blogs. So we used our own little truth instead: 'of the last 40 receipts
clients sent us, 31 arrived after ten pm.' Smaller number, entirely ours, and the comments loved it. One
small step: when a stat won't show you its study, show your own." — zombie killed, owned data as the upgrade.

## Never
Publish an unverifiable number as fact · trust a citation because the link works · cite the aggregator when
the primary is one click up · reuse a retracted or superseded stat · dress intuition as research ('studies
show') · fabricate or misattribute a quote · skip the heightened YMYL bar · fabricate a source log · verify
after scheduling instead of before.


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资料：Frank Heijdenrijk / pavelhov/social-media-skills

原始版本：https://github.com/pavelhov/social-media-skills/blob/1680b37bf0dc32b52da247a8196ef27a6cd47bd4/skills/content-research-and-sourcing/references/protocols-and-templates.md

许可：MIT。目录与内部链接已经整理，未收录图片已省略。

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