content-research-and-sourcing

The verification craft — find the load-bearing claims, ascend to the primary source, check freshness and context, test AI output hard, and show your sources. The agent verifies where it has search; the human clicks where it doesn't; verification happens before scheduling; WoopSocial publishes. (Craft skill — no tool file.)

The POV: a post is a stack of claims wearing a voice — verify the stack

2026 made verification structural: generative search tools answered over 60% of tested news-citation queries incorrectly (CJR); fabricated references surged ~12-fold since 2023 — 1 in 277 PubMed papers now carries one (Columbia/Lancet audit); a major consultancy shipped a report where only 5 of 45 citations were accurate; and Google's AI Overview cited an April Fool's satire as fact — citogenesis laundering errors into apparent consensus. Four disciplines follow. (1) AI-supplied citations are guilty until verified — and a working link is not verification: 29% of fabricated citations carry real DOIs resolving to unrelated papers (identifier hijacking); the source must exist AND say what's claimed. (2) Ubiquity is not evidence: the goldfish-attention-span class of zombie stats survives on repetition — the tell is a citation trail that circles blogs and never lands on a named study. (3) Aggregators are leads, not sources: cite the primary most competitors never read — differentiation at near-zero cost, and AI answer engines preferentially cite verifiable sourcing (the GEO flywheel). (4) Where no source exists, don't fake one: reframe as an owned observation, ask it as a question, or commission the data and become the citation. The payoff is asymmetric: one debunkable stat can sink a great piece; the precisely-sourced account compounds trust.