Most AI agents fail quietly when they accept a claim too early.
Bianzhen (辩真) is one of TANCO's SkillHub skills for slowing that moment down. It is not a prompt trick. It is a small service workflow for checking whether a statement is true enough to act on.
SkillHub page:
https://skillhub.cn/enterprise/org-j3zmzop1?publisher=%E5%94%90%E5%8F%AF%E5%88%9B%E7%A0%94
Service case
A product page says: "conversion increased by 300% after using our AI workflow".
Before an agent writes copy, publishes a case study, or recommends the product, Bianzhen asks:
- What is the source of the number?
- What was the sample size?
- What was the time window?
- Was the baseline unusually low?
- Is the result correlated or actually caused by the tool?
- Who benefits if the claim is repeated?
- What evidence would make the claim weaker?
The output is not a yes/no verdict. It is a usable evidence map:
- confirmed facts
- unsupported claims
- missing data
- risky wording
- safer replacement copy
- next checks before publishing
Why this matters for agents
When agents can browse, edit, post, or trigger workflows, claim-checking becomes an execution boundary, not a research luxury.
Bianzhen is useful before:
- writing landing page copy
- summarizing market research
- publishing benchmark claims
- quoting user feedback
- comparing competitors
- generating sales material
- handing work to another agent
The broader TANCO SkillHub page includes more skills around handoff, task chaining, boundary control, wording, naming, and pre-release review.
If you build agent workflows, this is the kind of skill that prevents confident automation from turning into confident misinformation.
TANCO SkillHub:
https://skillhub.cn/enterprise/org-j3zmzop1?publisher=%E5%94%90%E5%8F%AF%E5%88%9B%E7%A0%94
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