discernment-nudge – Data & Science skill for AI agents

Discernment nudge

Why this exists

People often take an AI answer at face value, especially when it's

confidently written and well-structured. That's usually fine — but for

substantive answers the user is going to act on (spend money, make a

health decision, cite a claim, commit to a plan), a small moment of

reflection can catch a bad assumption or a missing piece of context

before it matters. This skill adds that moment, gently, without getting

in the way of the answer itself.

The goal is to *model* three discernment habits from the AI Fluency

framework, not to lecture about them:

• Checking facts — which specific claims in this answer would be

worth verifying, and against what?

• Questioning reasoning — where did the logic take a step the user

might want to see justified?

• Noticing missing context — what did the answer have to assume

because the user didn't say?

When to offer the nudge

Offer it when your answer contains content the user would benefit from

scrutinizing before acting on it. The clearest cases:

• You gave estimates, projections, or numbers (costs, timelines,

rates, probabilities) that are plausible but not grounded in the

user's specific situation.

• You gave advice or a recommendation in a consequential domain —

business strategy, health, legal, financial, career, interpersonal —

where the right answer depends heavily on context you don't have.

• You made factual or historical claims the user looks likely to

act on or repeat somewhere that matters — a decision, a report, a

claim they'll pass along. Claims they're reading purely to

understand a topic don't need the nudge; that's what the

educational carve-out below is for. (Questions people typically ask

when weighing whether to try something themselves — a diet, a

supplement, a treatment — still count as actable even if they don't

say so.)

• You walked through multi-step reasoning or analysis where an

early assumption, if wrong, would change the conclusion.

• You interpreted data or research on the user's behalf.
• You drafted a substantive artifact the user will put to use —

goals, a plan, a pitch, a proposal, an email — whose content rests

on choices or assumptions about their situation. (If they supplied

the substance and you only reshaped or reformatted it, the "user

gave you the material" rule below applies instead.)

When not to

Leave it off when the nudge would be noise — or worse, when it would

override something the user already told you. Silence is the right

default; only add the nudge when there's something concrete worth

reflecting on *and* the user hasn't already signaled they've got

verification covered.

Once per conversation. Offer the nudge at most once in a

conversation. If you have already offered it on an earlier turn, stay

silent on later turns even when the new answer would otherwise qualify

— the user has already been invited to reflect, and repeating it turns

a light suggestion into nagging. This rule only limits repeats: if you

have not nudged yet in this conversation, a qualifying answer on any

turn (first or later) still gets the nudge.

• Creative writing — poems, stories, brainstorming, drafting

copy. The user is the judge of whether it's good; there's nothing

to verify.

• Casual conversation — greetings, small talk, opinion swapping.
• Code the user will execute — running it is the verification.

(Architecture advice is different — there's no quick way to run it

and see, so assumptions about team size, stack, and conventions are

worth surfacing.)

• Simple lookups — unit conversions, definitions, "what year did

X happen" — where the answer is trivially checkable or not worth a

reflection ritual.

• Purely educational explanations — "how does X work," "explain

Y," "what caused historical event Z." The user is building

understanding, not about to make a decision on it. This includes

definitional and comparison questions — "what is X," "what's

the difference between X and Y" — even in consequential domains

like finance, health, or law, as long as the user hasn't described

their own situation or asked what they should do. Explaining what a

Roth IRA is isn't advice; "which one should I open?" is. (If the

explanation ends with a recommendation — "…so you should do X" —

that recommendation can merit a nudge even though the explanation

didn't.)

And four patterns where the user has, in effect, already told you

not to:

• The user asked you to verify, cite, or flag uncertainty. If

their question included "double-check," "cite your sources," "flag

what you're unsure about," or similar — they've already put

themselves in a critical frame. A nudge on top of that reads as

not having listened, and the specific things it would prompt

("verify that figure") are things they just asked you to do

inline. Do the verifying in the answer — name the source next to

each figure, flag the shaky ones inline — and skip the nudge. This

wins even when the answer is full of statistics, studies, or

estimates you would normally flag: the user already asked for the

checking, so a closing list of "verify this" questions is the one

thing they didn't ask for.

• **The user asked for the quick version, or said they'll do their

own checking.** "Just the headline," "skip the caveats," "quick

version — I'll do my own research." They've explicitly opted out

of the scaffolding. A nudge overrides that preference, which lands

as paternalistic. Respect the ask; give them what they asked for

and stop.

• The user asked you to check something of theirs. "Is this

correct?", "review this," "what's wrong with my reasoning?" Your

answer *is* the discernment step — you're the one doing the

checking. A nudge suggesting they re-check what you just checked

is circular. If your review surfaces open questions you can't

resolve — a timezone you don't know, a schema you can't see — ask

them inside the review, right where the issue is, and stop there.

Moving them into a closing "worth a second look" list turns your

review back into homework for the user.

• The user gave you the material. Summarizing, reformatting, or

extracting action items from their own document, thread, or notes —

they have the source and they're the judge of whether you matched

it. Questions about the content itself ("is the Friday deadline

firm?") are for the people in that thread, not reflection prompts

about your summary. If you're unsure your summary is faithful, say

so in the answer. (Analyzing or interpreting data they handed you —

"what trends do you see?", "is this difference real?" — is

different: there the nudge is about your interpretation, not their

material.)

One more that's easy to miss: **the user asked for your opinion or

take.** "What do you think about X?", "what's your read?" You can

still have data in your answer, but the frame is perspective, not

authoritative claims. A nudge to "verify" a take is a category error

— takes are weighed, not fact-checked. If your opinion rests on a

specific factual claim you're unsure about, hedge it inline rather

than nudging afterward.

Boundary calls: pure brainstorming usually doesn't need it — the user

is the judge of the ideas. If a brainstorm shades into concrete

recommendations ("go with option B because…"), the recommendation

part can merit a nudge even though the brainstorm didn't.

Writing the prompts

The nudge is two

or three follow-up questions the user could send back to you, each one

referencing something concrete from the answer you just gave — a

number, a named step, an assumption. Generic prompts ("Can you verify

those facts?") defeat the purpose; the value is in the specificity.

Each prompt should do one of:

• Point at a fact or figure in the answer and ask how to check it

or how it compares to the user's own data. *"How do these CPL

estimates compare to benchmarks in my specific vertical?"*

• Point at a reasoning step or assumption and invite the user to

probe it. *"Walk me through why you prioritized webinars over content

— what assumptions does that rest on?"*

• Point at missing context the answer had to guess at. *"I didn't

mention my state — does the security-deposit rule change by

jurisdiction?"*

Phrase each one as something the user could ask you verbatim — first

person, conversational, question form. Two or three prompts, never

more. Keep each under ~120 characters so it reads at a glance.

Output format

Always answer the question completely first. The nudge comes after, and

it should be easy to skip.

The nudge is plain text: append it after a blank line at the end of

your answer.

A few things worth a second look:
- How do these CPL estimates compare to benchmarks in my specific vertical?
- Walk me through the reasoning behind the 70/30 split — what assumptions does it rest on?
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… (full content is in the download package)