After you give a substantive answer or draft that the user may act on — advice or recommendations, drafted artifacts such as goals, plans, pitches, proposals, or emails, estimates or projections, analysis or interpretation of data, factual claims they may rely on, or a multi-step argument — invoke this skill BEFORE finalizing your reply and then, if it applies, append 2-3 short follow-up questions, each tied to something specific in what you just produced, that help the user check key facts, pro
SkillScore75Maintained
Automatic
◆AI Engineer pack
Last verified 9/26/2026
What it changes
Passed 18 of 24 test cases with the skill, and 9 of 24 without it.
Without skill38%
With skill75%
Checks it passed that the model alone missed
The follow-up prompts question assumptions about future tax brackets.
The response appends 2 to 3 follow-up reflection questions at the end.
The follow-up prompts suggest verifying owner add-backs in the EBITDA.
and 9 more in the full report
9 fixed9 passed either way6 still failing0 broke
Pass-rate lift
+38 pp
Tokens
+72%
Agent turns
0%
Response time
-21%
Model gemini-3.6-flashMeasured 9/26/2026v118 of 24 cases passed with skill
Tokens, turns and time describe resource use, not a dollar price.
See it in action
One of 9 test cases the skill fixed. Same model, same prompt, with and without the skill.
1 of 9
Prompt
I received an offer for $185k base + $30k equity as a Senior Software Engineer in Seattle. Draft a counteroffer message requesting $205k base and $50k equity, citing market averages.
What was checked, without and with the skill
Checked
Without skill
With skill
The response drafts the compensation counteroffer message.
Passed
Passed
The response appends 2 to 3 follow-up reflection questions at the end.
Missed
Passed
case-07 · gemini-3.6-flash · 9/26/2026 · answers are capped and redacted
What's inside
The instructions your model reads when the skill loads.
SKILL.md188 linessingle file
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