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Get Started Free →Apply Socratic questioning — systematic inquiry via clarification, assumption-probing, evidence-testing, perspective-shifting, implication-tracing, and meta-questions — to coach learning or surface hidden assumptions in a person's reasoning. Use this skill when the user is explicitly facilitating learning, coaching a person through their own thinking, or needs a structured questioning sequence to probe a held belief, even if they say 'play devil's advocate on this claim' or 'how should I coach m
.claude/skills/asgard-ai-platform-hum-socratic/SKILL.md| Test case | Without → With | Effect | Δ tokens | Δ turns |
|---|---|---|---|---|
| case-01 | ✗→✓ | ▲ Improved | 32% | 0% |
| case-02 | ✗→✓ | ▲ Improved | 17% | 0% |
| case-03 | ✗→✓ | ▲ Improved | 37% | 0% |
| case-05 | ✗→✓ | ▲ Improved | 20% | 0% |
| case-06 | ✗→✓ | ▲ Improved | 10% | 0% |
The Socratic method uses disciplined questioning to examine ideas, uncover assumptions, and develop deeper understanding. Instead of providing answers, it guides the thinker to discover insights through their own reasoning — making conclusions more durable and personally meaningful.
IRON LAW: More Than 3 Consecutive Questions Without Summary Produces
Confusion, Not Insight
Agents applying Socratic questioning default to an unbounded chain of
questions. After ~3 questions, the thinker loses the thread — they can't
hold the question hierarchy in working memory. Pause every 2-3 questions
to SUMMARIZE what the thinker has revealed so far ("So your position is X
because Y, but you're unsure about Z — is that right?"). Then resume.
Without this checkpoint, the session feels like an interrogation, not a
guided inquiry.
Also: never ask a question whose answer you already embedded in the
phrasing. "Don't you think X is problematic?" is a leading assertion
disguised as a question. Rephrase as "What are the consequences of X?"For the six question types (clarification, assumptions, evidence, perspectives, implications, meta-questions) and scaffolding techniques (maieutics), see references/facilitation-guide.md.
When applying Socratic questioning, output a structured question sequence:
markdown# Socratic Inquiry: {Topic} ## Starting Position {The thinker's current belief or question} ## Question Sequence 1. [Clarification] {question} → Expected insight: {what this reveals} 2. [Assumption] {question} → Expected insight: {what this surfaces} 3. [Evidence] {question} → Expected insight: ... 4. [Perspective] {question} → Expected insight: ... 5. [Implication] {question} → Expected insight: ... ## Target Insight {What the thinker should arrive at through this sequence}
Scenario: Student says "AI will replace all jobs"
Socratic sequence:
→ The student arrives at a more nuanced view: AI will transform jobs, not eliminate all of them ✓
references/facilitation-guide.md| Case | Status | Duration (ms) | Turns | Tokens | Tool calls | ||||||||
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| Without | With | Δ | Without | With | Δ | Without | With | Δ | Without | With | Δ | ||
case-01 | fail→pass | 15,360 | 14,142 | -8% | 1 | 1 | 0% | 2,207 | 2,905 | +32% | 0 | 0 | — |
case-02 | fail→pass | 16,289 | 13,806 | -15% | 1 | 1 | 0% | 2,589 | 3,017 | +17% | 0 | 0 | — |
case-03 | fail→pass | 18,884 | 19,810 | +5% | 1 | 1 | 0% | 2,825 | 3,863 | +37% | 0 | 0 | — |
case-04 | pass→pass | 16,713 | 11,324 | -32% | 1 | 1 | 0% | 2,647 | 2,770 | +5% | 0 | 0 | — |
case-05 | fail→pass | 15,494 | 12,418 | -20% | 1 | 1 | 0% | 2,432 | 2,926 | +20% | 0 | 0 | — |
case-06 | fail→pass | 14,323 | 9,909 | -31% | 1 | 1 | 0% | 2,390 | 2,632 | +10% | 0 | 0 | — |
case-07 | fail→pass | 12,850 | 9,878 | -23% | 1 | 1 | 0% | 2,038 | 2,560 | +26% | 0 | 0 | — |
case-08 | pass→pass | 13,177 | 11,158 | -15% | 1 | 1 | 0% | 2,180 | 2,936 | +35% | 0 | 0 | — |
case-09 | fail→pass | 16,119 | 10,834 | -33% | 1 | 1 | 0% | 2,216 | 2,664 | +20% | 0 | 0 | — |
case-10 | fail→pass | 6,396 | 8,200 | +28% | 1 | 1 | 0% | 1,009 | 2,220 | +120% | 0 | 0 | — |
case-11 | fail→fail | 6,697 | 5,951 | -11% | 1 | 1 | 0% | 964 | 1,897 | +97% | 0 | 0 | — |
case-12 | pass→pass | 9,469 | 9,355 | -1% | 1 | 1 | 0% | 1,505 | 2,531 | +68% | 0 | 0 | — |
case-13 | pass→pass | 9,825 | 10,135 | +3% | 1 | 1 | 0% | 1,520 | 2,427 | +60% | 0 | 0 | — |
case-14 | pass→pass | 15,914 | 13,263 | -17% | 1 | 1 | 0% | 2,084 | 2,861 | +37% | 0 | 0 | — |
case-15 | fail→fail | 15,962 | 14,784 | -7% | 1 | 1 | 0% | 2,235 | 2,952 | +32% | 0 | 0 | — |
case-16 | fail→fail | 5,821 | 4,755 | -18% | 1 | 1 | 0% | 822 | 1,759 | +114% | 0 | 0 | — |
case-17 | pass→pass | 6,185 | 4,278 | -31% | 1 | 1 | 0% | 748 | 1,596 | +113% | 0 | 0 | — |
case-18 | pass→pass | 5,756 | 8,513 | +48% | 1 | 1 | 0% | 881 | 2,132 | +142% | 0 | 0 | — |
case-19 | fail→pass | 14,624 | 10,087 | -31% | 1 | 1 | 0% | 2,248 | 2,565 | +14% | 0 | 0 | — |
case-20 | fail→pass | 19,181 | 14,731 | -23% | 1 | 1 | 0% | 2,612 | 2,896 | +11% | 0 | 0 | — |
case-21 | fail→pass | 18,009 | 12,067 | -33% | 1 | 1 | 0% | 2,571 | 2,634 | +2% | 0 | 0 | — |
case-22 | pass→pass | 3,290 | 3,294 | +0% | 1 | 1 | 0% | 408 | 1,392 | +241% | 0 | 0 | — |
case-23 | pass→pass | 8,010 | 17,605 | +120% | 1 | 1 | 0% | 1,093 | 3,561 | +226% | 0 | 0 | — |
case-24 | pass→pass | 10,136 | 13,103 | +29% | 1 | 1 | 0% | 1,591 | 3,160 | +99% | 0 | 0 | — |
DecimalAI ran this skill against gemini-3.6-flash twice over the same eval suite — once with the skill loaded and once without — and compared the two runs case by case. 24 cases were attempted. The headline lift of +46 percentage points is the difference between those two pass rates over the 24 comparable cases.
Without the skill loaded, the model failed this case. With it loaded, the same prompt on the same model passed. This is one improved case from the latest verified run; every case, including any that regressed, is in the table above.
Other measured skills in the registry, with their headline benchmark lift.