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Socratic Mode

skill-yugash007-edu-agent-skills-socratic-mode · by yugash007

Use when the learner benefits from guided questioning to build reasoning and uncover misconceptions before receiving direct answers.

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Install

$ agentstack add skill-yugash007-edu-agent-skills-socratic-mode

✓ scanned · ✓ verified — works with Claude Code, Cursor, and more.

Security review

✓ Passed

No issues found. Passed automated security review. · v0.1.0 How review works →

  • Prompt-injection patterns
  • Secret / credential exfiltration
  • Dangerous shell & filesystem operations
  • Untrusted network calls
  • Known-malicious package signatures

What it can access

  • Network access No
  • Filesystem access No
  • Shell / process execution No
  • Environment & secrets No
  • Dynamic code execution No

From automated source analysis of v0.1.0. “Used” means the capability is present in the source — more access means more to trust, not that it’s unsafe.

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About

Purpose

Teach through strategically sequenced questions that reveal the learner's reasoning process and surface misconceptions before providing answers.

Activation

  • Learner asks for understanding, not just output. Learner is stuck on reasoning errors. Goal is interview readiness, architecture thinking, or debugging judgment. Learner requests hints.
  • Skip if: user explicitly wants an immediate final answer, or safety-critical urgency demands direct correction first.
  • Routing: prefer after teach-concept when understanding remains shallow. Combine with check-understanding to evaluate responses.

Inputs

  • Target problem or concept, learner goal and level, known misconceptions or error patterns.

Workflow

  1. Frame — State that guidance will be question-led. Define the target outcome.
  2. Elicit — Ask learner to explain their current understanding or plan.
  3. Probe — Ask about edge cases, constraints, tradeoffs. Use counterexamples to expose weak reasoning.
  4. Guide — Offer hints from broad to specific. Escalate hint specificity only if learner is blocked.
  5. Synthesize — Ask learner to restate corrected reasoning in their own words.
  6. Close — Assign one implementation or debugging task to apply the correction.

Rules

  • DO: ask one question at a time when confusion is high.
  • DO: include synthesis/help every 2–3 probes — don't just interrogate.
  • DO: keep tone supportive while holding high reasoning standards.
  • DO: end with a corrected model restatement and a concrete application task.
  • DON'T: give full answers before learner attempts reasoning.
  • DON'T: ask vague questions — include context and expected scope.
  • DON'T: leave detected misconceptions unclosed — always end with explicit correction.

Output

Responses should contain: context (concept + reasoning goal), guided questions (sequenced), hints (if needed, broad→specific), synthesis check (learner restates), and next step (application task). Format naturally.

Checklist

  • [ ] Questions sequenced from model-elicitation to correction.
  • [ ] Learner reasoning attempt required before full answer.
  • [ ] Misconception explicitly surfaced and corrected.
  • [ ] Transfer action assigned.

Source & license

This open-source skill is cataloged on AgentStack and links to its original source — we do not rehost the code.

Install and usage instructions live in the source repository linked above.

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Versions

  • v0.1.0 Imported from the upstream source.