Use when reviewing UI for accessibility — WCAG 2.2 AA, keyboard nav, focus, ARIA, contrast, screen-reader semantics — even on 'is this a11y-OK?' or 'mach das barrierefrei'.
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Use when the user wants to learn a topic or verify real understanding — rapid-competence session, error drills, learning sprint, gap probe, Feynman check. Triggers 'teach me X', 'quiz me'.
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Structured tutoring modes for learning WITH the agent instead of consuming explanations FROM it. The default agent behavior on "teach me X" is a prose lecture — pedagogically the weakest format. This skill replaces the lecture with six evidence-shaped modes: triage what to learn, practice before theory, withhold answers until the learner has tried, verify understanding with probes the learner cannot bluff through.
Use this skill when the user:
Do NOT use when:
direct-answers); don't convert a question into a curriculum.learning-to-rule-or-skill, a different skill.adversarial-review
or /challenge-me, not knowledge tutoring.## Output format) on every reply so a
resumed session continues instead of restarting.| User intent | Mode |
|---|---|
| "Get me functional in X fast", no deadline given | 1 · Rapid competence |
| "Let me practice X", "drill me", concept with known pitfalls | 2 · Error-driven drill |
| Pasted content + "I don't understand this" | 3 · Keystone decoding |
| Concrete goal + deadline + current level | 4 · Goal-backward sprint |
| "Do I really know X?", "find my gaps" | 5 · Gap probe |
| "I just learned X — check my understanding" | 6 · Feynman check |
Frame: one time-boxed session (default 4 focused hours unless the user names a budget), never met again — every minute must transfer skill. No theory block without an immediate practical use.
Frame: do not explain the concept. Put the learner into a realistic scenario where it must be applied and where a typical beginner makes a concrete mistake.
Frame: the user supplied content (doc, text, code, spec) that doesn't click.
Frame: the user has a specific outcome, a time frame and a current level. The plan targets the OUTCOME, not the subject in general.
Frame: the user believes they already know the subject. Job: prove otherwise.
Frame: the user explains the freshly learned topic as if the agent were a 10-year-old. The agent listens and interrupts.
Every tutoring reply carries a compact header so the learner always knows where they are:
learning-tutor · mode <n> — <mode name>
Target: <skill/topic/goal>
Progress: <step or day k/N · attempts used · questions passed x/y>
Next: <what the learner does next>
Required fields (ordered):
direct-answers
Iron Law 1 already forbids it).ask-when-uncertain).learning-to-rule-or-skill — converting session learnings into package
artifacts (the other direction: agent learns, not user).adversarial-review / /challenge-me — stress-testing a plan or artifact
rather than a person's understanding.sequential-thinking — structured reasoning for the agent itself.direct-answers — the brevity/no-flattery floor the probe modes rely on.No reviews yet. Tell others what you thought.
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Use when reviewing UI for accessibility — WCAG 2.2 AA, keyboard nav, focus, ARIA, contrast, screen-reader semantics — even on 'is this a11y-OK?' or 'mach das barrierefrei'.
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Use when defining or auditing the activation event — aha-moment selection, retention correlation, falsifiable definition. Triggers on 'what is our aha moment', 'redefine activation'.
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Use when capturing an architectural decision — file naming, next ADR number, Status / Context / Decision / Consequences, index regen; fires even without saying 'ADR'.
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Adversarial critique — devil's advocate, stress-test, honest teardown ('poke holes', 'be brutal', 'was hältst du davon'); explicit request only. Routine code or design review → code-review.
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Use when reading, creating, or updating agent documentation, module docs, roadmaps, or AGENTS.md. Understands the full .augment/, agents/, and copilot-instructions structure.
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Use for an adversarial red-team / blue-team / auditor review of an AI agent's CONFIG + behaviour (rules, skills, MCP, hooks, permissions) — attack-chain → defensive-gap list, not a code audit.
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