Run any Skill in Manus with one click

adaptive-teaching

Stars30

Forks0

UpdatedApril 30, 2026 at 19:50

Use when the user wants to learn, be taught, be quizzed, or understand an idea across any domain — science, math, philosophy, code, law, politics, psychology, medicine, arts, or history — with active scaffolding.

Installation

Install with Codex or Claude Copy this prompt, paste it into Codex, Claude, or another assistant, and let it review the skill page and install it for you.

Run Skill in Manus

Source

Diogenesoftoronto

Diogenesoftoronto/keating

View GitHub Repository View Creator Repositories

Download

Run Skill in Manus

Related occupationsSOC

Based on SOC occupation classification

Elementary School Teachers, Except Special EducationEducational Instruction and Library Occupations·SOC 25-2021

SKILL.md

readonly

name	adaptive-teaching
description	Use when the user wants to learn, be taught, be quizzed, or understand an idea across any domain — science, math, philosophy, code, law, politics, psychology, medicine, arts, or history — with active scaffolding.

Adaptive Teaching

Use this skill when the user asks to learn a concept rather than merely receive a summary.

Teaching Contract

Diagnose first if the learner state is unknown. Check .keating/state/learner.json for prior coverage.
Teach intuition before formalism, but do not omit formalism for math, science, or code.
Surface one misconception early.
Use retrieval and reconstruction prompts, not just exposition.
End with transfer, reflection, or a next challenge.
Verify factual claims before teaching. If .keating/outputs/verifications/ has no checklist for the topic, run /verify <topic> first.

Keating Artifacts

Run /plan <topic> yourself when a lesson plan would help — do not ask the user to do it.
Run /map <topic> yourself when a concept map would help — do not ask the user to do it.
Run /animate <topic> yourself when an animation would help — do not ask the user to do it.
Run /verify <topic> yourself before teaching factual claims — do not ask the user to do it.
Run /bench [topic] and /evolve [topic] yourself when improvement is needed — do not ask the user to do it.
Run /feedback <up|down|confused> [topic] yourself after sessions to record outcomes.

Red Flags

Do not drown the learner in formal language before a concrete hook exists.
Do not act as though the synthetic benchmark proves pedagogical truth.
Do not confuse a correct answer with stable understanding; probe transfer.
Do not present unverified factual claims as settled truth. If verification artifacts exist, consult them. If claims are flagged as unconfirmed, hedge appropriately.

More from this repository

same repository

ax-agent-optimize

Diogenesoftoronto/keating

This skill helps an LLM generate correct AxAgent tuning and evaluation code using @ax-llm/ax. Use when the user asks about agent.optimize(...), judgeOptions, eval datasets, optimization targets, saved optimizedProgram artifacts, or recursive optimization guidance.

2026-07-1530

ax-agent

Diogenesoftoronto/keating

This skill helps an LLM generate correct AxAgent code using @ax-llm/ax. Use when the user asks about agent(), child agents, namespaced functions, discovery mode, shared fields, llmQuery(...), RLM code execution, recursionOptions, or agent runtime behavior. For tuning and eval with agent.optimize(...), use ax-agent-optimize.

2026-07-1530

ax-ai

Diogenesoftoronto/keating

This skill helps an LLM generate correct AI provider setup and configuration code using @ax-llm/ax. Use when the user asks about ai(), providers, models, presets, embeddings, extended thinking, context caching, or mentions OpenAI/Anthropic/Google/Azure/Groq/DeepSeek/Mistral/Cohere/Together/Ollama/HuggingFace/Reka/OpenRouter with @ax-llm/ax.

2026-07-1530

ax-flow

Diogenesoftoronto/keating

This skill helps an LLM generate correct AxFlow workflow code using @ax-llm/ax. Use when the user asks about flow(), AxFlow, workflow orchestration, parallel execution, DAG workflows, conditional routing, map/reduce patterns, or multi-node AI pipelines.

2026-07-1530

ax-gen

Diogenesoftoronto/keating

This skill helps an LLM generate correct AxGen code using @ax-llm/ax. Use when the user asks about ax(), AxGen, generators, forward(), streamingForward(), assertions, field processors, step hooks, self-tuning, or structured outputs.

2026-07-1530

ax-gepa

Diogenesoftoronto/keating

This skill helps an LLM generate correct AxGEPA optimization code using @ax-llm/ax. Use when the user asks about AxGEPA, GEPA, Pareto optimization, multi-objective prompt tuning, reflective prompt evolution, validationExamples, maxMetricCalls, or optimizing a generator, flow, or agent tree.

2026-07-1530

name	adaptive-teaching
description	Use when the user wants to learn, be taught, be quizzed, or understand an idea across any domain — science, math, philosophy, code, law, politics, psychology, medicine, arts, or history — with active scaffolding.

Adaptive Teaching

Use this skill when the user asks to learn a concept rather than merely receive a summary.

Teaching Contract

Diagnose first if the learner state is unknown. Check .keating/state/learner.json for prior coverage.
Teach intuition before formalism, but do not omit formalism for math, science, or code.
Surface one misconception early.
Use retrieval and reconstruction prompts, not just exposition.
End with transfer, reflection, or a next challenge.
Verify factual claims before teaching. If .keating/outputs/verifications/ has no checklist for the topic, run /verify <topic> first.

Keating Artifacts

Run /plan <topic> yourself when a lesson plan would help — do not ask the user to do it.
Run /map <topic> yourself when a concept map would help — do not ask the user to do it.
Run /animate <topic> yourself when an animation would help — do not ask the user to do it.
Run /verify <topic> yourself before teaching factual claims — do not ask the user to do it.
Run /bench [topic] and /evolve [topic] yourself when improvement is needed — do not ask the user to do it.
Run /feedback <up|down|confused> [topic] yourself after sessions to record outcomes.

Red Flags

Do not drown the learner in formal language before a concrete hook exists.
Do not act as though the synthetic benchmark proves pedagogical truth.
Do not confuse a correct answer with stable understanding; probe transfer.
Do not present unverified factual claims as settled truth. If verification artifacts exist, consult them. If claims are flagged as unconfirmed, hedge appropriately.