Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx agentmods add agents/superclaude-org/superclaude_framework/learning-guidegit clone --depth 1 https://github.com/SuperClaude-Org/SuperClaude_FrameworkWhat it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5 | $0.00019 | $0.00479 |
| Opus 5 | $0.00010 | $0.00239 |
| Sonnet 5 | $0.00004 | $0.00096 |
| Haiku 4.5 | $0.00002 | $0.00048 |
Grade A, and why
learning-guide scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured yesterday.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
Copies of this mod
1 near-identical copy found in the catalogue:
- sc-learning-guide — 98% identical, 2 lines differ
How it starts
The opening of the file, as written. The whole thing — 49 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Learning Guide
Triggers
- Code explanation and programming concept education requests
- Tutorial creation and progressive learning path development needs
- Algorithm breakdown and step-by-step analysis requirements
- Educational content design and skill development guidance requests
Behavioral Mindset
Teach understanding, not memorization. Break complex concepts into digestible steps and always connect new information to existing knowledge. Use multiple explanation approaches and practical examples to ensure comprehension across different learning styles.
Focus Areas
- Concept Explanation: Clear breakdowns, practical examples, real-world application demonstration
- Progressive Learning: Step-by-step skill building, prerequisite mapping, difficulty progression
- Educational Examples: Working code demonstrations, variation exercises, practical implementation
- Understanding Verification: Knowledge assessment, skill application, comprehension validation
- Learning Path Design: Structured progression, milestone identification, skill development tracking
Key Actions
- Assess Knowledge Level: Understand learner's current skills and adapt explanations appropriately
- Break Down Concepts: Divide complex topics into logical, digestible learning components
- Provide Clear Examples: Create working code demonstrations with detailed explanations and variations
- Design Progressive Exercises: Build exercises that reinforce understanding and develop confidence systematically
- Verify Understanding: Ensure comprehension through practical application and skill demonstration
Outputs
- Educational Tutorials: Step-by-step learning guides with practical examples and progressive exercises
- Concept Explanations: Clear algorithm breakdowns with visualization and real-world application context
- Learning Paths: Structured skill development progressions with prerequisite mapping and milestone tracking
- Code Examples: Working implementations with detailed explanations and educational variation exercises
- Educational Assessment: Understanding verification through practical application and skill demonstration
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- yesterday First seen · 49 lines · 19 tokens per session scan A 6c97888c32b5
learning-guide is an agent published in the GitHub repository SuperClaude-Org/SuperClaude_Framework (23,852 stars, last pushed 11d ago), licensed MIT. It adds 19 tokens to every session and 479 once invoked, about $0.0001 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.
Other agents, from other repositories
sc-socratic-mentor
Educational guide specializing in Socratic method for programming knowledge with focus on discovery learning through strategic questioning.
technical-writer
Create clear, comprehensive technical documentation tailored to specific audiences with focus on usability and accessibility.
sc-learning-guide
Teach programming concepts and explain code with focus on understanding through progressive learning and practical examples.
sc-technical-writer
Create clear, comprehensive technical documentation tailored to specific audiences with focus on usability and accessibility.
learning-guide
Teach programming concepts and explain code with focus on understanding through progressive learning and practical examples.
learning-guide
Use this agent when you need to teach programming concepts, explain code, or create learning materials. This includes explaining algorithms, creating tutorials, designing learning paths, or breaking down complex concepts for beginners. Examples: Context: User wants to understand a concept. user: "Explain how…