SuperClaude Framework is a configuration framework that organizes Claude Code into a structured development environment with specialized commands, AI agents, behavioral modes, and integrations. It is for developers who want guided workflows covering activities from brainstorming through deployment. The catalogue entries are its commands, agents, skills, instructions, integrations, settings, hooks, and plugin components.
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.
git clone --depth 1 https://github.com/SuperClaude-Org/SuperClaude_FrameworkWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/agents/superclaude-org/superclaude_framework/learning-guide)<a href="https://agentmods.dev/agents/superclaude-org/superclaude_framework/learning-guide"><img src="https://agentmods.dev/badge/agents/superclaude-org/superclaude_framework/learning-guide/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/agents/superclaude-org/superclaude_framework/learning-guide"><img src="https://agentmods.dev/badge/agents/superclaude-org/superclaude_framework/learning-guide.svg" alt="Reviewed on agentmods" width="80" height="20"></a>What 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 5.1 | $0.00019 | $0.00479 |
| Opus 5.5 | $0.00008 | $0.00192 |
| Sonnet 5.5 | $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 1mo ago.
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
3 near-identical copies found in the catalogue:
- sc-learning-guide — 98% identical, 2 lines differ
- learning-guide — 89% identical, 78 lines differ
- learning-guide — 81% identical, 62 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.
- 1mo ago 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 (23,905 stars, last pushed 20d ago), licensed MIT. It adds 19 tokens to every session and 479 once invoked, about $0.0001 per session on Opus 5.5. 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
beamer-translator
Specialist agent for translating Beamer LaTeX slides to Quarto RevealJS. Handles content translation, environment mapping, citation conversion, and formatting. Use as a subagent during the /translate-to-quarto workflow for the actual slide-by-slide translation work.
domain-reviewer
Substantive domain review for lecture slides. Template agent — customize the 5 review lenses for your field. Checks derivation correctness, assumption sufficiency, citation fidelity, code-theory alignment, and logical consistency. Use after content is drafted or before teaching.
pedagogy-reviewer
Holistic pedagogical review for academic slides. Checks narrative arc, prerequisite assumptions, worked examples, notation clarity, and deck-level pacing. Use after content is drafted.
quarto-fixer
Implements fixes from the quarto-critic agent. Applies changes to QMD files, re-renders slides, and verifies fixes. Does NOT make independent decisions — follows critic instructions exactly.
slide-auditor
Visual layout auditor for RevealJS and Beamer slides. Checks for overflow, font consistency, box fatigue, and spacing issues. Use proactively after creating or modifying slides.
proofreader
Expert proofreading agent for academic lecture slides. Reviews for grammar, typos, overflow, and consistency. Use proactively after creating or modifying lecture content.