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/commands/superclaude-org/superclaude_framework/save)<a href="https://agentmods.dev/commands/superclaude-org/superclaude_framework/save"><img src="https://agentmods.dev/badge/commands/superclaude-org/superclaude_framework/save/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/commands/superclaude-org/superclaude_framework/save"><img src="https://agentmods.dev/badge/commands/superclaude-org/superclaude_framework/save.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 | $0.00013 | $0.00688 |
| Opus 5.5 | $0.00005 | $0.00275 |
| Sonnet 5.5 | $0.00003 | $0.00138 |
| Haiku 4.5 | $0.00001 | $0.00069 |
Grade A, and why
save 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
1 near-identical copy found in the catalogue:
- save — 100% identical, 12 lines differ
How it starts
The opening of the file, as written. The whole thing — 93 lines — stays where its author put it; the contents beside it link to each section on GitHub.
/sc:save - Session Context Persistence
Triggers
- Session completion and project context persistence needs
- Cross-session memory management and checkpoint creation requests
- Project understanding preservation and discovery archival scenarios
- Session lifecycle management and progress tracking requirements
Usage
/sc:save [--type session|learnings|context|all] [--summarize] [--checkpoint]
Behavioral Flow
- Analyze: Examine session progress and identify discoveries worth preserving
- Persist: Save session context and learnings using Serena MCP memory management
- Checkpoint: Create recovery points for complex sessions and progress tracking
- Validate: Ensure session data integrity and cross-session compatibility
- Prepare: Ready session context for seamless continuation in future sessions
Key behaviors:
- Serena MCP integration for memory management and cross-session persistence
- Automatic checkpoint creation based on session progress and critical tasks
- Session context preservation with comprehensive discovery and pattern archival
- Cross-session learning with accumulated project insights and technical decisions
MCP Integration
- Serena MCP: Mandatory integration for session management, memory operations, and cross-session persistence
- Memory Operations: Session context storage, checkpoint creation, and discovery archival
- Performance Critical: <200ms for memory operations, <1s for checkpoint creation
Tool Coordination
- write_memory/read_memory: Core session context persistence and retrieval
- think_about_collected_information: Session analysis and discovery identification
- summarize_changes: Session summary generation and progress documentation
- TodoRead: Task completion tracking for automatic checkpoint triggers
Key Patterns
- Session Preservation: Discovery analysis → memory persistence → checkpoint creation
- Cross-Session Learning: Context accumulation → pattern archival → enhanced project understanding
- Progress Tracking: Task completion → automatic checkpoints → session continuity
- Recovery Planning: State preservation → checkpoint validation → restoration readiness
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 · 93 lines · 13 tokens per session scan A 15a5e9b6e11b
save is a command published in the GitHub repository SuperClaude-Org/SuperClaude_Framework (23,905 stars, last pushed 20d ago), licensed MIT. It adds 13 tokens to every session and 688 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 commands, from other repositories
INFO
A startup routine for giving a coding agent the context it needs at the beginning of a terminal session. It checks platform, project, and current-task information from a fixed set of files and records a short summary.
mpm-session-resume
Load context from paused session.
load
Session lifecycle management with Serena MCP integration for project context loading.
save
Session lifecycle management with Serena MCP integration for session context persistence.
mcp-proxy-start-session
Start a new context tracking session for this conversation.
load
Session lifecycle management with Serena MCP integration for project context loading.