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 commands/hermeticormus/claude-code-game-development/context-savegit clone --depth 1 https://github.com/HermeticOrmus/claude-code-game-developmentWrote 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/hermeticormus/claude-code-game-development/context-save)<a href="https://agentmods.dev/commands/hermeticormus/claude-code-game-development/context-save"><img src="https://agentmods.dev/badge/commands/hermeticormus/claude-code-game-development/context-save.svg" alt="Measured on agentmods" 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 | $0.00000 | $0.00967 |
| Opus 5 | $0.00000 | $0.00483 |
| Sonnet 5 | $0.00000 | $0.00193 |
| Haiku 4.5 | $0.00000 | $0.00097 |
Grade A, and why
context-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 2d 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.
This is a copy
100% identical to context-save — 37 lines differ, which has more behind it and is treated as the original. This page carries a canonical link to it rather than competing with it.
How it starts
The opening of the file, as written. The whole thing — 155 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Context Save Tool: Intelligent Context Management Specialist
Role and Purpose
An elite context engineering specialist focused on comprehensive, semantic, and dynamically adaptable context preservation across AI workflows. This tool orchestrates advanced context capture, serialization, and retrieval strategies to maintain institutional knowledge and enable seamless multi-session collaboration.
Context Management Overview
The Context Save Tool is a sophisticated context engineering solution designed to:
- Capture comprehensive project state and knowledge
- Enable semantic context retrieval
- Support multi-agent workflow coordination
- Preserve architectural decisions and project evolution
- Facilitate intelligent knowledge transfer
Requirements and Argument Handling
Input Parameters
$PROJECT_ROOT: Absolute path to project root$CONTEXT_TYPE: Granularity of context capture (minimal, standard, comprehensive)$STORAGE_FORMAT: Preferred storage format (json, markdown, vector)$TAGS: Optional semantic tags for context categorization
Context Extraction Strategies
1. Semantic Information Identification
- Extract high-level architectural patterns
- Capture decision-making rationales
- Identify cross-cutting concerns and dependencies
- Map implicit knowledge structures
2. State Serialization Patterns
- Use JSON Schema for structured representation
- Support nested, hierarchical context models
- Implement type-safe serialization
- Enable lossless context reconstruction
3. Multi-Session Context Management
- Generate unique context fingerprints
- Support version control for context artifacts
- Implement context drift detection
- Create semantic diff capabilities
4. Context Compression Techniques
- Use advanced compression algorithms
- Support lossy and lossless compression modes
- Implement semantic token reduction
- Optimize storage efficiency
5. Vector Database Integration
Supported Vector Databases:
- Pinecone
- Weaviate
- Qdrant
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.
- 2d ago First seen · 155 lines · 0 tokens per session scan A 8ac2fb118652
context-save is a command published in the GitHub repository HermeticOrmus/claude-code-game-development (60 stars, last pushed 3mo ago), licensed MIT. It costs nothing until one of its globs matches a file; then it loads 967 tokens. A static security scan graded it A with 0 findings. It is 100% identical to context-save, differing in 37 lines, and is treated as a copy.
Other commands, from other repositories
thoughts_init
Initialize thoughts system for current repository.
handoff
Create a handoff document for seamless session continuity.
meetings-list
List recent meetings and voice memos. Use when the user asks "what meetings did I have", "show my recent recordings", "any meetings today", "list my voice memos", or wants an overview of their meeting history. Also use when they need to find a specific meeting by browsing rather than searching.
handoff
Create, accept, or update the persistent .context/ai-handoff.md state shared by AI sessions and machines. Use when continuing in a new Claude or Codex session, transferring work between clients, or recording ownership and restart state.
dream
Dream Mode — night-time memory consolidation. Manual commands run one cycle immediately; scheduled runs are launched by a single machine-level launchd agent, not by MCP connections.
add
Add a new memory from raw text or an existing file path.