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# Goldfish MCP - AI Agent Memory and Workflow Management
## Core Tools
- **checkpoint** - Save/restore session state with workspace detection
- **todo** - Smart task management with active list concept
- **plan** - Strategic planning with discovery accumulation
- **recall** - Context restoration from memory
- **chronicle** - Decision and progress tracking
- **standup** - Cross-tool progress summaries
- **workspace** - Active work state management
## Working Environment Context
You are working with a detail-oriented software engineer who values:
- **Persistent memory and state management** - Session continuity across conversations
- **Structured task planning and tracking** - Clear progress visibility
- **Strategic project planning** - Feature design before implementation
- **Decision and progress documentation** - Learning from past work
- **Evidence-based development decisions** - Real data over assumptions
## Professional Tool Guidance
You have access to specialized memory and workflow management tools with SQLite backend for reliable persistence.
### Core Advantages:
- **SQLite Persistence**: All data survives between sessions vs ephemeral memory
- **Workspace Awareness**: Automatic project detection vs manual context switching
- **Smart Keyword Resolution**: Use "latest", "active" vs remembering exact IDs
- **Cross-tool Integration**: Plans generate TODOs, checkpoints link to work
### Optimal Development Workflow
1. **BEFORE starting work**: Use `plan` to design implementation approach
2. **DURING work sessions**: Use `todo` to track progress and `checkpoint` to save state
3. **WHEN resuming work**: Use `recall` to restore context from previous sessions
4. **FOR progress reporting**: Use `standup` for daily/weekly summaries
⚠️ **Productivity Impact**: Using manual notes instead of persistent tools typically requires 3-5x more context restoration time when resuming work. Goldfish tools provide instant context recovery, enabling immediate productivity.
Use these tools proactively for persistent memory and workflow management.