@-Mention System

Mysti's @-mention system lets you reference files and route tasks to specific AI agents directly from the chat input.

File Mentions

Use @filename to add a file as transient context for your current message.

How It Works

@utils.ts Can you explain what the helper functions do?

• Mysti resolves the filename to a file in your workspace
• The file content is added as transient context (only for this message, not persisted)
• The AI receives the file content alongside your question

Examples

@package.json What version are we on?
@src/auth.ts Is there a security vulnerability in the login flow?
@styles.css @layout.css Can you unify these two stylesheets?

You can mention multiple files in a single message.

Agent Mentions

Use @agent-name to route tasks to specific AI providers.

Available Agents

Mention	Routes to
@claude	Claude Code
@codex	OpenAI Codex
@gemini	Google Gemini
@cline	Cline
@copilot	GitHub Copilot
@cursor	Cursor
@openclaw	OpenClaw

How It Works

When you mention an agent, Mysti:

1. Parses the message for all @-mentions
2. Generates a task list — determines what each mentioned agent should do
3. Executes tasks sequentially — each agent runs its task in order
4. Builds context — prior agent responses are provided as context to later agents
5. Returns results — all sub-agent responses are combined into the final response

Examples

Ask a specific agent

@gemini What's the fastest way to parse this JSON in Python?

Routes the question directly to Gemini, regardless of your default provider.

Multi-agent collaboration

@claude Write a sorting algorithm, then @codex optimize it for performance

1. Claude writes the initial algorithm
2. Codex receives Claude's response as context and optimizes it

Switch providers

Switch to @cursor

Changes your active provider to Cursor.

Task Generation

Mysti uses a smart task generation system to determine what each agent should do.

Heuristic Mode (Fast)

For common patterns, Mysti uses heuristics:

• Switch patterns: "switch to @agent" → changes the active provider
• Informational questions: Direct question → routes to the mentioned agent
• Directive verbs: "write", "fix", "refactor" → creates an execution task

AI Fallback

For complex messages with multiple agents and ambiguous intent, Mysti falls back to AI-powered task generation that analyzes the full message context.

Execution Details

Sequential Processing

Sub-agent tasks run in order, not in parallel. This allows:

• Later agents to see earlier agents' responses
• Dependency chains (e.g., "write with @claude, then review with @gemini")
• Consistent, predictable behavior

Error Handling

• Auto-retry: Failed tasks retry once automatically
• Timeout: Each sub-agent task has a 2-minute timeout
• Partial results: If one agent fails, others continue with available context
• Error reporting: Failures are reported in the response without halting the pipeline

Streaming

During execution, the chat shows real-time progress:

• Which agent is currently working
• Task list with completion status
• Streaming text from the active agent
• Tool use notifications

Combining Mentions

You can combine file and agent mentions:

@src/api.ts @claude Review this API for security issues, then @gemini suggest performance improvements

This:

1. Adds src/api.ts as context
2. Routes the security review to Claude
3. Passes Claude's review to Gemini for performance suggestions

Tips

1. Use file mentions instead of manually adding context — they're faster and don't persist
2. Chain agents for multi-perspective reviews
3. Switch providers quickly with "switch to @agent"
4. Be specific about what each agent should do for best results
5. Order matters — later agents receive earlier agents' responses as context