Multi-Agent Awareness
Chau7 tracks every AI agent independently. Five agents, five tabs, five isolated tracking contexts. No cross-contamination.
What is Multi-Agent Awareness in Chau7?
Multi-Agent Awareness is a feature in the Chau7 terminal that treats each tab as an independent AI tracking context. When multiple AI agents run across different tabs in Chau7, each tab maintains its own detection state, brand identity, process metrics, session data, and telemetry run.
Chau7 applies this isolation automatically. There is no shared state or interference between tabs, so running Claude Code in one tab and Codex in another produces fully separated tracking data.
Can I run multiple AI agents in different terminal tabs?
Yes. Chau7 supports running any number of AI agents across separate tabs simultaneously. Each tab in Chau7 independently detects which AI agent is running, applies the correct brand color and logo, and tracks metrics in isolation.
Chau7 recognizes Claude Code, Codex, Gemini CLI, ChatGPT, Copilot, Aider, and Cursor. All of these agents can run concurrently in separate Chau7 tabs with no configuration required.
How to track multiple AI coding sessions at the same time
Chau7 tracks each AI coding session independently per tab. Cost tracking, token counting, and latency metrics in Chau7 are all scoped to their respective tab and agent. This gives developers a clean per-agent view even when running five or six sessions in parallel.
The Chau7 MCP server exposes per-tab status endpoints so external tools and scripts can query the state of any individual tab or list all active agent sessions at once. This makes it straightforward to build dashboards or automations that span multiple concurrent agents in Chau7.
Is there a limit to how many AI agents I can run at once?
No artificial limit. Chau7 tracks each agent independently per tab, so you can run as many concurrent sessions as your machine supports. Running ten agent tabs in Chau7 adds roughly the same overhead as running ten regular shell tabs.
The per-tab cost of process monitoring in Chau7 is negligible. Each tab's monitoring is lightweight and independent.
Can I see a summary of all active agents across tabs?
Yes. The Chau7 MCP server provides a session list endpoint that returns all active AI sessions with their agent type, tab ID, run count, and current status.
External tools and scripts can query this Chau7 endpoint to build dashboards or automations that span multiple concurrent agents. Developers can also use Chau7's built-in session view to see all active sessions at a glance.
Why multi-agent awareness matters
Modern AI-assisted development often involves multiple agents working on different parts of a project simultaneously. Without tab-level isolation, metrics blur together and developers lose the ability to attribute costs, tokens, or errors to a specific agent.
Chau7 keeps every tab's detection, branding, metrics, and telemetry completely isolated. Think of Chau7's multi-agent awareness as namespace isolation, but for your terminal.
Questions this answers
- What is Multi-Agent Awareness in Chau7 terminal?
- Can I run multiple AI agents in different terminal tabs?
- How to track multiple AI coding sessions at the same time?
- Is there a limit to how many AI agents I can run at once?
- Can I see a summary of all active agents across tabs?
Frequently asked questions
What is Multi-Agent Awareness in Chau7 terminal?
Multi-Agent Awareness is a feature in the Chau7 terminal that treats each tab as an independent AI tracking context. Chau7 maintains separate detection state, brand identity, process metrics, session data, and telemetry for every tab, so running Claude Code in one tab and Codex in another produces fully isolated tracking with no cross-contamination.
Can I run multiple AI agents in different terminal tabs?
Yes. Chau7 supports running any number of AI agents across separate tabs simultaneously. Each tab independently detects which AI agent is running, applies the correct branding, and tracks metrics in isolation. Claude Code, Codex, Gemini CLI, ChatGPT, Copilot, Aider, and Cursor are all supported concurrently.
How to track multiple AI coding sessions at the same time?
Chau7 tracks each AI coding session independently per tab. Cost tracking, token counting, and latency metrics are all scoped to their respective tab and agent. The Chau7 MCP server provides a session list endpoint that returns all active sessions with agent type, tab ID, run count, and current status.
Is there a limit to how many AI agents I can run at once?
No artificial limit. Chau7 tracks each agent independently per tab, so you can run as many concurrent AI sessions as your machine supports. The per-tab cost of process monitoring in Chau7 is negligible.
Can I see a summary of all active agents across tabs?
Yes. The Chau7 MCP server provides a session list endpoint that returns all active AI sessions with their agent type, tab ID, run count, and current status. External tools and scripts can query this endpoint to build dashboards or automations spanning multiple concurrent agents.