agent-communication
The agent-communication skill enables inter-agent coordination within the ai-devkit ecosystem by discovering active agents, retrieving their recent context, and sending or receiving messages. Use this when a Claude Code instance or other AI agent needs to locate collaborating agents, share information bidirectionally, or coordinate tasks across a distributed agent network.
git clone --depth 1 https://github.com/codeaholicguy/ai-devkit /tmp/agent-communication && cp -r /tmp/agent-communication/skills/agent-communication ~/.claude/skills/agent-communicationSKILL.md
# Agent Communication Use `ai-devkit agent ...` to discover and communicate with active agents. If `ai-devkit` is not on PATH, use `npx ai-devkit@latest agent ...`. ## Commands ```bash ai-devkit agent list --json ai-devkit agent detail --id <agent-name> --json --tail 20 ai-devkit agent send --id <agent-name> "<message>" ai-devkit agent send --id <agent-name> --wait --timeout 120000 --json "<message>" <command> 2>&1 | ai-devkit agent send --id <agent-name> --stdin ``` ## Notes - `list --json` returns active agents with fields such as `name`, `type`, `status`, `summary`, `projectPath`, and `lastActive`. - Use the `name` from `list --json` as `--id`. Partial matches are supported, but exact names are safer. - Use `detail --json --tail <n>` to read recent context from an agent before deciding what to send. - `send --wait` waits for a reply; add `--json` when the response should be machine-readable. - `send --stdin` forwards piped command output or larger text.
AI DevKit · Compare implementation with design and requirements docs to ensure alignment.
AI DevKit · Pre-push code review against design docs.
AI DevKit · Execute a feature plan task by task.
AI DevKit · Scaffold feature documentation from requirements through planning.
AI DevKit · Store reusable guidance in the knowledge memory service.
AI DevKit · Review feature design for completeness.
AI DevKit · Review feature requirements for completeness.
AI DevKit · Update planning docs to reflect implementation progress.