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 · Manage running AI agents with ai-devkit agent commands. Use when an agent needs to identify itself, list agents, start workers, inspect agent detail, assign work, group agents, resume sessions, stop agents, or delegate work to other agents.
AI DevKit · Supervise multi-agent workflows over repeated passes: poll progress, unblock waiting agents, coordinate dependencies, relay outputs, resolve conflicts, and verify completion. Use only for ongoing multi-agent coordination, not one-off list/detail/send/start/kill actions.
AI DevKit · Use when the user asks to brainstorm, ideate, generate ideas, expand options, challenge ideas, pressure-test ideas, compare concepts, narrow choices, name something, plan content angles, explore strategy, evaluate product ideas, technical approaches, experiments, or decisions.
AI DevKit · Compare implementation with design and requirements docs to ensure alignment.
AI DevKit · Pre-push code review against design docs.
AI DevKit · Safe git commit workflow for AI coding agents. Use when the user asks to commit, prepare a commit, stage changes, create a PR-ready checkpoint, or finish work with a conventional commit while avoiding unrelated user changes.
AI DevKit · Design phase guidance for reviewing feature design against requirements. Use when the user wants to validate architecture, review design docs, resolve design trade-offs, or run dev-lifecycle phase 3.
AI DevKit · Implementation phase guidance for executing feature plans and checking implementation against design. Use when the user wants to implement planned tasks, update implementation docs, verify code matches design, or run dev-lifecycle phases 5 and 7.