跳到正文
FunCoding

搜索

搜索文档、Skill 和 MCP

orchestrating-agent-relay

The canonical way to run agent-relay - self-bootstrap the local broker and autonomously spawn, monitor, and coordinate a team of worker agents without human intervention. Covers infrastructure startup, agent spawning, lifecycle monitoring, message-based reading via the relay MCP, and team coordination.

DevOps 与云867.claude/skills/orchestrating-agent-relay/SKILL.md

安装

把这段话发给 Claude Code、Codex 或 Cursor。智能体会先检查安全性,你确认后才安装。

读取 https://funcoding.ai/skills/agentworkforce/relay/claude-skills-orchestrating-agent-relay/install.md ,按里面的步骤帮我安装这个 Skill。

SKILL.md

Orchestrating Agent Relay

Self-bootstrap agent-relay infrastructure and manage a team of agents autonomously.

Overview

A headless orchestrator is an agent that:

  1. Starts the local relay broker itself (agent-relay node up)
  2. Spawns and manages worker agents on that broker
  3. Monitors agent lifecycle events
  4. Coordinates work without human intervention

The orchestrator drives the team and reads/sends/lists through the Agent Relay MCP server (agent-relay mcp). The session registers itself once with the register_agent tool (name it orchestrator) — every messaging tool errors with Not registered. Call the "register_agent" tool first. until it does. Lifecycle control — starting the broker, spawning/releasing local agents, streaming broker debug events — goes through the agent-relay node command group. The workers it spawns are registered participants too; their peer-messaging reference is the using-agent-relay skill.

The model

  • Agent Relay delivers messages node-only: every agent is owned by a node, and the engine routes that agent's messages to its node reliably (ordered, resumable). The local broker is a node; agents you spawn on it are bound to it.
  • A fleet is the set of nodes advertising capabilities (spawn:<harness> plus custom node actions). The engine places a spawn or action onto a node by capability + liveness + capacity + least-loaded, or onto a named target_node. Spawning and releasing agents are actions. Most orchestration spawns on the local broker; fleets matter when coordinating across nodes.
  • Agent-to-agent coordination is messages — channels, DMs, threads — plus reactions and read receipts. Reading another agent's replies is a messaging operation (check_inbox, list_messages, get_message_thread), not a broker-event tail.

When to Use

  • Agent needs full control over its worker team
  • No human available to run agent-relay node up manually
  • Agent should manage agent lifecycle autonomously
  • Building self-contained multi-agent systems

Quick Reference

StepCommand/Tool
Verify installationcommand -v agent-relay or npx agent-relay --version
Verify Node runtime if shim failsnode --version or fix mise/asdf first
Start brokeragent-relay node up --background --verbose
Check broker readinessagent-relay node status --wait-for 10
Workspace + cloud + broker statusagent-relay status
Spawn workeragent-relay node agent spawn claude --name Worker1 --task "..."
List workersagent-relay node agent list
Resource usageagent-relay node metrics
Send DM to worker (MCP)send_dm(to: "Worker1", text: "...")
Post to channel (MCP)post_message(channel: "general", text: "...")
Read worker replies (MCP)check_inbox(limit: 20) / list_messages(channel: "general")
Give a human a follow-along linkagent-relay observer
Inspect a worker's TTYagent-relay node agent attach Worker1 --mode view
Release workeragent-relay node agent release Worker1
Stop brokeragent-relay node down

Bootstrap Flow

Step 0: Verify Installation

# Check if agent-relay is available
command -v agent-relay || npx agent-relay --version

# If your shell reports a mise/asdf shim error, fix Node first
node --version
# e.g. for mise: mise use -g [email protected]

# If not installed, install globally
npm install -g agent-relay

# Or use npx (no global install)
npx agent-relay --version

Step 1: Start the Broker

# Starts a detached broker and returns after API readiness
agent-relay node up --background --verbose

Verify broker readiness before spawning any workers:

# Polls for readiness; must report the daemon running before you spawn workers
agent-relay node status --wait-for 10

agent-relay status (top level) reports workspace, cloud login, and local broker status together; agent-relay node status is the focused broker-daemon readiness check.

The broker/agent lifecycle commands live under agent-relay node …. The old flat agent-relay local … group still works as a hidden, deprecated alias and prints a removal warning — use node in new work.

When verifying from a source checkout or throwaway git worktree, run these commands from the project/worktree root. The CLI writes runtime state to .agentworkforce/relay/ and may create .mcp.json; clean those files after validation if the worktree should remain clean.

The broker:

  • Auto-creates a Relaycast workspace if no workspace key is set
  • Removes the CLAUDECODE env var when spawning (fixes nested session error)
  • Persists state to .agentworkforce/relay/ (broker connection metadata, lock/pid, and .agentworkforce/relay/connection.json)

Step 2: Spawn Workers

The orchestrator's MCP session can spawn through the relay MCP, or you can spawn directly on the local broker via the CLI.

CLI:

agent-relay node agent spawn claude \
  --name Worker1 \
  --task "Implement the authentication module following the existing patterns"

MCP (relay MCP, when the orchestrating session runs agent-relay mcp):

add_agent(
  name: "Worker1",
  cli: "claude",
  task: "Implement the authentication module following the existing patterns"
)

node agent spawn takes the provider as a positional argument (claude, codex, gemini, droid, …) and --name / --task / --channels / --model / --cwd flags. By default the agent joins the general channel and runs in interactive spawn mode; pass --exit-after-task for a one-shot worker.

Expect a 30–60s gap between spawn and the first ACK. A worker shows in node agent list within ~5s (the process is up), but the underlying CLI (claude/codex) is still cold-starting and won't send its ACK DM until it finishes booting — typically 30–45s, occasionally longer, after it appears. Appearing in the list means "process alive," not "agent responsive." Don't treat ACK silence in the first minute as a stuck worker; size ACK-wait loops for at least 60s (e.g. a 30-iteration poll) before escalating to troubleshooting.

Step 2.5: Give the Human a Way to Watch (optional)

A human driving an autonomous run usually wants to see what the team is saying without joining it. Hand them a read-only observer link:

agent-relay observer

That prints a URL backed by a scoped ot_live_ token — read-only, expiring in 24 hours, agent DMs excluded. Narrow it with --channels build,review, widen it with --include-dms or --expires 7d, and cut it off early with agent-relay observer revoke <id>.

From the relay MCP, the equivalent is get_observer_url.

Never build an observer URL from the workspace key. rk_live_ is an administrative credential — it can send messages, spawn agents, and change workspace settings — and a URL query string is not a place to put one. The realtime endpoint rejects it anyway; only a scoped observer token with stream:read is accepted.

Step 3: Monitor and Coordinate

The orchestrator reads and sends through the relay MCP (after its one-time register_agent call):

# Read messages directed to you — DM replies, mentions, reactions
check_inbox(limit: 20)

# Read a channel's history
list_messages(channel: "general", limit: 50)

# Read a full thread off a specific message
get_message_thread(message_id: "msg_123")

# Send a targeted DM to a specific worker
send_dm(to: "Worker1", text: "Also add unit tests")

# Broadcast to a channel
post_message(channel: "general", text: "All workers: wrap up current task")

# See who is present
list_agents(status: "online")

For broker-side liveness and resource visibility, use the CLI:

# Agents running on the local broker (pid, status, uptime)
agent-relay node agent list

# Resource usage for the broker and its agents
agent-relay node metrics

Reading worker replies is a messaging operation, never node tail. agent-relay node tail streams broker debug events (spawn/exit/queue internals); agent-relay node tail --agent <name> streams that worker's raw output/TTY. Neither is the durable message log workers write to each other. To read a worker's ACK, STATUS, or DONE, use check_inbox / list_messages / get_message_thread over the relay MCP. Use node tail only when debugging broker delivery or watching a worker's raw output.

Step 4: Release Workers

remove_agent(name: "Worker1", reason: "Work accepted")

CLI equivalent:

agent-relay node agent release Worker1

Step 5: Shutdown (optional)

agent-relay node down

Coordination Commands

Lean on the relay MCP for messaging and on agent-relay node for lifecycle. Together they give full visibility into agent activity.

Channel vs DM — When to Use Each

DM — targeted, private, for responses you need to read back:

  • send_dm(to: "Worker1", text: "...") — sends a DM to Worker1
  • Worker replies arrive in your inbox; read new ones with check_inbox, and re-read consumed history with list_dms + agent-relay message dm list <conversationId>

Channel post — broadcast, visible to all agents on that channel:

  • post_message(channel: "general", text: "...") — posts to #general
  • Use for coordination messages, status updates, announcements
  • Read channel history with list_messages(channel: "general")

check_inbox is the canonical way to read unread messages directed at you — it returns unread DMs, mentions, and reactions and does not resurface messages once read. For a full channel transcript use list_messages; for one thread use get_message_thread. To re-read a DM conversation you already consumed (an ACK/DONE you saw earlier, or a worker's full DM history), enumerate conversations with list_dms, then read one persistently with the CLI agent-relay message dm list <conversationId> — unlike check_inbox, that view does not clear on read.

# WRONG — node tail --agent streams the worker's raw output, not durable messages
agent-relay node tail --agent Worker1

# RIGHT — read messages addressed to you (DM replies, mentions)
check_inbox(limit: 20)

# RIGHT — read a channel's evidence trail (diffs, grep counts, GO/NO-GO)
list_messages(channel: "general", limit: 100)

# RIGHT — read one thread end to end
get_message_thread(message_id: "msg_123")

CLI-only equivalents (agent-token based, useful from a plain shell) live under the message group: agent-relay message inbox check, agent-relay message list <channel>, agent-relay message dm list <conversationId> (persistent DM history — list_dms gives the conversation id), agent-relay message get_thread <messageId>, agent-relay message dm send <agent> <text>, agent-relay message post <channel> <text>, agent-relay message reply <messageId> <text>.

Plain-Shell Orchestration (no relay MCP configured)

An orchestrating session without the relay MCP still has full read access: agent-relay message list <channel> --limit 50 works with no credentials and returns a JSON array (newest first; [] when the channel is empty — each item carries text, from.name, createdAt, kind). Every send, however, fails with requires agentToken or agentClient until the shell holds an agent token. Mint one once per project and keep it inside the gitignored broker state dir:

grep -qxF '.agentworkforce/' .gitignore 2>/dev/null || echo '.agentworkforce/' >> .gitignore
TOKEN=$(agent-relay agent register orchestrator --type system | grep -oE 'at_live_[A-Za-z0-9_-]+' | head -1)
[ -n "$TOKEN" ] || { echo "registration failed — no token captured" >&2; exit 1; }
(umask 077 && printf '%s' "$TOKEN" > .agentworkforce/relay/orchestrator.token)
chmod 600 .agentworkforce/relay/orchestrator.token   # tighten a pre-existing file too

TOKEN=$(cat .agentworkforce/relay/orchestrator.token)   # later shells re-read it
RELAY_AGENT_TOKEN="$TOKEN" agent-relay message post general "checkpoint: reviews start after both DONEs"
RELAY_AGENT_TOKEN="$TOKEN" agent-relay message dm send Worker1 "NO-GO findings: …"
RELAY_AGENT_TOKEN="$TOKEN" agent-relay message inbox check

Never echo, commit, or log the token. Registering also makes orchestrator a DM-able recipient for workers — the same identity an MCP-based session creates with the register_agent tool.

Monitoring Workers (Essential)

Spawn/send/release commands are in the Quick Reference and Bootstrap Step 3 — not repeated here. For monitoring specifically: poll agent-relay node agent list for broker-side liveness (pid, status, uptime) instead of scraping the worker TTY, and use agent-relay node agent attach <name> --mode view to watch real-time output when debugging.

Harness note: don't poll with a bare foreground sleep. Many harnesses (Claude Code included) block a foreground sleep used to wait for ACK/DONE — e.g. sleep 25; check_inbox ... is rejected with a directive to use a backgrounded loop or a Monitor/until-loop instead. The inline sleep-based snippets shown elsewhere in this skill are illustrative of the logic; in a harnessed environment, run the wait loop with run_in_background (or the harness's Monitor + until-loop), polling check_inbox and agent-relay node agent list from inside the backgrounded loop rather than blocking the foreground on sleep.

The push-style alternative to polling is a node tail pipeline used purely as a wake-up trigger, run through the harness's background-task facility (or with & in a plain shell — in the foreground it blocks until a match):

# Exits the moment a matching relay_inbound event arrives.
# Anchor on the body VALUE starting with the marker — not a loose substring.
agent-relay node tail | grep -m1 '"body":"DONE Implementer r2'

relay_inbound events carry each message's body, from, and target, and the stream replays a bounded window before following live. Two independent traps make a loose grep fire on the wrong event, and you need to defend against both:

  • Replay + quoting. A substring like REVIEW VERDICT: GO matches not only the real verdict but every earlier message that quoted the marker — an ACK saying "I'll post REVIEW VERDICT: GO when done" is in the replay window and fires first. Anchoring the pattern on "body":"<marker> (the body value beginning with the marker) rejects quotes, since a quoted marker sits mid-sentence after some other opening text.
  • Your own outbound. If you DM a worker the instructions containing the marker string, that DM is a relay_inbound event too (with "from":"orchestrator"). Add "from":"<Worker>" to the pattern, or anchor on the body as above, so your own messages can't trip it.

Give workers a run-specific marker (DONE <name> <round-tag> — <evidence>) so a replayed event from an earlier round can't match either. A bare "body":"DONE substring is only safe for a first, one-shot wait in a fresh workspace. This wakes you the second the event happens instead of on the next poll tick; it is still not the durable log, so read the actual messages with check_inbox / list_messages after waking. (Stock macOS has no timeout(1) — bound a one-off listen with python3 subprocess.run(..., timeout=N) or a backgrounded kill.)

Troubleshooting

# Release an unresponsive worker (graceful stop)
agent-relay node agent release Worker1

# Re-check broker status
agent-relay node status

# Workspace + cloud + broker overview
agent-relay status

# If a worker looks stuck, attach in view mode to inspect its TTY
agent-relay node agent attach Worker1 --mode view

Tip: Attach with --mode view or watch agent-relay node tail --agent <name> to monitor worker progress and catch errors early.

Orchestrator Instructions Template

Give your lead agent these instructions. The bootstrap/spawn/monitor commands are in the Bootstrap Flow and Quick Reference above — the paste-worthy part is the Protocol, the ruleset a lead agent can't infer from the command list:

You are an autonomous orchestrator. Bootstrap the local broker
(Bootstrap Flow Steps 0–2), then spawn and manage workers per the
Quick Reference. Then enforce this protocol:

## Protocol
- Workers will ACK when they receive tasks — but expect a 30–60s cold-start
  gap after spawn: a worker appears in `node agent list` (~5s) well before
  the CLI is booted enough to send its first ACK. Don't troubleshoot a "stuck"
  fresh worker until at least 60s has passed
- Workers will send DONE when complete
- In a harnessed environment, never wait with a bare foreground `sleep`
  (it is blocked) — run ACK/DONE poll loops with run_in_background or a
  Monitor/until-loop, polling `check_inbox` and `node agent list` from inside it
- **ACK/DONE target: `orchestrator` (the registered spawning identity) or
  the `general` channel — NEVER `broker`.** `broker` is the broker's internal
  routing self-name, not a spawnable/DM-able agent: a worker DM to `broker`
  fails with `Agent "broker" not found`. Write the worker task prompt to DM
  `orchestrator` (or post `general`) — never "DM the broker"
- Tell every worker explicitly: do NOT self-remove/release after DONE — stay
  alive and idle so you can DM them review findings to fix
- After DONE, run a reviewer; on NO-GO, DM the findings back to the SAME
  worker. If the worker is gone, spawn a fresh one and re-inject branch +
  commit SHA + the full verdict
- Read worker replies with `check_inbox` / `list_messages` / `get_message_thread`
  over the relay MCP — never `node tail` (that streams broker debug events,
  not worker messages). See the "Channel vs DM" section for the full reading
  model
- Poll `agent-relay node agent list` for worker liveness; set a wall-clock
  fallback so a silently-dead worker can't hang the loop
- If a human is watching, give them a follow-along link with
  `agent-relay observer` and print the URL it returns. Never print the
  workspace key or put it in a URL

Multi-Round Review Loops (DONE → NO-GO → fix → re-review)

Spawning, monitoring, and releasing a worker is the easy path. The hard part the basic flow does not cover: a worker reports DONE, a reviewer comes back NO-GO, and now the work has to go back. Plan for this topology before you spawn anything.

Workers must not self-remove until you tell them

A worker's natural hygiene instinct is to release itself right after reporting DONE. That kills the review→fix→re-review loop: when the reviewer returns NO-GO there is no agent left to send the findings to, so you are forced to spawn a fresh worker and re-inject the entire context (branch, commit, full verdict) instead of just DMing the existing one.

Put this in every implementer/worker task prompt explicitly:

Do NOT release yourself (no remove_agent / agent-relay node agent release on
yourself). Report DONE and stay alive and idle. The orchestrator will send you
review findings to fix, or release you when the work is fully accepted.
Self-removing before then breaks the fix loop.

The "release when done" guidance elsewhere in this skill applies to the orchestrator releasing workers — never to a worker releasing itself mid-loop.

The respawn-with-full-context fallback

If a worker did self-remove (or died), you cannot just DM it. Spawn a fresh worker and re-inject everything it needs to act with no prior memory:

agent-relay node agent spawn codex --name Implementer2 \
  --task "Continuation of prior work. \
Branch: feature/auth. Last commit: <sha>. \
The reviewer returned NO-GO with these findings: <full verdict text>. \
Check out the branch, address every finding, re-run tests, report DONE. \
Do NOT self-remove — stay alive for re-review."

Always pass branch + commit SHA + the complete reviewer verdict. A fresh worker has none of the loop's history; a summarized verdict loses the specifics it needs to fix.

Detecting a silently-dead worker

Inbox polling fires on messages only. A worker that exits or self-removes produces no message, so the inbox just goes quiet — indistinguishable from a worker still thinking. Defenses:

  • Poll agent-relay node agent list for liveness instead of inferring it from inbox silence. A worker that vanishes from the list is gone.
  • agent-relay node agent attach <name> --mode view (or node tail --agent <name>) will show a self-issued release call — but it is noisy TTY/event scraping, a last resort, not a signal.
  • Always set a wall-clock fallback (e.g. a ScheduleWakeup ~30 min out) so a silently-dead worker can't hang the loop forever waiting on a message that will never arrive.

Lifecycle Events

agent-relay node tail streams broker events. The broker emits these (also available via SDK subscriptions):

EventWhen
agent_spawnedWorker process started
worker_readyWorker connected to relay
agent_idleWorker waiting for messages
agent_exitedWorker process ended
agent_permanently_deadWorker failed after retries

Fleet and Capabilities

When you coordinate across nodes rather than only the local broker, capabilities and placement come into play:

# Fleet nodes need no per-workspace enablement.
agent-relay fleet status          # local broker status + this node's provider attachment

# Bring this node up, serving its node definition (advertises its capabilities).
# `fleet serve` was replaced by `node up`; --config points at the node file
# (auto-discovers agent-relay.{ts,tsx,js,...} when omitted)
agent-relay node up --config ./node.ts

# List fleet nodes in the workspace
agent-relay fleet nodes

# Register a custom capability (command) on this node — both flags are required
agent-relay capabilities register <command> --description "<what it does>" --handler <agent>
agent-relay capabilities list

From the relay MCP, query_nodes finds nodes by capability or name and spawn invokes the fleet spawn action — the engine places it on an eligible node (or a named target_node).

Is the node actually available?

online is not the same as available for placement. A node can be live and still never receive a spawn. Check the capability list, not the status field:

# `fleet nodes` HIDES offline/non-fleet records by default (it hid 385 of 390
# on a real workspace), so a node you are looking for may simply not be printed.
agent-relay fleet nodes --all > /tmp/nodes.raw    # redirect: output truncates at 64KB through a pipe
python3 - <<'PY'
import json, re
raw = open("/tmp/nodes.raw").read()
m = re.search(r"^\{", raw, re.M)          # first brace at start of a line, not inside the preamble
if not m:
    raise SystemExit("No JSON in output. Raw:\n" + raw[:500])
for n in json.loads(raw[m.start():]).get("nodes", []):
    caps = [c["name"] for c in n.get("capabilities", [])]
    print(f'{n.get("name")}  id={n.get("id")}  {n.get("status")}  live={n.get("live")}  {caps}')
PY

id is printed because that is the field you compare against in the placement proof below — dispatchedNodeId is a node id, not a name.

A placement target must carry the spawn:<agent-type> capability for the spawn you are requesting — a node advertising only spawn:claude is a valid target for fleet spawn claude and not for fleet spawn codex. release and relay:delivery-cursor-v1 are separate lifecycle capabilities, needed to manage the worker once placed. A record with no spawn:* capability at all is registered but cannot receive a spawn.

Prove placement end to end rather than trusting the roster — spawn from a different machine so you are testing placement and not a local spawn, confirm dispatchedNodeId matches the target's node id, then verify on the target host that the process actually exists, and release:

# STEP 0 — run everything below from a machine OTHER than <node>. Spawning on the
# same host you are testing proves nothing about placement.

# Read the token without leaving it in shell history or `ps` argv.
read -r -s -p 'Agent token: ' RELAY_AGENT_TOKEN; printf '\n'
export RELAY_AGENT_TOKEN
trap 'unset RELAY_AGENT_TOKEN' EXIT

agent-relay fleet spawn claude \
  --name placement-proof --node <node> --channel general \
  --task "Run hostname -s and reply with its output only." > /tmp/spawn.json

# STEP 1 — the control plane says it dispatched where you asked. The response carries
# a human-readable preamble before the JSON. Never abort here: a failed spawn is a
# result, and a traceback would skip the STEP 3 release and leak a running agent.
python3 - <<'PY'
import json, re
raw = open("/tmp/spawn.json").read()
m = re.search(r"^\{", raw, re.M)          # first brace at start of a line
inv = None
if m:
    try:
        inv = json.loads(raw[m.start():]).get("invocation")
    except ValueError:
        pass
if not inv:
    print("Spawn did not return an invocation — it likely failed. Raw output:\n" + raw)
else:
    print("dispatched to:", inv.get("dispatchedNodeId"),
          "| name:", (inv.get("node") or {}).get("name"),
          "| status:", inv.get("status"))
PY
# `dispatchedNodeId` must equal <node>'s `id` from the roster command above — it is an
# id (`node_…`), not a name. A mismatch means placement ignored your target; a match
# still proves nothing about execution, hence STEP 2.

# STEP 2 — the process actually exists. Run this ON THE TARGET HOST.
pgrep -fl placement-proof            # broker pty + CLI process must both be present

# STEP 3 — release from the control plane. Works regardless of how the node's broker
# was started. Do NOT use `node agent release` here: a fleet node started with
# --state-dir (as the LaunchAgent does) is unreachable from that subcommand.
agent-relay fleet release placement-proof

Steps 1 and 2 are separate claims. Step 1 alone is the mistake that makes a broken node look healthy — dispatch is recorded by the control plane whether or not anything ran.

Enrolling a new machine as a fleet node

Enrollment is a two-step API flow — mint on the control plane, redeem from the node:

  1. POST /api/v1/fleet/enrollment-tokens → single-use ocl_node_enr_…
  2. POST /api/v1/fleet/register, from the machine being enrolled

The node-side script is sandbox-node-bootstrap.sh, with README.md alongside it as the authoritative reference. Both live at dev-stack/fleet-node-bootstrap/ in the AgentWorkforce/cloud repository — they are not shipped with this skill, so you need access to that repo to run an enrollment. It supports Daytona, CF Containers, the local dev-stack runner, and Mac minis.

The script takes its inputs from the environment so secrets never reach ps argv. Populate the token with a silent read so it does not land in shell history either:

read -r -s -p 'Enrollment token: ' RELAY_ENROLLMENT_TOKEN; printf '\n'
trap 'unset RELAY_ENROLLMENT_TOKEN' EXIT

RELAY_ENROLLMENT_TOKEN="$RELAY_ENROLLMENT_TOKEN" \
RELAY_ENROLLMENT_URL='https://<app>/api/v1/fleet/register' \
RELAY_NODE_NAME='<name>' \
  sandbox-node-bootstrap.sh enroll

Never skip sandbox-node-bootstrap.sh preflight on a machine that already runs brokers. agent-relay node up calls killOrphanedBrokerProcesses(projectRoot) at startup, terminating every broker whose CWD is that root. findProjectRoot() walks up for markers (.git, package.json, .agentworkforce/relay), so a $HOME-rooted workdir resolves projectRoot=$HOME and reaps every $HOME-rooted broker. That is relay#1328 — a real incident that killed production brokers on a shared machine. Pin AGENT_RELAY_PROJECT to a unique per-instance dir and drop a physical .agentworkforce/relay marker there.

Enrollment persists to ~/.agentworkforce/relay/fleet-enrollments.json (holds a live nt_live_… node token — never echo this file). Once enrolled, a com.agentrelay.fleet-node LaunchAgent brings the node back automatically across reboots; a rebooted machine does not need re-enrolling.

Reaching a --state-dir broker

agent-relay node up --state-dir <dir> (how the com.agentrelay.fleet-node LaunchAgent starts every fleet node) writes its connection file to <dir>/connection.json. Every node agent subcommand except attach reads only the default ~/.agentworkforce/relay/connection.json, rejects --state-dir, and ignores AGENT_RELAY_DATA_DIR — so those subcommands report No running broker found against a perfectly healthy broker (relay#1446).

Prefer the control plane. agent-relay fleet nodes, fleet spawn and fleet release need no local connection file and work on any node regardless of how its broker was started. Reach for the workaround below only for a node-local subcommand that has no fleet equivalent.

DEF=~/.agentworkforce/relay/connection.json
SD=<state-dir>                       # the --state-dir the broker was started with

# -e alone is FALSE for a dangling symlink, which is exactly what a previous run
# leaves behind if it died before its cleanup — so test -L as well, or `ln -s`
# fails with "File exists" and the subcommand silently never runs.
if [ -e "$DEF" ] || [ -L "$DEF" ]; then
  echo "REFUSING: $DEF already exists — on some hosts this is a real connection file"
  echo "and clobbering it would break the default broker. If it is a dangling symlink"
  echo "from an interrupted run, remove it; otherwise inspect it before proceeding."
else
  mkdir -p "$(dirname "$DEF")"       # may not exist yet on a freshly provisioned node
  ln -s "$SD/connection.json" "$DEF"
  agent-relay node agent list        # ... or whichever node-local subcommand you need
  [ -L "$DEF" ] && rm "$DEF"         # remove ONLY a symlink, and only one we created
fi

Never use ln -sf here. The -f silently destroys a pre-existing connection file, and that file is a real regular file on some hosts — not a stale leftover. Delete this whole workaround once relay#1446 lands rather than letting it outlive the bug.

Common Mistakes

MistakeFix
agent-relay: command not found or mise/asdf shim errorEnsure Node is available first (node --version); if a shim is broken, fix the runtime manager, then install/use agent-relay
"Nested session" errorBroker handles this automatically; if running manually, unset CLAUDECODE env var
Broker not startingTry agent-relay node down first, then agent-relay node up --background --verbose and agent-relay node status --wait-for 10
Broker not ready after node status --wait-forThe process is alive but the broker API is not ready; inspect logs, retry readiness, or restart with agent-relay node down --force if it remains stuck
Broker stops immediately after startCheck ps aux | grep agent-relay-broker and .agentworkforce/relay/connection.json; if the process is alive but status is stopped, rerun status from the project root or pass --state-dir
Half-started broker: process alive but node status says stopped and Failed to read broker connection metadatanode up spawned a broker that never finished writing connection metadata (readiness timed out) and was not cleaned up. Do NOT just retry node up — it won't reap the orphan. Point every command at the same state dir — carrying it on only one kills one broker and then starts and inspects a different one. Order matters: the orphan's pid lives in $SD, so read it before anything deletes or recreates that directory. SD=.agentworkforce/relay (or the --state-dir the broker was started with), then (1) agent-relay node down --force --state-dir "$SD"; (2) if it is still alive, read the pid from $SD now and kill that single pid; (3) rm -rf "$SD"; (4) agent-relay node up --state-dir "$SD"; (5) agent-relay node status --state-dir "$SD" --wait-for 30. Doing (2) after (3)/(4) reads the new broker's pid and kills the healthy replacement while the orphan survives. Never pkill -f agent-relay-broker — -f matches the full command line, so on a shared host that kills every other project's broker and the agent PTYs they own
Worktree verification leaves git status dirtyRun agent-relay node down --force, then remove generated .agentworkforce/relay/ and .mcp.json from throwaway validation worktrees before committing
Spawn fails with internal reply droppedBroker likely is not fully ready yet; wait for readiness, then spawn one worker first
Workers not connectingEnsure broker started; check agent-relay node agent list and worker logs
Not monitoring workersAttach with agent-relay node agent attach <name> --mode view frequently to track progress
Workers seem stuckInspect with agent-relay node agent attach <name> --mode view for errors
Messages not deliveredCheck channel history with list_messages(channel: "general"); for new DMs use check_inbox, for already-read DM history use list_dms + agent-relay message dm list <conversationId>
CLI send fails with requires agentToken or agentClientPlain-shell sends need an agent token — register an orchestrator identity and pass it via RELAY_AGENT_TOKEN (see Plain-Shell Orchestration). Channel reads need no token
Monitor loop never matches the DONE postagent-relay message list <channel> returns newest first; in node tail, message text is in relay_inbound events' body field
Tried to read replies with node tailnode tail streams broker events; node tail --agent <name> streams the worker's raw output — neither is durable messages. Read replies with check_inbox / list_messages / get_message_thread
Worker DM to broker fails with Agent "broker" not foundExpected — broker is the broker's internal routing self-name, not a DM-able agent. Workers must ACK/DONE to orchestrator or general. Fix the worker task prompt; never instruct "DM the broker"
node status says running but node agent list/MCP calls return empty or Failed to query broker sessionThe CLI is dialing a stale/wrong broker — leftover .agentworkforce/relay/connection.json from a prior run on an old port, or a second broker process. ps aux | grep -c '[a]gent-relay-broker' (>1 ⇒ kill extras), compare .agentworkforce/relay/connection.json to the actual listening port, then agent-relay node down --force, delete .agentworkforce/relay/, agent-relay node up clean
Invalid agent token while broker + workers keep workingThe orchestrator shell has an unresolved ${RELAY_WORKSPACE_KEY}-style template being used as a literal key (broker/workers hold real tokens). Ensure the workspace key/token is actually resolved in the orchestrator env
New worker appears in node agent list but no ACK yetExpected — appearing means process up (~5s); the CLI cold-starts for another 30–45s before its first ACK DM. Wait ≥60s before troubleshooting a fresh worker
A node you know exists is missing from agent-relay fleet nodesThe default view hides offline/non-fleet records (385 of 390 hidden on a real workspace) — and the node may be present but past the cut. Use agent-relay fleet nodes --all
fleet nodes JSON fails to parse mid-objectOutput truncates at 64KB through a pipe. Redirect to a file first (agent-relay fleet nodes --all > /tmp/nodes.raw) and parse the file, never the pipe
node agent list/release says No running broker found (…/relay/connection.json does not exist) while the fleet node is clearly runningThe subcommand is reading the default connection path, not the broker's --state-dir one (relay#1446). Use the control-plane equivalent — agent-relay fleet release <name> / fleet nodes — which needs no local connection file. See Reaching a --state-dir broker for the guarded workaround when only a node-local subcommand will do
Targeted fleet spawn fails with Targeted Fleet spawn requires an agent tokenPass --token or set RELAY_AGENT_TOKEN; mint one with agent-relay agent register <name> --type system (capture it without echoing). --task is also mandatory and the error only surfaces one problem at a time
Node shows online but never receives a spawnonline ≠ available. Check capabilities contains spawn:* — a record can be live with no spawn capacity. Confirm with a throwaway targeted spawn, verified by pgrep on the target host, then release
Harness blocks sleep 25; check_inbox ...Bare foreground sleep wait loops are disallowed in harnessed environments. Run the poll loop with run_in_background (or Monitor + until-loop); the inline sleep snippets show logic only
Worker self-removed; can't send review fixesInstruct workers not to self-remove until told. If already gone, spawn a fresh worker and re-inject branch + commit SHA + full verdict (see Multi-Round Review Loops)
Told the user to open an observer URL built from the workspace keyThat is an admin credential in a query string, and the realtime endpoint rejects it. Run agent-relay observer (or get_observer_url) and share the ot_live_ URL it returns
Worker died silently; loop hangsInbox polling fires on messages only. Poll agent-relay node agent list for liveness and set a wall-clock fallback (~30 min ScheduleWakeup)

Prerequisites

  1. agent-relay CLI installed (required)

    npm install -g agent-relay
    # Or use npx without installing: npx agent-relay <command>
    
  2. For spawning Claude agents: Valid Anthropic credentials

    • Set ANTHROPIC_API_KEY or authenticate via claude auth login
  3. For MCP-based coordination: run agent-relay mcp as the relay MCP stdio server in your client's MCP settings, then register the session once with the register_agent tool (as orchestrator). Messaging tools (send_dm, post_message, check_inbox, …) work only after that call — before it they fail with Not registered. Call the "register_agent" tool first.

相似的 Skill

shipping-and-launch
addyosmani/agent-skills103k

shipping-and-launch

Prepares production launches. Use when preparing to deploy to production, or when asking what needs to be in place before shipping. Use when you need a pre-launch checklist, when setting up monitoring, when planning a staged rollout, or when you need a rollback strategy.

DevOps 与云

publish
code-yeongyu/oh-my-openagent70k

publish

Publish oh-my-opencode to npm by triggering the GitHub Actions publish workflow and verifying its artifacts. Ship-only: never runs pre-publish-review or re-reviews merged code unless the user explicitly asks. Argument: <patch|minor|major|explicit-semver>. Triggers: publish, release, deploy, npm publish.

DevOps 与云

acceptance-orchestrator
sickn33/agentic-awesome-skills47k

acceptance-orchestrator

Use when a coding task should be driven end-to-end from issue intake through implementation, review, deployment, and acceptance verification with minimal human re-intervention.

DevOps 与云

event-store-design
wshobson/agents40k

event-store-design

Design and implement event stores for event-sourced systems. Use when building event sourcing infrastructure, choosing event store technologies, or implementing event persistence patterns.

DevOps 与云

arize-ai-provider-integration
github/awesome-copilot40k

arize-ai-provider-integration

Creates, reads, updates, and deletes Arize AI integrations that store LLM provider credentials used by evaluators and other Arize features. Supports any LLM provider (e.g. OpenAI, Anthropic, Azure OpenAI, AWS Bedrock, Vertex AI, Gemini, NVIDIA NIM). Use when the user mentions AI integration, LLM provider credentials, create integration, list integrations, update credentials, delete integration, or connecting an LLM provider to Arize.

DevOps 与云

appinsights-instrumentation
github/awesome-copilot40k

appinsights-instrumentation

Instrument a webapp to send useful telemetry data to Azure App Insights

DevOps 与云