Writing Agent Relay Workflows

Writing Agent Relay Workflows

Overview

The relay broker-sdk workflow system orchestrates multiple AI agents (Claude, Codex, Gemini, Aider, Goose) through typed DAG-based workflows. Workflows can be written in TypeScript (preferred), Python, or YAML.

Language preference: TypeScript > Python > YAML. Use TypeScript unless the project is Python-only or a simple config-driven workflow suits YAML.

When to Use

• Building multi-agent workflows with step dependencies
• Orchestrating different AI CLIs (claude, codex, gemini, aider, goose)
• Creating DAG, pipeline, fan-out, or other swarm patterns
• Needing verification gates, retries, or step output chaining
• Dynamic channel management: agents joining/leaving/muting channels mid-workflow

Quick Reference

import { workflow } from '@agent-relay/sdk/workflows';

const result = await workflow('my-workflow')
  .description('What this workflow does')
  .pattern('dag') // or 'pipeline', 'fan-out', etc.
  .channel('wf-my-workflow') // dedicated channel (auto-generated if omitted)
  .maxConcurrency(3)
  .timeout(3_600_000) // global timeout (ms)

  .agent('lead', { cli: 'claude', role: 'Architect', retries: 2 })
  .agent('worker', { cli: 'codex', role: 'Implementer', retries: 2 })

  .step('plan', {
    agent: 'lead',
    task: `Analyze the codebase and produce a plan.`,
    retries: 2,
    verification: { type: 'output_contains', value: 'PLAN_COMPLETE' },
  })
  .step('implement', {
    agent: 'worker',
    task: `Implement based on this plan:\n{{steps.plan.output}}`,
    dependsOn: ['plan'],
    verification: { type: 'exit_code' },
  })

  .onError('retry', { maxRetries: 2, retryDelayMs: 10_000 })
  .run({ cwd: process.cwd() });

  console.log('Result:', result.status);

Critical TypeScript rules: 1. Check the project's package.json for "type": "module" — if ESM, use import and top-level await. If CJS, use require() and wrap in async function main(). 2. agent-relay run <file.ts> executes the file as a standalone subprocess — it does NOT inspect exports. The file MUST call .run(). 3. Use .run({ cwd: process.cwd() }) — createWorkflowRenderer does not exist 4. Validate with --dry-run before running: agent-relay run --dry-run workflow.ts

⚡ Parallelism — Design for Speed

This is the most important design consideration. Sequential workflows waste hours. Always design for maximum parallelism.

Cross-Workflow Parallelism: Wave Planning

When a project has multiple workflows, group independent ones into parallel waves:

# BAD — sequential (14 hours for 27 workflows at ~30 min each)
agent-relay run workflows/34-sst-wiring.ts
agent-relay run workflows/35-env-config.ts
agent-relay run workflows/36-loading-states.ts
# ... one at a time

# GOOD — parallel waves (3-4 hours for 27 workflows)
# Wave 1: independent infra (parallel)
agent-relay run workflows/34-sst-wiring.ts &
agent-relay run workflows/35-env-config.ts &
agent-relay run workflows/36-loading-states.ts &
agent-relay run workflows/37-responsive.ts &
wait
git add -A && git commit -m "Wave 1"

# Wave 2: testing (parallel — independent test suites)
agent-relay run workflows/40-unit-tests.ts &
agent-relay run workflows/41-integration-tests.ts &
agent-relay run workflows/42-e2e-tests.ts &
wait
git add -A && git commit -m "Wave 2"

Wave Planning Heuristics

Two workflows can run in parallel if they don't have write-write or write-read file conflicts:

Declare File Scope for Planning

Help wave planners (human or automated) understand what each workflow touches:

workflow('48-comparison-mode')
  .packages(['web', 'core'])                // monorepo packages touched
  .isolatedFrom(['49-feedback-system'])      // explicitly safe to parallelize
  .requiresBefore(['46-admin-dashboard'])    // explicit ordering constraint

Within-Workflow Parallelism

Use shared dependsOn to fan out independent sub-tasks:

// BAD — unnecessary sequential chain
.step('fix-component-a', { agent: 'worker', dependsOn: ['review'] })
.step('fix-component-b', { agent: 'worker', dependsOn: ['fix-component-a'] })  // why wait?

// GOOD — parallel fan-out, merge at the end
.step('fix-component-a', { agent: 'impl-1', dependsOn: ['review'] })
.step('fix-component-b', { agent: 'impl-2', dependsOn: ['review'] })  // same dep = parallel
.step('verify-all', { agent: 'reviewer', dependsOn: ['fix-component-a', 'fix-component-b'] })

Impact

Real-world example (Relayed — 60 workflows):

• Sequential: ~30 min × 60 = 30 hours
• Parallel waves (4-6 per wave): ~12 waves × 35 min = ~7 hours (4x faster)
• Aggressive parallelism (8-way): ~4 hours (7.5x faster)

---

Key Concepts

Step Output Chaining

Use {{steps.STEP_NAME.output}} in a downstream step's task to inject the prior step's terminal output.

Only chain output from clean sources:

• Deterministic steps (shell commands — always clean)
• Non-interactive agents (preset: 'worker' — clean stdout)

Never chain from interactive agents (cli: 'claude' without preset) — PTY output includes spinners, ANSI codes, and TUI chrome. Instead, have the agent write to a file, then read it in a deterministic step.

Verification Gates

verification: { type: 'exit_code' }                        // preferred for code-editing steps
verification: { type: 'output_contains', value: 'DONE' }   // optional accelerator
verification: { type: 'file_exists', value: 'src/out.ts' } // deterministic file check

Only these four types are valid: exit_code, output_contains, file_exists, custom. Invalid types are silently ignored and fall through to process-exit auto-pass.

Verification token gotcha: If the token appears in the task text, the runner requires it twice in output (once from task echo, once from agent). Prefer exit_code for code-editing steps to avoid this.

DAG Dependencies

Steps with dependsOn wait for all listed steps. Steps with no dependencies start immediately. Steps sharing the same dependsOn run in parallel:

.step('fix-types',  { agent: 'worker', dependsOn: ['review'], ... })
.step('fix-tests',  { agent: 'worker', dependsOn: ['review'], ... })
.step('final',      { agent: 'lead',   dependsOn: ['fix-types', 'fix-tests'], ... })

Self-Termination

Do NOT add exit instructions to task strings. The runner handles this automatically.

Step Completion Model

Steps complete through a multi-signal pipeline (highest priority first):

1. Deterministic verification — exit_code, file_exists, output_contains pass → immediate completion 2. Owner decision — OWNER_DECISION: COMPLETE|INCOMPLETE_RETRY|INCOMPLETE_FAIL 3. Evidence-based — channel signals, file artifacts, clean exit code 4. Marker fast-path — STEP_COMPLETE:<step-name> (optional accelerator) 5. Process-exit fallback — agent exits 0 with no signals → completes after grace period

Key principle: No single signal is mandatory. Describe the deliverable, not what to print.

Dynamic Channel Management

Agents can dynamically subscribe, unsubscribe, mute, and unmute channels after spawn. This eliminates the need for client-side channel filtering and manual peer fanout.

SDK API

// Subscribe an agent to additional channels post-spawn
relay.subscribe({ agent: 'security-auditor', channels: ['review-pr-456'] });

// Unsubscribe — agent leaves the channel entirely
relay.unsubscribe({ agent: 'security-auditor', channels: ['general'] });

// Mute — agent stays subscribed (history access) but messages are NOT injected into PTY
relay.mute({ agent: 'security-auditor', channel: 'review-pr-123' });

// Unmute — resume PTY injection
relay.unmute({ agent: 'security-auditor', channel: 'review-pr-123' });

Agent-level methods are also available:

const agent = await relay.claude.spawn({ name: 'auditor', channels: ['ch-a'] });
await agent.subscribe(['ch-b']);       // now subscribed to ch-a and ch-b
await agent.mute('ch-a');              // ch-a messages silenced (still in history)
await agent.unmute('ch-a');            // ch-a messages resume
await agent.unsubscribe(['ch-b']);     // leaves ch-b
console.log(agent.channels);          // ['ch-a']
console.log(agent.mutedChannels);     // []

Semantics

Events

relay.onChannelSubscribed = (agent, channels) => { /* ... */ };
relay.onChannelUnsubscribed = (agent, channels) => { /* ... */ };
relay.onChannelMuted = (agent, channel) => { /* ... */ };
relay.onChannelUnmuted = (agent, channel) => { /* ... */ };

When to Use in Workflows

• Multi-PR chat sessions: Agents focused on one PR can mute other PR channels to reduce noise
• Phase transitions: Subscribe agents to new channels as work progresses between phases
• Team isolation: Workers mute the main coordination channel during focused work, unmute for review
• Dynamic fanout: A lead subscribes workers to sub-channels at runtime based on task decomposition

What This Eliminates

With broker-managed subscriptions, you no longer need: 1. Client-side persona filtering (personaNames.has(from) checks) 2. Channel prefix regex for message routing 3. Manual peer fanout (iterating agents to forward messages) 4. Dedup caches for dual-path delivery

Agent Definition

.agent('name', {
  cli: 'claude' | 'codex' | 'gemini' | 'aider' | 'goose' | 'opencode' | 'droid',
  role?: string,
  preset?: 'lead' | 'worker' | 'reviewer' | 'analyst',
  retries?: number,
  model?: string,
  interactive?: boolean, // default: true
})

Post-spawn channel operations (available on Agent instances and AgentRelay facade):

// Agent instance methods
agent.subscribe(channels: string[]): Promise<void>
agent.unsubscribe(channels: string[]): Promise<void>
agent.mute(channel: string): Promise<void>
agent.unmute(channel: string): Promise<void>
agent.channels: string[]          // current subscribed channels
agent.mutedChannels: string[]     // currently muted channels

// AgentRelay facade methods (by agent name)
relay.subscribe({ agent: string, channels: string[] }): Promise<void>
relay.unsubscribe({ agent: string, channels: string[] }): Promise<void>
relay.mute({ agent: string, channel: string }): Promise<void>
relay.unmute({ agent: string, channel: string }): Promise<void>

Non-interactive presets run via one-shot mode (claude -p, codex exec). Output is clean and available via {{steps.X.output}}.

Critical rule: Pre-inject content into non-interactive agents. Don't ask them to read large files — pre-read in a deterministic step and inject via {{steps.X.output}}.

Step Definition

Agent Steps

.step('name', {
  agent: string,
  task: string,                   // supports {{var}} and {{steps.NAME.output}}
  dependsOn?: string[],
  verification?: VerificationCheck,
  retries?: number,
})

Deterministic Steps (Shell Commands)

.step('verify-files', {
  type: 'deterministic',
  command: 'test -f src/auth.ts && echo "FILE_EXISTS"',
  dependsOn: ['implement'],
  captureOutput: true,
  failOnError: true,
})

Use for: file checks, reading files for injection, build/test gates, git operations.

Common Patterns

Pipeline (sequential handoff)

.pattern('pipeline')
.step('analyze', { agent: 'analyst', task: '...' })
.step('implement', { agent: 'dev', task: '{{steps.analyze.output}}', dependsOn: ['analyze'] })
.step('test', { agent: 'tester', task: '{{steps.implement.output}}', dependsOn: ['implement'] })

Error Handling

.onError('fail-fast')   // stop on first failure (default)
.onError('continue')    // skip failed branches, continue others
.onError('retry', { maxRetries: 3, retryDelayMs: 5000 })

Multi-File Edit Pattern

When a workflow needs to modify multiple existing files, use one agent step per file with a deterministic verify gate after each. Agents reliably edit 1-2 files per step but fail on 4+.

steps:
  - name: read-types
    type: deterministic
    command: cat src/types.ts
    captureOutput: true

  - name: edit-types
    agent: dev
    dependsOn: [read-types]
    task: |
      Edit src/types.ts. Current contents:
      {{steps.read-types.output}}
      Add 'pending' to the Status union type.
      Only edit this one file.
    verification:
      type: exit_code

  - name: verify-types
    type: deterministic
    dependsOn: [edit-types]
    command: 'if git diff --quiet src/types.ts; then echo "NOT MODIFIED"; exit 1; fi; echo "OK"'
    failOnError: true

  - name: read-service
    type: deterministic
    dependsOn: [verify-types]
    command: cat src/service.ts
    captureOutput: true

  - name: edit-service
    agent: dev
    dependsOn: [read-service]
    task: |
      Edit src/service.ts. Current contents:
      {{steps.read-service.output}}
      Add a handlePending() method.
      Only edit this one file.
    verification:
      type: exit_code

  - name: verify-service
    type: deterministic
    dependsOn: [edit-service]
    command: 'if git diff --quiet src/service.ts; then echo "NOT MODIFIED"; exit 1; fi; echo "OK"'
    failOnError: true

  # Deterministic commit — never rely on agents to commit
  - name: commit
    type: deterministic
    dependsOn: [verify-service]
    command: git add src/types.ts src/service.ts && git commit -m "feat: add pending status"
    failOnError: true

Key rules:

• Read the file in a deterministic step right before the edit (not all files upfront)
• Tell the agent "Only edit this one file" to prevent it touching other files
• Verify with git diff --quiet after each edit — fail fast if the agent didn't write
• Always commit with a deterministic step, never an agent step

File Materialization: Verify Before Proceeding

After any step that creates files, add a deterministic file_exists check before proceeding. Non-interactive agents may exit 0 without writing anything (wrong cwd, stdout instead of disk).

- name: verify-files
  type: deterministic
  dependsOn: [impl-auth, impl-storage]
  command: |
    missing=0
    for f in src/auth/credentials.ts src/storage/client.ts; do
      if [ ! -f "$f" ]; then echo "MISSING: $f"; missing=$((missing+1)); fi
    done
    if [ $missing -gt 0 ]; then echo "$missing files missing"; exit 1; fi
    echo "All files present"
  failOnError: true

Rules for file-writing tasks: 1. Use full paths from project root — say src/auth/credentials.ts, not credentials.ts 2. Add IMPORTANT: Write the file to disk. Do NOT output to stdout. 3. Use file_exists verification for creation steps (not just exit_code) 4. Gate all downstream steps on the verify step

DAG Deadlock Anti-Pattern

# WRONG — deadlock: coordinate depends on context, work-a depends on coordinate
steps:
  - name: coordinate
    dependsOn: [context]    # lead waits for WORKER_DONE...
  - name: work-a
    dependsOn: [coordinate] # ...but work-a can't start until coordinate finishes

# RIGHT — workers and lead start in parallel
steps:
  - name: context
    type: deterministic
  - name: work-a
    dependsOn: [context]    # starts with lead
  - name: coordinate
    dependsOn: [context]    # starts with workers
  - name: merge
    dependsOn: [work-a, coordinate]

Rule: if a lead step's task mentions downstream step names alongside waiting keywords, that's a deadlock.

Step Sizing

One agent, one deliverable. A step's task prompt should be 10-20 lines max.

Split into a lead + workers team when:

• The task requires a 50+ line prompt
• The deliverable is multiple files that must be consistent
• You need one agent to verify another's output

# Team pattern: lead + workers on a shared channel
steps:
  - name: track-lead-coord
    agent: track-lead
    dependsOn: [prior-step]
    task: |
      Lead the track on #my-track. Workers: track-worker-1, track-worker-2.
      Post assignments to the channel. Review worker output.

  - name: track-worker-1-impl
    agent: track-worker-1
    dependsOn: [prior-step]  # same dep as lead — starts concurrently
    task: |
      Join #my-track. track-lead will post your assignment.
      Implement the file as directed.
    verification:
      type: exit_code

  - name: next-step
    dependsOn: [track-lead-coord]  # downstream depends on lead, not workers

Supervisor Pattern

When you set .pattern('supervisor') (or hub-spoke, fan-out), the runner auto-assigns a supervisor agent as owner for worker steps. The supervisor monitors progress, nudges idle workers, and issues OWNER_DECISION.

Auto-hardening only activates for hub patterns — not pipeline or dag.

Concurrency

Cap `maxConcurrency` at 4-6. Spawning 10+ agents simultaneously causes broker timeouts.

Common Mistakes

YAML Alternative

version: '1.0'
name: my-workflow
swarm:
  pattern: dag
  channel: wf-my-workflow
agents:
  - name: lead
    cli: claude
    role: Architect
  - name: worker
    cli: codex
    role: Implementer
workflows:
  - name: default
    steps:
      - name: plan
        agent: lead
        task: 'Produce a detailed implementation plan.'
      - name: implement
        agent: worker
        task: 'Implement: {{steps.plan.output}}'
        dependsOn: [plan]
        verification:
          type: exit_code

Run with: agent-relay run path/to/workflow.yaml

Available Swarm Patterns

dag (default), fan-out, pipeline, hub-spoke, consensus, mesh, handoff, cascade, debate, hierarchical, map-reduce, scatter-gather, supervisor, reflection, red-team, verifier, auction, escalation, saga, circuit-breaker, blackboard, swarm

See skill choosing-swarm-patterns for pattern selection guidance.