pipeline-subagents

name	pipeline-subagents
description	Design and execute a custom multi-agent pipeline using Claude Code subagents directly. Spawns researcher, builder, etc. via the Agent tool with native parallel and background execution. Use when the user says 'run a pipeline for X' and factory subagents are available.
disable-model-invocation	true
argument-hint	<goal>

Pipeline (Subagents) — Dynamic Multi-Agent Orchestrator

You design and execute custom multi-agent pipelines using Claude Code's native Agent tool to spawn factory subagents directly.

The user wants: $ARGUMENTS

Setup

mkdir -p .factory/pipeline

Your Agents

Spawn specialists using the Agent tool with the plugin-namespaced subagent type factory:<role>:

Agent({
  description: "<short description>",
  prompt: "<detailed task>",
  subagent_type: "factory:<role>"
})

Subagent Type	Purpose
factory:researcher	Web research, codebase analysis, domain studies
factory:strategist	Generate prioritized hypotheses from observations
factory:builder	Implement code changes on a feature branch, open PRs
factory:qa	Health checks, code review, adversarial QA verification
factory:archivist	Record findings to .factory/archive/
factory:distiller	Refine vague ideas into buildable specs

Also available: factory:failure_analyst (classify experiment failures by root cause — use when analyzing why a prior experiment failed).

Parallel Execution

Issue multiple Agent tool calls in the same message — they run concurrently:

Agent({ subagent_type: "factory:researcher", prompt: "Research the auth bug..." })
Agent({ subagent_type: "factory:qa", prompt: "Run baseline eval..." })

This is concurrent execution via parallel tool calls, not shell backgrounding. Each Agent call is still individually synchronous.

Background Execution

For non-blocking steps (e.g., archival):

Agent({ subagent_type: "factory:archivist", prompt: "Archive findings...", run_in_background: true })

Phase 1: Design the Pipeline

1. Understand the goal — what outcome is desired? Which agents are needed?
2. Inspect project state (use Bash tool):

   ls .factory/config.json 2>/dev/null && cat .factory/config.json
   

3. Write the pipeline plan to .factory/pipeline/plan.md:

## Pipeline: <goal summary>

### Steps

| Step | Role | Task Summary | Depends On |
|------|------|-------------|-----------|
| S1 | researcher | ... | - |
| S2 | qa | ... | - |
| S3 | strategist | ... | S1, S2 |
| ... | ... | ... | ... |

### Gate Rules
- After S1: PROCEED if ...; REDIRECT if ...
- After S3: PROCEED if ...; ABORT if ...

Design Principles

• Minimize invocations — only agents needed for this goal
• Maximize parallelism — steps whose dependencies are all satisfied and that don't depend on each other can be spawned in the same message
• Mandatory archival — always include at least one archivist step at the end
• Gate rules — define PROCEED/REDIRECT/ABORT criteria for critical transitions

Phase 2: Execute the Pipeline

Process steps in topological order:

1. Identify next batch — steps whose dependencies are all complete
2. Build prompts — incorporate output from prior steps (agent results are returned directly)
3. Emit start event and invoke agents:

   factory emit agent.started --agent <role> --project "$(pwd)"
   

   Then invoke via Agent tool (single, parallel batch, or background for archival).
4. Read results — Agent tool returns subagent output directly
5. Persist review and emit completion:

   mkdir -p .factory/reviews
   factory emit agent.completed --agent <role> --project "$(pwd)"
   

   Then use the Write tool to save the agent output to .factory/reviews/<role>-latest.md
6. Apply gate rule:
   • PROCEED: Move to next step
   • REDIRECT: Re-invoke with corrections (max 2 per step)
   • ABORT: Skip downstream steps, jump to summary
7. Repeat until done

Error Recovery

• Agent error: retry once with simpler prompt
• 2 consecutive failures: ABORT pipeline

Final Summary

Write .factory/pipeline/summary.md with goal, status, step results, and key findings.