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BuilderIO/factory

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factory

Experimental workflow for configuring an autonomous software delivery factory. Use when choosing feedback sources, schedules, worktree behavior, autonomy gates, or host automations.

v1.0LATEST
NewUpdated Sep 24, 2026

Factory

Start with the Factory guide for workflow setup and configuration.

Read .agent-factory/config.yaml and apply the optional skill_prompts.factory entry as additional project guidance. Configure the current project to turn selected product or maintenance signals into verified, reviewed changes. Factory coordinates the other modules; it does not assume a provider, repository, schedule, or autonomy level.

Set up

Use the Factory configuration reference for field meanings, examples, and host limitations.

  1. Read .agent-factory/config.yaml if it exists. Preserve explicit choices.
  2. Show the read-capable integrations this host exposes. There is no built-in Factory source catalog. Confirm the source scope; add a custom source only when a connected tool can read it.
  3. Set each action policy independently: implement, reply, close, review, approve, publish, merge, deploy, recover, and notify.
  4. Add optional per-skill prompts under skill_prompts when you want project-specific rules layered onto a module.
  5. Choose schedules, time zone, worktree ownership, runtime, and notifications only where the host supports them.
  6. Write the agreed config. Never put credentials or tokens in it.
  7. If asked to create automations, create one job per enabled workflow, then read back its saved schedule, target, runtime, and notification settings. Report fields the host could not honor.

A config entry or written prompt does not prove a job exists. Treat unavailable or partial reads as unknown, not empty or successful.

Safe defaults

  • Keep replies, issue closure, approvals, merges, production deploys, and recovery disabled unless their own policy is explicit.
  • For criteria-based actions, record both conditions that allow the action and conditions that require a human.
  • Missing or unclear policy means hold. Permission to fix does not authorize publication or another external action.

Modules

Skill Scope
factory-collect Collect and triage configured feedback, telemetry, errors, and issues.
factory-lookback Find recurring signals and brittle paths that need systemic fixes.
factory-human-digest Aggregate work that still needs a human decision.
factory-review-prs Review a filtered PR queue.
factory-babysit-pr Follow one explicitly authorized PR.
factory-ship Publish and complete a delivery lifecycle.
factory-watchdog Find stopped, authorized delivery work.
factory-recover Resume valid interrupted runs.

Modules can run independently. Each reads the same project config and must not borrow permissions from another workflow.

Prompt overlays

skill_prompts is an open map from a skill name to a multiline prompt. Each Factory module reads its matching entry, such as skill_prompts.factory-babysit-pr, and treats it as additional project guidance. Editing or removing that value replaces or removes the project overlay; it never replaces the installed skill instructions.

For scheduled runs, include the matching overlay in the saved automation prompt and verify the host retained it. A prompt cannot grant a permission, weaken repository or host safeguards, or override the user's current request. If it conflicts with those rules, follow the more restrictive requirement and surface the conflict.

Report

State which sources and host capabilities were verified, which policies and jobs were configured, what remains manual, and any unavailable evidence. Never claim that a schedule, integration, merge, or deployment exists without reading back its live state.

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Overall Score

82/100

Grade

B

Good

Grades are signals, not a certification. Always review a skill yourself before use.

Safety

88

Quality

80

Clarity

83

Completeness

76

Summary

The factory skill configures an autonomous software delivery system by reading and writing `.agent-factory/config.yaml` to define feedback sources, action policies, schedules, and worktree behavior. It serves as a coordinator that delegates to specialized factory modules (collect, review, ship, recover, etc.) and applies optional project-specific prompts as overlays. The skill emphasizes safe defaults and explicit human gates for sensitive actions.

Detected Capabilities

file read (.agent-factory/config.yaml)file write (.agent-factory/config.yaml)project configuration managementdocumentation reference (GitHub links)integration discovery and verification

Trigger Keywords

Phrases that agents use to match this skill to user intent.

autonomous delivery setupconfigure factory workflowdefine merge policiesset up automation jobsconfigure feedback sourcesdelivery pipeline automation

Risk Signals

INFO

External documentation links (GitHub) for full configuration reference

SKILL.md line 18, reference to external docs
INFO

Explicit instruction to never write credentials or tokens to config

SKILL.md step 6
INFO

Reads and preserves existing .agent-factory/config.yaml state

SKILL.md step 1

Referenced Domains

External domains referenced in skill content, detected by static analysis.

github.com

Use Cases

  • Set up autonomous feedback collection and triage workflows
  • Define approval, merge, and deployment policies for automated delivery
  • Configure project-specific constraints and prompts for factory modules
  • Map available integrations and data sources to collection workflows
  • Establish schedules, time zones, and notification settings for automation jobs
  • Document which actions remain manual vs. automated in a delivery pipeline

Quality Notes

  • Excellent safety guardrails: step 6 explicitly forbids credentials in config; safe defaults section emphasizes human gates for sensitive actions
  • Clear modular design with distinct skill responsibilities documented in table format
  • Prompt overlay mechanism is well-explained and includes safeguards against permission escalation
  • Strong emphasis on verification: never claims a schedule/job exists without reading back live state
  • Scope is deliberately broker-agnostic (no built-in provider assumptions), which is appropriate for a coordinator
  • Comprehensive setup checklist with numbered steps that include verification and validation
  • Uses conditional language (available, partial reads, unknown) appropriately for error states
  • Reference to external Factory guide and configuration reference docs supports but does not replace in-skill guidance
Model: claude-haiku-4-5-20251001Analyzed: Sep 24, 2026

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