Add Custom Settings

Complete workflow for adding custom settings to a Bottlerocket variant, from model creation through local testing.

Roles

You (reading this file) are the orchestrator.

Role	Reads	Does
Orchestrator (you)	SKILL.md, next-step.py output	Runs state machine, spawns subagents, writes outputs
State machine	progress.json, workspace files	Decides next action, validates gates
Subagent	Phase file (e.g., PLAN.md)	Executes phase instructions

⚠️ You do NOT read files in phases/ — pass them to subagents via context_files. Subagents read their phase file and execute it.

Orchestrator Loop

python

import json
from datetime import datetime

timestamp = datetime.now().strftime("%Y%m%d-%H%M%S")
workspace = f"planning/add-custom-settings-{timestamp}"
bash(f"mkdir -p {workspace}", on_error="raise")

while True:
    result = bash(f"python3 skills/add-custom-settings/next-step.py {workspace}", on_error="raise")
    action = json.loads(result)
    
    if action["type"] == "done":
        final = fs_read("Line", f"{workspace}/FINAL.md", 1, -1)
        log(final)
        break
    
    if action["type"] == "gate_failed":
        log(f"Gate failed: {action['reason']}")
        break
    
    if action["type"] == "spawn":
        r = spawn(
            action["prompt"],
            context_files=action["context_files"],
            context_data=action.get("context_data", {}),
            allow_tools=True
        )
        write("create", f"{workspace}/{action['output_file']}", file_text=r.response)

Handling Exceptions

The state machine handles the happy path. When things go wrong, exercise judgment:

Exception	Response
Spawn times out	Assess: retry with longer timeout? Report partial progress?
Spawn returns error	Report failure to state machine, let it track retries
Empty/invalid response	Treat as failure, report to state machine

Don't silently advance past failures. Either retry, fail explicitly, or document gaps.

Anti-Patterns

❌ Don't	✅ Do
Read phase files yourself	Pass phase files via context_files to subagents
Decide what phase is next	State machine decides via next-step.py
Skip gates "because it looks done"	Always validate gates
Store state in your memory	State lives in progress.json
Silently advance past failures	Retry, fail, or document gaps

Phases

PLAN: Gather requirements (settings name, structure, target variant)
CREATE-MODEL: Execute create-settings-model skill
WIRE-VARIANT: Execute add-settings-to-variant skill
TEST: Execute test-settings-locally skill
FINALIZE: Create summary document

Inputs

The orchestrator needs to create a workspace before starting. The PLAN phase will gather:

Settings name and structure
Target variant
Any special requirements

Outputs

Produces workspace at planning/add-custom-settings-<timestamp>/ containing:

requirements.json - Captured requirements
01-model.md - Model creation output
02-variant.md - Variant wiring output
03-test.md - Testing output
FINAL.md - Complete workflow summary

Search AI Tools

add-custom-settings-cbgbt-bottlerocket-forest

Install this agent skill to your Project

SKILL.md