Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx skills add darkroomengineering/cc-settings --skill refactorgit clone --depth 1 https://github.com/darkroomengineering/cc-settingsWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/skills/darkroomengineering/cc-settings/refactor)<a href="https://agentmods.dev/skills/darkroomengineering/cc-settings/refactor"><img src="https://agentmods.dev/badge/skills/darkroomengineering/cc-settings/refactor/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/darkroomengineering/cc-settings/refactor"><img src="https://agentmods.dev/badge/skills/darkroomengineering/cc-settings/refactor.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector pass
What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00058 | $0.00782 |
| Opus 5.5 | $0.00023 | $0.00313 |
| Sonnet 5.5 | $0.00012 | $0.00156 |
| Haiku 4.5 | $0.00006 | $0.00078 |
Grade A, and why
refactor scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 14d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
How it starts
The opening of the file, as written. The whole thing — 76 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Refactoring Workflow
Standalone Codex
Create each new agent with spawn_agent, deliver
context to a running agent with send_message, trigger another turn for an idle
existing agent with followup_task, wait with wait_agent, and stop a current
turn with interrupt_agent only when necessary. Never spawn codex-verifier
and never run codex-run.ts from inside Codex.
Writers share the working tree unless the live host explicitly offers isolation. Assign non-overlapping ownership and serialize planner handoff, implementer, and test-writer phases; only read-only reviewers may overlap. Codex implementers are not promised Claude worktree isolation.
You are in Maestro orchestration mode. Delegate immediately.
Workflow
- Clarify - A refactor's target shape is rarely fixed by the request. Before exploring, run clarifying rounds through the host's question tool until no fork is left: target shape, what must not change, and what "done" looks like; recommendation first on each
- Explore - Spawn
exploreagent to analyze current code - Plan - Spawn
planneragent to design refactoring approach - Implement - Spawn
implementeragent to refactor - Test - Spawn
testeragent to verify behavior unchanged - Review - Spawn
revieweragent to check quality - Learn - Store patterns discovered during refactoring
Agent Delegation
Spawn explore and planner first — they accept thin prompts because they discover what they need from the codebase:
Agent(explore, "Analyze the code to refactor: $ARGUMENTS. Identify patterns, issues, dependencies.")
Agent(planner, "Design refactoring approach based on analysis. Keep behavior unchanged.")
Claude: then assemble the implementer prompt from the actual planner output. The Claude implementer runs in an isolated worktree with no access to prior agent results, so paste the real plan — not "according to plan":
- The user's refactor target (
$ARGUMENTS) verbatim - The planner's step-by-step plan, including file paths and each move/rename/extract operation
- Any "preserve behavior" invariants the planner called out
- The test command that must remain green
- Scope: "only the files in the plan; do not touch anything else"
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 14d ago Changed · -8 lines f571daeedfad
- 28d ago Changed 720fb468e7b0
- 1mo ago Changed cf97fc5ff198
- 1mo ago Changed · +1 lines 9fab9b070cac
- 1mo ago Changed · +2 tokens per session 444f8c507ff4
- 1mo ago Changed · -3 lines 2eb5c8e6a198
- 2mo ago First seen · 86 lines · 56 tokens per session scan A 0adc29bc60a6
refactor is a skill published in the GitHub repository darkroomengineering/cc-settings (52 stars, last pushed today), licensed MIT. It adds 58 tokens to every session and 782 once invoked, about $0.0002 per session on Opus 5.5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.
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