Getting it into your agent
This one installs as part of its plugin. Adding the marketplace and installing the plugin brings it with everything else the plugin ships.
/plugin marketplace add imgompanda/fireauto/plugin install fireautoWrote 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/commands/imgompanda/fireauto/loop)<a href="https://agentmods.dev/commands/imgompanda/fireauto/loop"><img src="https://agentmods.dev/badge/commands/imgompanda/fireauto/loop/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/commands/imgompanda/fireauto/loop"><img src="https://agentmods.dev/badge/commands/imgompanda/fireauto/loop.svg" alt="Reviewed on agentmods" width="80" height="20"></a>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 | $0.00023 | $0.00589 |
| Opus 5.5 | $0.00009 | $0.00236 |
| Sonnet 5.5 | $0.00005 | $0.00118 |
| Haiku 4.5 | $0.00002 | $0.00059 |
Grade A, and why
loop 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 1mo 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.
What it actually says
fireauto loop
사용자가 자연어로 작성한 요청에서 루프 설정을 추출하세요.
1단계: 자연어 파싱
사용자의 $ARGUMENTS를 분석해서 3가지를 추출하세요:
- 할 일 (필수): 실제 작업 내용
- 최대 반복 횟수: 숫자가 있으면 추출, 없으면 0 (무제한)
- 완료 조건: 완료/목표/조건에 해당하는 부분, 없으면 null
파싱 예시
| 입력 | 할 일 | 최대 횟수 | 완료 조건 |
|---|---|---|---|
| "최대 20번 반복해서 TODO API 만들어줘 테스트 통과하면 끝" | TODO API 만들어줘 | 20 | 테스트 통과 |
| "인증 버그 고쳐줘 10번까지" | 인증 버그 고쳐줘 | 10 | null |
| "캐시 레이어 리팩토링" | 캐시 레이어 리팩토링 | 0 | null |
| "5번 반복하면서 UI 개선해줘 목표는 반응형 완성" | UI 개선해줘 | 5 | 반응형 완성 |
기존 형식(--max-iterations 20 --completion-promise '조건')도 호환해야 합니다.
2단계: 셋업 스크립트 실행
추출한 값으로 셋업 스크립트를 실행하세요:
"${CLAUDE_PLUGIN_ROOT}/scripts/setup-loop.sh" {할 일} --max-iterations {횟수} --completion-promise '{완료 조건}'
- 최대 횟수가 0이면
--max-iterations생략 - 완료 조건이 null이면
--completion-promise생략
3단계: 작업 시작
이제 작업을 시작하세요. 작업을 끝내고 나가려고 하면, 같은 프롬프트가 다시 들어와요. 이전 작업 결과는 파일과 git 히스토리에 남아있으니, 매번 더 나은 결과를 만들 수 있어요.
중요 규칙: completion-promise가 설정되어 있으면, 그 조건이 진짜로 완전히 달성되었을 때만 <promise>완료조건</promise>을 출력하세요. 루프를 탈출하기 위해 거짓말하지 마세요.
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.
- 1mo ago First seen · 48 lines · 23 tokens per session scan A 77a3e2f97961
loop is a command published in the GitHub repository imgompanda/fireauto (140 stars, last pushed 6mo ago), licensed MIT. It adds 23 tokens to every session and 589 once invoked, about $0.0001 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.
Other commands, from other repositories
land
Resolve and squash merge one named, currently authorized pull request.
analyze-context
USE WHEN you want to analyze project context before starting work on a task. Calls context + recall, then synthesizes goals, decisions, gotchas, and relevant memories into a pre-task brief.
incident
Live incident response — intake a Sentry issue, stack trace, or symptom; gate mitigate-first vs root-cause-first; keep a UTC timeline. Use when production is broken RIGHT NOW; for the after-action write-up alone, use /orc:postmortem.
me-cfd-review
Review thermal-fluid CFD setup, boundary conditions, mesh, wall treatment, convergence, validation, and whether the claims are supported.
me-figure-discussion
Write or review thermal-fluid figure discussion with observation, physical mechanism, comparison, uncertainty, and claim limits.
bug-check
Run automated tests and build checks first, then agent code review. For each bug found, propose or document a regression test.