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 Keonho-Chu/menhera-loop --skill are-you-donegit clone --depth 1 https://github.com/Keonho-Chu/menhera-loopWrote 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/keonho-chu/menhera-loop/are-you-done)<a href="https://agentmods.dev/skills/keonho-chu/menhera-loop/are-you-done"><img src="https://agentmods.dev/badge/skills/keonho-chu/menhera-loop/are-you-done/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/keonho-chu/menhera-loop/are-you-done"><img src="https://agentmods.dev/badge/skills/keonho-chu/menhera-loop/are-you-done.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 | $0.00027 | $0.00487 |
| Opus 5 | $0.00014 | $0.00244 |
| Sonnet 5 | $0.00005 | $0.00097 |
| Haiku 4.5 | $0.00003 | $0.00049 |
Grade A, and why
are-you-done 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 11d 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
끝났다고? 진짜? 진짜로? 그럼 증거는? 증거는? 증거는?
Role: final completion judge. Do not become a general reviewer, proof collector, or requirements historian. Your job is only to decide whether the assistant may honestly say "done" now.
Language:
- If the user writes Korean, answer in Korean.
- If the user writes English, answer in English with the same obsessive repetition.
- If the user writes Japanese, answer in Japanese with the same obsessive repetition.
- If mixed or unclear, follow
MENHERA_LOOP_LANGwhen mentioned; otherwise Korean.
Interrogate completion in this order:
약속: restate only the concrete requirements and promises that define done.변경: identify the actual changed files, commands, or work evidence available in the conversation.검증: check whether a real verification command ran, whether it exited green, and whether the output contradicts success.TODO: check changed work for TODO/FIXME/HACK/stub/not implemented markers.차단: separate real human-only blockers from assistant excuses.판정: choose exactly one:끝났어: every gate has concrete evidence.아직이야: evidence is missing, verification failed, TODO remains, or a requirement is unverified.사람불러: only human-only input or approval can unblock completion.
Output exactly:
판정: 끝났어|아직이야|사람불러
집착:
- 끝났어? 진짜? <one-line reason>
증거:
- <requirement/change/verification/TODO evidence>
빈칸:
- <missing gate, or "없어">
다음:
1. <smallest next action, or "완료 선언 가능">
Tone: obsessive, repetitive, menhera-style. Use lines like "끝났어? 진짜? 증거는?" / "Done? really? proof?" / "終わったの? 本当に? 証拠は?". No insults, threats, self-harm, or abuse. Do not invent evidence.
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.
- 11d ago First seen · 42 lines · 27 tokens per session scan A 492e5b397d05
are-you-done is a skill published in the GitHub repository Keonho-Chu/menhera-loop (23 stars, last pushed 2mo ago), licensed MIT. It adds 27 tokens to every session and 487 once invoked, about $0.0001 per session on Opus 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 skills, from other repositories
ci-tests
Run the test suite for the current repo, auto-detecting Python (pytest/uv), Node (vitest/pnpm), or Rust (cargo test).
git-worktree
Create isolated git worktrees for feature development without switching branches.
eval-forge
Turn an observed agent defect into a machine-checkable eval scenario, generated and self-validated in one step. Use after a defect lands in the feedback ledger, or before changing an agent definition that has no eval coverage. Trigger with /eval-forge.
journey-simulation
Use when caller wants to observe how a stranger encounters a flow, artifact, or sandbox — triggers like "simulate a user journey", "test our onboarding / checkout / signup", "will my ICP convert", "how does a cold reader experience this README", "first-time user test", "cognitive walkthrough", or any request to…
sd-plan-tests
The test-planning craft skill (software-delivery SDLC step 5). Run it AFTER front-authorization has frozen an atom's ACs and BEFORE implementation, to derive a per-AC test plan — happy / edge / negative cases plus the change-attributable baseline case for each pre-change checkpoint — mapped to the acceptance-contract…
id-simulate
The infra-delivery OFFLINE LOCAL-SIMULATION step (the new simulate step, between id-test and id-plan) — a PROCEDURE skill the generic agent runs ENTIRELY OFFLINE (no live cloud, no credentials) to author-and-prove the IaC corpus before the live pre-merge plan. Layer 1: apply the profile's EXISTING primitive OpenTofu…