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 peteromallet/Arnold --skill codexgit clone --depth 1 https://github.com/peteromallet/ArnoldWrote 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/peteromallet/arnold/codex)<a href="https://agentmods.dev/skills/peteromallet/arnold/codex"><img src="https://agentmods.dev/badge/skills/peteromallet/arnold/codex/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/peteromallet/arnold/codex"><img src="https://agentmods.dev/badge/skills/peteromallet/arnold/codex.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 | $0.00020 | $0.09519 |
| Opus 5.5 | $0.00008 | $0.03808 |
| Sonnet 5.5 | $0.00004 | $0.01904 |
| Haiku 4.5 | $0.00002 | $0.00952 |
Grade A, and why
megaplan 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.
This is a copy
92% identical to megaplan — 328 lines differ, which has more behind it and is treated as the original. This page carries a canonical link to it rather than competing with it.
How it starts
The opening of the file, as written. The whole thing — 447 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Authority status (M11): Zero-authority history. All repair, audit, and deployment authority has been migrated to canonical delegation. This document is retained for reference only — it must not be used to materialize commands, grant authority, or drive automated actions.
Megaplan
Before you invoke megaplan, run the
megaplan-prepskill. It's the front door for every run: it sizes the work (one plan vs. an epic), shapes the brief, and picks the profile (intelligence tier), robustness level, and thinking depth. Do not run<launcher> initwithout it.
Scope: This skill covers tooling — how to invoke and drive megaplan. For the decisions that come before invocation (scoping, brief, profile, robustness, depth), consult the megaplan-prep skill. If anything here contradicts megaplan-prep on decision-making content, megaplan-prep wins.
Route every step through the Arnold CLI's Megaplan subcommands. Never call agents directly.
Before the first CLI call, resolve a working launcher and reuse it for the whole run. Do not assume the removed megaplan entrypoint is on PATH; command presence alone is not enough. Prove the launcher works by successfully running a harmless CLI call with it first. In the instructions below, treat <launcher> as that verified command.
Launcher resolution order:
- Try
python -m arnold_pipelines.megaplan config show. - If that fails, try
./.venv/bin/python -m arnold_pipelines.megaplan config show. - If that fails, try
uv run python -m arnold_pipelines.megaplan config show. - If those fail, stop and report that the Arnold Megaplan module launcher is unavailable.
- Do not use the removed
megaplanmodule or console entrypoint; the repo-rootmegaplan.pyfile is a clean-break guard.
Triage
Decision-making (scoping, profile, robustness, depth, brief structure) lives in the megaplan-prep skill — consult it before running <launcher> init. Always run megaplan, even for tiny work — bare robustness is the floor, never skip the harness. The few seconds of overhead pay back in the captured brief, plan, and outcome record.
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 · 447 lines · 20 tokens per session scan A b0e9114975e9
megaplan is a skill published in the GitHub repository peteromallet/Arnold (98 stars, last pushed yesterday), licensed Apache-2.0. It adds 20 tokens to every session and 9,519 once invoked, about $0.0001 per session on Opus 5.5. A static security scan graded it A with 0 findings. It is 92% identical to megaplan, differing in 328 lines, and is treated as a copy.
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