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 agentmods add commands/cutepkq/newton/rungit clone --depth 1 https://github.com/CUTEPKQ/NEWTONWrote 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/cutepkq/newton/run)<a href="https://agentmods.dev/commands/cutepkq/newton/run"><img src="https://agentmods.dev/badge/commands/cutepkq/newton/run.svg" alt="Measured on agentmods" 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 | $0.00032 | $0.00734 |
| Opus 5 | $0.00016 | $0.00367 |
| Sonnet 5 | $0.00006 | $0.00147 |
| Haiku 4.5 | $0.00003 | $0.00073 |
Grade A, and why
run 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 4d 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.
You are helping the user run the Newton physics-video generation loop. Follow each step below.
Step 1 — Pre-flight checks
Verify the environment is ready:
- Check that
.envexists in the project root. If not, tell the user to run/setupfirst. - Scan
.envfor placeholder values (lines still containing<your-). Warn if any required keys are missing:PLANNER_API_KEYandPLANNER_BASE_URL— requiredSEEDANCE_API_KEYandSEEDANCE_HOST— required- Others are optional but enable more tools (tell the user which tools will be unavailable).
- Check that the
newtonconda environment is active. If not, activate it.
Step 2 — Scenario input
Ask the user: "What physics scenario do you want to generate?"
Encourage them to describe a concrete physical interaction — objects, materials, and what happens. Give a few examples to inspire them:
- "A glass marble rolls down a wooden ramp and launches off the end"
- "A water balloon drops onto a table and bursts"
- "A pendulum swings and knocks over a row of dominoes"
Once they provide a description, help refine it if needed — the prompt should be specific about:
- Object types and materials
- Initial positions and motions
- The key physical interaction (collision, deformation, fluid flow, etc.)
- Expected outcome
Confirm the final scenario text with the user before proceeding.
Step 3 — Configure run options
Ask the user if they want to adjust any settings, or use defaults:
| Flag | Default | Description |
|---|---|---|
--max-turns |
8 | Maximum planner/executer/verifier rounds |
--duration |
5 | Generated video length in seconds |
--out-dir |
outputs/loop |
Output directory |
--baseline |
(none) | Path to an existing baseline mp4 to skip baseline generation |
Most users should use the defaults. Only ask about these options once — don't repeat.
Step 4 — Run the loop
Execute the inference loop:
python loop/run_loop.py "<scenario>" --max-turns <N> --duration <D> --out-dir <dir>
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.
- 4d ago First seen · 76 lines · 32 tokens per session scan A 2e907793da36
run is a command published in the GitHub repository CUTEPKQ/NEWTON (143 stars, last pushed 1mo ago), licensed MIT. It adds 32 tokens to every session and 734 once invoked, about $0.0002 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.
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