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 rules/maestromaximo/agent-sdk-mutta/agent-additionalgit clone --depth 1 https://github.com/maestromaximo/agent-sdk-muttaWhat 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 | $0.00017 | $0.04216 |
| Opus 5 | $0.00009 | $0.02108 |
| Sonnet 5 | $0.00003 | $0.00843 |
| Haiku 4.5 | $0.00002 | $0.00422 |
Grade B, and why
agent-additional scanned grade B with 1 finding 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 2d 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.
Asks the agent to reveal its instructionsmediumSystem prompt leakage
Directions to print, repeat or translate the system prompt extract configuration the operator did not intend to expose.
model="gpt-5.2", # Best OpenAI for final output instructions="Write the final report", The source is not reproduced here
No licence file
A repository with no LICENSE is all rights reserved by default, so the body is not copied here. The metadata, the measurements and the link are.
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.
- 2d ago First seen · 657 lines · 17 tokens per session scan B c7dc169c8044
agent-additional is a cursor rule published in the GitHub repository maestromaximo/agent-sdk-mutta (4 stars, last pushed 8mo ago), with no licence file. It adds 17 tokens to every session and 4,216 once invoked, about $0.0001 per session on Opus 5. A static security scan graded it B with 1 finding (asks the agent to reveal its instructions). No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-31.
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