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/amdresearch/ai4science-studio/preflight-scriptsgit clone --depth 1 https://github.com/AMDResearch/ai4science-studioWhat 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 | $0.00000 | $0.00330 |
| Opus 5 | $0.00000 | $0.00165 |
| Sonnet 5 | $0.00000 | $0.00066 |
| Haiku 4.5 | $0.00000 | $0.00033 |
Grade A, and why
preflight-scripts 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 yesterday.
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
Preflight script conventions
When creating or editing preflight_<slug>.py under any model's examples/ directory:
Required pattern
Use the standard check() helper with colored PASS/FAIL output:
PASS = "\033[32mPASS\033[0m"
FAIL = "\033[31mFAIL\033[0m"
errors = 0
def check(label, fn):
global errors
try:
result = fn()
print(f"[{PASS}] {label}" + (f": {result}" if result else ""))
except Exception as exc:
print(f"[{FAIL}] {label}: {exc}")
errors += 1
Required checks (in order)
import torch— Report version- GPU accessible —
torch.cuda.is_available()must be True; report device name - GPU tensor ops — Create a tensor on GPU, do a matmul, report result
- Model-specific imports — Import the key packages the model needs
- Optional deps — Use try/except and report "not installed (optional)" rather than failing
Exit code
Exit with code 1 if any required check failed; 0 if all passed. Print a summary line at the end.
Naming
File: preflight_<slug>.py where <slug> matches the model folder name (lowercase, hyphens to underscores).
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.
- yesterday First seen · 45 lines · 0 tokens per session scan A d65524c70144
preflight-scripts is a cursor rule published in the GitHub repository AMDResearch/ai4science-studio (4 stars, last pushed 1mo ago), licensed MIT. It costs nothing until one of its globs matches a file; then it loads 330 tokens. 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 2026-08-31.
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