Getting it into your agent
It runs from inside its repository, so the clone comes first — what it calls does not travel with the file alone.
git clone --depth 1 https://github.com/NVIDIA-NeMo/Megatron-Bridgenpx agentmods add skills/nvidia-nemo/megatron-bridge/testingWrote 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/nvidia-nemo/megatron-bridge/testing)<a href="https://agentmods.dev/skills/nvidia-nemo/megatron-bridge/testing"><img src="https://agentmods.dev/badge/skills/nvidia-nemo/megatron-bridge/testing/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/nvidia-nemo/megatron-bridge/testing"><img src="https://agentmods.dev/badge/skills/nvidia-nemo/megatron-bridge/testing.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector warn
SkillSpector: 1 finding, up to medium
These are SkillSpector’s own severities. On a checked sample its high-severity flags on skills were ~96% false positives — a documented command, a public API, a “never do X” rule — so we show them as a caution to read, not a verdict. Why →
- medium MCP Rug Pull · line 65 Docker image references without a specific tag (:latest is implicit) or digest (@sha256:...) can be silently replaced by a malicious image.Fix: Pin the image: image:tag or image@sha256:abc123
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 | $0.00045 | $0.01544 |
| Opus 5.5 | $0.00018 | $0.00618 |
| Sonnet 5.5 | $0.00009 | $0.00309 |
| Haiku 4.5 | $0.00005 | $0.00154 |
Grade A, and why
testing 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.
How it starts
The opening of the file, as written. The whole thing — 159 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Testing
Directory Layout
tests/
unit_tests/ # fast, isolated, no GPU required
functional_tests/
launch_scripts/
h100/
active/ # H100 tests that run in CI automatically
flaky/ # H100 tests quarantined from blocking CI
gb200/
active/ # GB200 tests that run in CI automatically
flaky/ # GB200 tests quarantined from blocking CI
Unit tests are independent of the launch script layout. Functional test
scripts are named {Tier}_{Description}.sh (e.g., L0_Launch_training.sh).
Tier Semantics
| Tier | Trigger | Blocking |
|---|---|---|
| L0 | Every PR, every push to main, schedule |
Yes — PR cannot merge if L0 fails |
| L1 | Push to main, schedule, PRs with needs-more-tests label |
Yes |
| L2 | Schedule, workflow_dispatch, PRs with full-test-suite label |
Yes (when triggered) |
| flaky | workflow_dispatch with test_suite=all only |
No — failures are informational |
H100 and GB200 each have independent L0/L1/L2/flaky jobs. Moving a script to
flaky/ removes it from blocking CI on that hardware target only.
Tier assignment criteria
Reserve L0 for high-risk shared paths and the smallest current set of
representative first-tier gates. L1 holds secondary but still broadly useful
coverage that runs on main, on schedules, and for opt-in PRs through the
established needs-more-tests label. Place legacy, redundant, niche,
specialized, or expensive model-family coverage in L2. Popularity alone does
not determine a test's tier; weigh risk, representativeness, cost, and overlap
with existing coverage.
Prefer unit tests over functional tests. CI GPU resources are limited; every functional test slot has a real cost.
Running Tests Locally
Unit Tests
No GPU required:
uv run pytest tests/unit_tests/ -x -v
Or inside Docker:
docker run --rm --gpus all -v $(pwd):/workdir/ -w /workdir/ megatron-bridge \
uv run pytest tests/unit_tests/
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 · 159 lines · 45 tokens per session scan A 5c2155982b6c
testing is a skill published in the GitHub repository NVIDIA-NeMo/Megatron-Bridge (970 stars, last pushed today), licensed Apache-2.0. It adds 45 tokens to every session and 1,544 once invoked, about $0.0002 per session on Opus 5.5. 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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