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 NVIDIA-TAO/tao-skill-bank --skill tao-run-deft-od-aoigit clone --depth 1 https://github.com/NVIDIA-TAO/tao-skill-bankWrote 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-tao/tao-skill-bank/tao-run-deft-od-aoi)<a href="https://agentmods.dev/skills/nvidia-tao/tao-skill-bank/tao-run-deft-od-aoi"><img src="https://agentmods.dev/badge/skills/nvidia-tao/tao-skill-bank/tao-run-deft-od-aoi/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-tao/tao-skill-bank/tao-run-deft-od-aoi"><img src="https://agentmods.dev/badge/skills/nvidia-tao/tao-skill-bank/tao-run-deft-od-aoi.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 | $0.00081 | $0.04042 |
| Opus 5.5 | $0.00032 | $0.01617 |
| Sonnet 5.5 | $0.00016 | $0.00808 |
| Haiku 4.5 | $0.00008 | $0.00404 |
Grade A, and why
tao-run-deft-od-aoi 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 15d 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 — 362 lines — stays where its author put it; the contents beside it link to each section on GitHub.
TAO DEFT OD AOI
Standalone install? If this session was not initialized by the TAO skill bank plugin, run the
tao-setupskill first (host preflight, credentials, cross-skill discovery).
This application is a disk-backed RT-DETR loop for one foreground class,
defect. Its core is real-data-only; AnomalyGenNext synthesis is an optional
route with separate preparation, generation, and admission gates.
References
Read only the references needed for the current stage:
- intake and launch:
references/defaults.md,references/data-contract.md,references/source-manifest.md, andreferences/preflight.md; - orchestration:
references/pipeline.mdandreferences/scripts-and-agents.md; - gaps and retrieval:
references/gap-routing.mdandreferences/tao-analyze-gaps-od-map.md; - training and selection:
references/training-policy.md; - optional synthesis:
references/anomalygen-pool.md.
Start
Select an installed platform, read its skill, then invoke
tao-launch-workflow. The single launch review must include the four normalized
COCO roles, trainable RT-DETR base checkpoint, maximum iterations, image and
Data Services containers, GPU shape, and expected runtime. After approval,
prepare source COCO files when needed:
scripts/prepare_deft_od_aoi_sources.py \
--manifest /data/dataset_sources.json --check-only
scripts/prepare_deft_od_aoi_sources.py \
--manifest /data/dataset_sources.json \
--output-dir /new/results/normalized
--check-only runs without a container. Materialization must run in the pinned
TAO Data Services image because it delegates each role's canonical COCO merge
to the existing annotations merge action. The application then validates the
merged role contracts before emitting sources.json. Include --gpus when
launching the materialization container, as documented in
references/source-manifest.md.
The user-facing manifest calls the held-out input benchmark. The second
command maps it to the existing internal kpi role and emits sources.json
with the canonical kpi, test, real, and clean mapping. Copy
assets/default_policy.yaml, use that mapping for sources, fill the other
required values, and initialize once:
What ships with it
42 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
- assets/default_policy.yaml 2.4 KB
- evals/evals.json 691 B
- references/anomalygen-pool.md 6.9 KB
- references/data-contract.md 6.7 KB
- references/defaults.md 2.9 KB
- references/gap-routing.md 7.1 KB
- references/pipeline.md 8.9 KB
- references/preflight.md 2.5 KB
- references/scripts-and-agents.md 2.3 KB
- references/source-manifest.md 5.0 KB
- references/tao-analyze-gaps-od-map.md 1.2 KB
- references/training-policy.md 2.8 KB
- scripts/admit_deft_od_aoi_coco.py 27 KB runs code
- scripts/commit_deft_od_aoi_stage.py 29 KB runs code
- scripts/deft_od_aoi_round_robin_admission.py 9.2 KB runs code
- scripts/deft_od_aoi_round_robin_contract.py 656 B runs code
- scripts/deft_od_aoi_round_robin_selection.py 18 KB runs code
- scripts/deft_od_aoi_synthesis_contract.py 2.7 KB runs code
- scripts/init_deft_od_aoi.py 18 KB runs code
- scripts/prepare_deft_od_aoi_measurement.py 8.5 KB runs code
- scripts/prepare_deft_od_aoi_retrieval.py 32 KB runs code
- scripts/prepare_deft_od_aoi_sources.py 15 KB runs code
- scripts/prepare_deft_od_aoi_synthesis.py 17 KB runs code
- scripts/prepare_deft_od_aoi_training.py 7.1 KB runs code
- scripts/resolve_deft_od_aoi_synthesis.py 4.6 KB runs code
- scripts/select_deft_od_aoi_training.py 9.1 KB runs code
- scripts/tests/fixtures/round_robin_similarity_reference.json 1.1 KB
- scripts/tests/test_admit_deft_od_aoi_coco.py 38 KB runs code
- scripts/tests/test_combined_synthesis_capacity.py 4.8 KB runs code
- scripts/tests/test_commit_deft_od_aoi_stage.py 28 KB runs code
- scripts/tests/test_deft_od_aoi_round_robin_admission.py 5.1 KB runs code
- scripts/tests/test_deft_od_aoi_round_robin_selection.py 23 KB runs code
- scripts/tests/test_init_deft_od_aoi.py 29 KB runs code
- scripts/tests/test_prepare_deft_od_aoi_measurement.py 6.1 KB runs code
- scripts/tests/test_prepare_deft_od_aoi_retrieval.py 45 KB runs code
- scripts/tests/test_prepare_deft_od_aoi_sources.py 13 KB runs code
- scripts/tests/test_prepare_deft_od_aoi_synthesis.py 22 KB runs code
- scripts/tests/test_prepare_deft_od_aoi_training.py 3.2 KB runs code
- scripts/tests/test_resolve_deft_od_aoi_synthesis.py 2.7 KB runs code
- scripts/tests/test_select_deft_od_aoi_training.py 5.5 KB runs code
- scripts/tests/test_synthetic_capacity_gate.py 7.4 KB runs code
- skill-card.md 2.2 KB
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.
- 15d ago Changed · +2 lines b24a19b5ee80
- 19d ago Changed · +5 lines d74dcbe14c06
- 21d ago Changed · +35 lines 2306a9d3c313
- 22d ago Changed · +29 lines 45679ceb134e
- 24d ago Changed · +36 lines b6c1c47dfd6b
- 1mo ago Changed · +12 lines 638db71b310b
- 1mo ago Changed · +21 lines 4d5b19262bb5
- 1mo ago Changed · +2 lines ad8ae7601ece
- 1mo ago Changed · +137 lines e03be2509d9c
- 1mo ago First seen · 83 lines · 81 tokens per session scan A d4fb6286350a
tao-run-deft-od-aoi is a skill published in the GitHub repository NVIDIA-TAO/tao-skill-bank (97 stars, last pushed 5d ago), licensed Apache-2.0. It adds 81 tokens to every session and 4,042 once invoked, about $0.0003 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 2026-09-10.
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