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-mine-nearest-neighborsgit 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-mine-nearest-neighbors)<a href="https://agentmods.dev/skills/nvidia-tao/tao-skill-bank/tao-mine-nearest-neighbors"><img src="https://agentmods.dev/badge/skills/nvidia-tao/tao-skill-bank/tao-mine-nearest-neighbors/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-mine-nearest-neighbors"><img src="https://agentmods.dev/badge/skills/nvidia-tao/tao-skill-bank/tao-mine-nearest-neighbors.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector warn
SkillSpector: 5 findings, up to high
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 →
- high YARA Match · line 30 YARA rule matched a hack tool or exploit indicator (offensive tools, reconnaissance, privilege escalation, or exploit frameworks).Fix: Remove offensive tool references and exploit code. Legitimate agent skills should not contain penetration testing tools, exploit frameworks, or reconnaissance utilities.
- high Privilege Escalation · line 73 Potential security issue detected. Manual review is recommended.Fix: Review the flagged content for security risks. Ensure no credentials, secrets, or sensitive data are exposed.
- high Privilege Escalation · line 82 Code accesses credential files (SSH keys, AWS credentials, etc.). This could indicate credential theft attempts.Fix: Remove references to credential paths. Use environment variables or secrets managers. For docs, use placeholder paths (e.g., /path/to/config). Never load .env or token files in production code paths.
- medium MCP Rug Pull · line 73 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
- medium MCP Rug Pull · line 117 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 | $0.00039 | $0.01490 |
| Opus 5 | $0.00019 | $0.00745 |
| Sonnet 5 | $0.00008 | $0.00298 |
| Haiku 4.5 | $0.00004 | $0.00149 |
Grade A, and why
tao-mine-nearest-neighbors 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 13d 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 — 149 lines — stays where its author put it; the contents beside it link to each section on GitHub.
TAO Mine Nearest Neighbors
Use this skill to run TAO Data Services TMM nearest-neighbor mining. The skill consumes embedding parquets and writes a mined source-sample parquet plus a mining summary. It does not compute embeddings; upstream steps must produce the source and target embedding parquets first.
The container entrypoint is:
tmm nearest_neighbors -e /absolute/path/to/nearest_neighbors.yaml
TAO Data Services requires -e/--experiment_spec_file. The tmm console script converts that YAML into Hydra --config-path and --config-name arguments internally.
Inputs
The user can provide either an existing nearest-neighbors YAML spec or the fields needed to generate one.
Required spec fields:
| Field | Meaning |
|---|---|
source_parquet |
Absolute path to the candidate/source embeddings parquet. |
target_parquet |
Absolute path to the target/query embeddings parquet. |
output_parquet |
Absolute path where TAO Data Services should write mined source filepaths. |
Common optional fields:
| Field | Default | Meaning |
|---|---|---|
topn |
5 |
Number of nearest source samples to retrieve per target sample. |
knn_metric |
cosine |
One of cosine, euclidean, or manhattan. |
source_embed_column_name |
embedding |
Embedding column in source_parquet. |
target_embed_column_name |
embedding |
Embedding column in target_parquet. |
filter_by_label |
"false" |
String flag. When "true", TAO DS filters neighbors by matching label columns when both parquets provide labels. |
distance_threshold |
-1.0 |
Maximum distance to keep. Negative disables thresholding. |
Both input parquets must contain a filepath column and a list-like embedding column. If filter_by_label is "true", both parquets should also contain label.
The default template is assets/default_nearest_neighbors.yaml.
Quick Start
Run from the tao-skill-bank repo root. Resolve the pinned TAO Data Services image from versions.yaml, verify the spec, mount the run root with identical host/container paths, and stream the Docker logs.
What ships with it
5 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.
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.
- 13d ago First seen · 149 lines · 39 tokens per session scan A 7d3617a5d687
tao-mine-nearest-neighbors is a skill published in the GitHub repository NVIDIA-TAO/tao-skill-bank (88 stars, last pushed today), licensed Apache-2.0. It adds 39 tokens to every session and 1,490 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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