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 oracle-samples/oracle-aidp-samples --skill aidp-azure-adlsgit clone --depth 1 https://github.com/oracle-samples/oracle-aidp-samplesWrote 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/oracle-samples/oracle-aidp-samples/aidp-azure-adls)<a href="https://agentmods.dev/skills/oracle-samples/oracle-aidp-samples/aidp-azure-adls"><img src="https://agentmods.dev/badge/skills/oracle-samples/oracle-aidp-samples/aidp-azure-adls/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/oracle-samples/oracle-aidp-samples/aidp-azure-adls"><img src="https://agentmods.dev/badge/skills/oracle-samples/oracle-aidp-samples/aidp-azure-adls.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 | $0.00072 | $0.00894 |
| Opus 5 | $0.00036 | $0.00447 |
| Sonnet 5 | $0.00014 | $0.00179 |
| Haiku 4.5 | $0.00007 | $0.00089 |
Grade A, and why
aidp-azure-adls 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 7d 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.
The source is not reproduced here
Licensed UPL-1.0
The repository is licensed UPL-1.0, which this catalogue does not treat as permission to reproduce the file. Read it at the source.
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.
- 7d ago First seen · 73 lines · 72 tokens per session scan A 4e25d082d110
aidp-azure-adls is a skill published in the GitHub repository oracle-samples/oracle-aidp-samples (46 stars, last pushed yesterday), licensed UPL-1.0. It adds 72 tokens to every session and 894 once invoked, about $0.0004 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 2026-09-03.
Other skills, from other repositories
ray-data
Scalable data processing for ML workloads. Streaming execution across CPU/GPU, supports Parquet/CSV/JSON/images. Integrates with Ray Train, PyTorch, TensorFlow. Scales from single machine to 100s of nodes. Use for batch inference, data preprocessing, multi-modal data loading, or distributed ETL pipelines.
spark-serverless-reliability-and-state-management
Enforces timeout-aware rollbacks, resumable checkpoints, and orphan cleanup for serverless Spark workloads on AWS Lambda, Glue, and similar runtimes. Use when writing or reviewing Spark jobs in serverless environments, S3 checkpoint patterns, partial-failure recovery, or IceGuard-style state management.
ds-deploy
Stands a packaged model up as a callable endpoint with prediction logging against the live baseline, drift detection, and a rollback pointer. Hard gate — refuses full traffic without all three, and stops before any remote or cloud push. Use when someone asks to serve, deploy, or stand up a model endpoint. Use when…
alterlab-modal
Runs Python code in the cloud with Modal — serverless containers, on-demand GPUs, and autoscaling. Use when deploying ML models, running batch processing jobs, scheduling compute-intensive tasks, or serving APIs that need GPU acceleration or dynamic scaling. Part of the AlterLab Academic Skills suite.
r-parallel-distributed
R distributed computing with sparklyr, future.batchtools. Use for cluster and cloud computing.
cloud-infra-data
AWS/GCP/Azure data infrastructure — S3/GCS/ADLS partitioning, BigQuery slot management, Redshift spectrum, Snowflake warehouses, IAM roles for data access, cost optimization, and managed service selection. Use this skill whenever the user is deploying a pipeline to cloud, choosing between managed data services…