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/Raidriar7170/hermes-skillevalnpx agentmods add skills/raidriar7170/hermes-skilleval/skillsbench__senior-data-scientistWrote 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/raidriar7170/hermes-skilleval/skillsbench__senior-data-scientist)<a href="https://agentmods.dev/skills/raidriar7170/hermes-skilleval/skillsbench__senior-data-scientist"><img src="https://agentmods.dev/badge/skills/raidriar7170/hermes-skilleval/skillsbench__senior-data-scientist/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/raidriar7170/hermes-skilleval/skillsbench__senior-data-scientist"><img src="https://agentmods.dev/badge/skills/raidriar7170/hermes-skilleval/skillsbench__senior-data-scientist.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 | $0.00091 | $0.01213 |
| Opus 5.5 | $0.00036 | $0.00485 |
| Sonnet 5.5 | $0.00018 | $0.00243 |
| Haiku 4.5 | $0.00009 | $0.00121 |
Grade A, and why
senior-data-scientist 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.
This is a copy
89% identical to senior-computer-vision — 34 lines differ, which has more behind it and is treated as the original. This page carries a canonical link to it rather than competing with it.
How it starts
The opening of the file, as written. The whole thing — 227 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Senior Data Scientist
World-class senior data scientist skill for production-grade AI/ML/Data systems.
Quick Start
Main Capabilities
# Core Tool 1
python scripts/experiment_designer.py --input data/ --output results/
# Core Tool 2
python scripts/feature_engineering_pipeline.py --target project/ --analyze
# Core Tool 3
python scripts/model_evaluation_suite.py --config config.yaml --deploy
Core Expertise
This skill covers world-class capabilities in:
- Advanced production patterns and architectures
- Scalable system design and implementation
- Performance optimization at scale
- MLOps and DataOps best practices
- Real-time processing and inference
- Distributed computing frameworks
- Model deployment and monitoring
- Security and compliance
- Cost optimization
- Team leadership and mentoring
Tech Stack
Languages: Python, SQL, R, Scala, Go ML Frameworks: PyTorch, TensorFlow, Scikit-learn, XGBoost Data Tools: Spark, Airflow, dbt, Kafka, Databricks LLM Frameworks: LangChain, LlamaIndex, DSPy Deployment: Docker, Kubernetes, AWS/GCP/Azure Monitoring: MLflow, Weights & Biases, Prometheus Databases: PostgreSQL, BigQuery, Snowflake, Pinecone
Reference Documentation
1. Statistical Methods Advanced
Comprehensive guide available in references/statistical_methods_advanced.md covering:
- Advanced patterns and best practices
- Production implementation strategies
- Performance optimization techniques
- Scalability considerations
- Security and compliance
- Real-world case studies
2. Experiment Design Frameworks
Complete workflow documentation in references/experiment_design_frameworks.md including:
- Step-by-step processes
- Architecture design patterns
- Tool integration guides
- Performance tuning strategies
- Troubleshooting procedures
3. Feature Engineering Patterns
Technical reference guide in references/feature_engineering_patterns.md with:
- System design principles
- Implementation examples
- Configuration best practices
- Deployment strategies
- Monitoring and observability
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 · 227 lines · 91 tokens per session scan A 7dbd76b05973
senior-data-scientist is a skill published in the GitHub repository Raidriar7170/hermes-skilleval (29 stars, last pushed 1mo ago), licensed MIT. It adds 91 tokens to every session and 1,213 once invoked, about $0.0004 per session on Opus 5.5. A static security scan graded it A with 0 findings. It is 89% identical to senior-computer-vision, differing in 34 lines, and is treated as a copy.
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