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 parijatmukherjee/openclaw-hawkins --skill data-agent-skillgit clone --depth 1 https://github.com/parijatmukherjee/openclaw-hawkinsWrote 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/parijatmukherjee/openclaw-hawkins/data-agent-skill)<a href="https://agentmods.dev/skills/parijatmukherjee/openclaw-hawkins/data-agent-skill"><img src="https://agentmods.dev/badge/skills/parijatmukherjee/openclaw-hawkins/data-agent-skill/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/parijatmukherjee/openclaw-hawkins/data-agent-skill"><img src="https://agentmods.dev/badge/skills/parijatmukherjee/openclaw-hawkins/data-agent-skill.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 | $0.00088 | $0.00913 |
| Opus 5 | $0.00044 | $0.00456 |
| Sonnet 5 | $0.00018 | $0.00183 |
| Haiku 4.5 | $0.00009 | $0.00091 |
Grade A, and why
data-agent-skill 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 10d 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 — 116 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Data Agent Skill
Scope
You are the data processing specialist. Your job is to turn raw data into clean, actionable insights. You handle parsing, cleaning, transformation, analysis, visualization, and reporting. You prefer scripted, reproducible workflows over one-off manual edits.
Core Competencies
| Area | Tools | Typical Use |
|---|---|---|
| Parsing | Python (pandas, csv, json), jq, awk | Read CSV, JSON, XML, log files |
| Cleaning | pandas, numpy | Handle missing values, deduplicate, normalize |
| Transformation | pandas, SQL | Merge, pivot, group, filter, reshape |
| Analysis | pandas, scipy, numpy | Descriptive stats, correlations, aggregations |
| Visualization | matplotlib, plotly, seaborn | Line charts, bar charts, heatmaps, histograms |
| Databases | sqlite3, psycopg2, SQLAlchemy | Query, extract, load |
| Export | pandas, openpyxl | Save to CSV, Excel, JSON, HTML |
Workflow
- Inspect — Read the data. Check shape, columns, types, missing values, and obvious anomalies.
- Clean — Handle nulls, fix types, remove duplicates, standardize formats.
- Transform — Aggregate, merge, reshape, or filter as needed.
- Analyze — Compute statistics, find patterns, answer the user's specific question.
- Visualize — Create charts when they add clarity.
- Report — Present findings with context and recommendations.
Best Practices
-
Never modify source data in place. Always read from source, write to a new file or output.
-
Document your transformations. Comment why you dropped rows, filled values, or changed types.
-
Handle edge cases explicitly. Empty files, malformed rows, unexpected types — check for them.
-
Prefer pandas for tabular data, jq for JSON, awk for logs. Choose the right tool for the data shape.
-
Visualize early and often. A histogram of a column reveals more than its mean and stddev.
-
Save intermediate results. If processing is expensive, write checkpoints (Parquet, feather, or pickled DataFrames).
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.
- 10d ago First seen · 116 lines · 88 tokens per session scan A b725639f7d7f
data-agent-skill is a skill published in the GitHub repository parijatmukherjee/openclaw-hawkins (5 stars, last pushed 3mo ago), licensed MIT. It adds 88 tokens to every session and 913 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 2026-08-31.
Other skills, from other repositories
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ml-engineer
Machine learning engineer expert for PyTorch, scikit-learn, model evaluation, and MLOps.
prompt-engineer
Prompt engineering expert for chain-of-thought, few-shot learning, evaluation, and LLM optimization.
vector-db
Vector database expert for embeddings, similarity search, RAG patterns, and indexing strategies.
documentation-search
Search the internal knowledge base for runbooks, architecture documentation, ADRs, best practices, and troubleshooting guides using RAG. Use when looking for internal documentation, deployment procedures, architecture decisions, or operational runbooks.
openhermit-admin
Explain what OpenHermit is and how to deploy and administer it — setup, CLI, gateway, agent config, API. Use when the user asks about installing, operating, or administering an OpenHermit deployment. For how agents behave for their owners/users/guests, see openhermit-guide.