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/JansenAnalytics/claudexnpx agentmods add skills/jansenanalytics/claudex/data-pipelineWrote 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/jansenanalytics/claudex/data-pipeline)<a href="https://agentmods.dev/skills/jansenanalytics/claudex/data-pipeline"><img src="https://agentmods.dev/badge/skills/jansenanalytics/claudex/data-pipeline/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/jansenanalytics/claudex/data-pipeline"><img src="https://agentmods.dev/badge/skills/jansenanalytics/claudex/data-pipeline.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 | $0.00030 | $0.00550 |
| Opus 5.5 | $0.00012 | $0.00220 |
| Sonnet 5.5 | $0.00006 | $0.00110 |
| Haiku 4.5 | $0.00003 | $0.00055 |
Grade A, and why
data-pipeline 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.
How it starts
The opening of the file, as written. The whole thing — 60 lines — stays where its author put it; the contents beside it link to each section on GitHub.
data-pipeline
ETL and data transformation: CSV, JSON, Parquet, NDJSON processing with filtering, mapping, joining, aggregating.
When to Use
- Converting between data formats (CSV ↔ JSON, NDJSON, etc.)
- Cleaning or filtering datasets
- Merging/joining files on a common key
- Aggregating data (sum, avg, count, min, max by group)
- Detecting file formats automatically
- Building multi-step data processing pipelines
Scripts
| Script | Purpose | Usage |
|---|---|---|
csv-to-json.py |
Convert CSV → JSON array | python3 csv-to-json.py input.csv [output.json] |
json-to-csv.py |
Convert JSON array → CSV | python3 json-to-csv.py input.json [output.csv] |
data-merge.py |
Join two files on a key | python3 data-merge.py left.csv right.csv --key id [--how inner] |
data-filter.py |
Filter + aggregate data | python3 data-filter.py input.csv --filter "col=val" --agg "col:sum" |
detect-format.py |
Auto-detect file format | python3 detect-format.py file.ext |
All scripts read from stdin if no file argument given. Output goes to stdout by default.
References
references/jq-cheatsheet.md— Common jq patterns for JSON processingreferences/csvkit-patterns.md— csvkit one-linersreferences/large-file-handling.md— Strategies for big datasets
Examples
# Convert CSV to JSON
python3 scripts/csv-to-json.py sales.csv > sales.json
# Filter rows and aggregate
python3 scripts/data-filter.py sales.csv --filter "region=Europe" --agg "revenue:sum,count"
# Merge two CSVs on 'id' column
python3 scripts/data-merge.py users.csv orders.csv --key user_id --how left
# Detect format
python3 scripts/detect-format.py mystery_file.dat
Dependencies
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 · 60 lines · 30 tokens per session scan A f4f6b84c6c38
data-pipeline is a skill published in the GitHub repository JansenAnalytics/claudex (5 stars, last pushed 4mo ago), licensed MIT. It adds 30 tokens to every session and 550 once invoked, about $0.0001 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 2026-08-31.
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