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 agentmods add skills/wentorai/research-plugins/wranglingnpx skills add wentorai/research-plugins --skill wranglinggit clone --depth 1 https://github.com/wentorai/research-pluginsWrote 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/wentorai/research-plugins/wrangling)<a href="https://agentmods.dev/skills/wentorai/research-plugins/wrangling"><img src="https://agentmods.dev/badge/skills/wentorai/research-plugins/wrangling.svg" alt="Measured on agentmods" 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 | $0.00041 | $0.00390 |
| Opus 5 | $0.00020 | $0.00195 |
| Sonnet 5 | $0.00008 | $0.00078 |
| Haiku 4.5 | $0.00004 | $0.00039 |
Grade A, and why
wrangling-skills 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 4d 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.
What it actually says
Data Wrangling — 10 Skills
Select the skill matching the user's need, then read its SKILL.md.
| Skill | Description |
|---|---|
| csv-data-analyzer | Load, explore, clean, and analyze CSV data with statistical summaries |
| data-cleaning-pipeline | Systematic data cleaning workflows for research datasets |
| data-cog-guide | Upload messy CSVs with minimal prompting for deep automated analysis |
| missing-data-handling | Diagnose missing data patterns and apply appropriate imputation strategies |
| pandas-data-wrangling | Data cleaning, transformation, and exploratory analysis with pandas |
| questionnaire-design-guide | Questionnaire and survey design with Likert scales and coding |
| stata-data-cleaning | Clean, transform, and validate messy research data using Stata |
| streamline-analyst-guide | End-to-end data analysis AI agent with Streamlit UI |
| survey-data-processing | Clean, recode, and prepare survey response data for analysis |
| text-mining-guide | Apply NLP and text mining techniques to research text data |
What ships with it
10 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.
- csv-data-analyzer/SKILL.md 6.8 KB
- data-cleaning-pipeline/SKILL.md 8.4 KB
- data-cog-guide/SKILL.md 7.0 KB
- missing-data-handling/SKILL.md 7.6 KB
- pandas-data-wrangling/SKILL.md 7.6 KB
- questionnaire-design-guide/SKILL.md 8.1 KB
- stata-data-cleaning/SKILL.md 8.4 KB
- streamline-analyst-guide/SKILL.md 3.6 KB
- survey-data-processing/SKILL.md 8.9 KB
- text-mining-guide/SKILL.md 6.8 KB
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.
- 4d ago First seen · 22 lines · 41 tokens per session scan A 37369ded5513
wrangling-skills is a skill published in the GitHub repository wentorai/research-plugins (285 stars, last pushed 2mo ago), licensed MIT. It adds 41 tokens to every session and 390 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.
Other skills, from other repositories
systematic-debugging
Use when encountering any bug, test failure, or unexpected behavior, before proposing fixes.
brainstorming
You MUST use this before any creative work - creating features, building components, adding functionality, or modifying behavior. Explores user intent, requirements and design before implementation.
auto-perf-optimize
Run agent-driven VS Code performance or memory investigations. Use when asked to launch Code OSS, automate a VS Code scenario, run the Chat memory smoke runner, capture renderer heap snapshots, take workflow screenshots, compare run summaries, or drive a repeatable scenario before heap-snapshot analysis.
chat-perf
Run chat perf benchmarks and memory leak checks against the local dev build or any published VS Code version. Use when investigating chat rendering regressions, validating perf-sensitive changes to chat UI, or checking for memory leaks in the chat response pipeline.
chat-pet-sprite-creation
Use when creating or changing VS Code chat pet sprite art, sprite sheets, state animations, eye treatments, Stable/Insiders variants, or pet transitions under src/vs/workbench/contrib/chat/browser/widget/media/chatPet.
cpu-profile-analysis
Analyze V8/Chrome CPU profiles (.cpuprofile) and DevTools trace files (Trace-.json). Use when: profiling performance, investigating slow functions, comparing code paths, finding bottlenecks, analyzing timeToRequest, understanding call trees from sampling profiler data, analyzing layout/paint/rendering, investigating…