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 Pixel-Process-UG/superkit-agents --skill xlsx-processinggit clone --depth 1 https://github.com/Pixel-Process-UG/superkit-agentsWrote 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/pixel-process-ug/superkit-agents/xlsx-processing)<a href="https://agentmods.dev/skills/pixel-process-ug/superkit-agents/xlsx-processing"><img src="https://agentmods.dev/badge/skills/pixel-process-ug/superkit-agents/xlsx-processing/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/pixel-process-ug/superkit-agents/xlsx-processing"><img src="https://agentmods.dev/badge/skills/pixel-process-ug/superkit-agents/xlsx-processing.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 | $0.00076 | $0.02983 |
| Opus 5 | $0.00038 | $0.01491 |
| Sonnet 5 | $0.00015 | $0.00597 |
| Haiku 4.5 | $0.00008 | $0.00298 |
Grade A, and why
xlsx-processing 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 6d 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 — 373 lines — stays where its author put it; the contents beside it link to each section on GitHub.
XLSX Processing
Overview
Manipulate Excel files programmatically using openpyxl for rich formatting and pandas for data analysis. This skill covers reading/writing spreadsheets, formulas, charts, conditional formatting, data validation, pivot table generation, CSV import/export, and strategies for handling large files.
Apply this skill whenever Excel files need to be created, read, transformed, or enriched through code rather than manual editing.
Multi-Phase Process
Phase 1: Requirements
- Determine operation (read, write, transform, report)
- Identify data sources and volume
- Define formatting and formula requirements
- Plan sheet structure and naming
- Assess performance needs (row count, file size)
STOP — Do NOT begin implementation until you know the row count and whether formatting is needed (this determines library choice).
Phase 2: Implementation
- Select library (see decision table)
- Implement data loading and transformation
- Apply formatting, formulas, and validation
- Add charts and conditional formatting
- Optimize for file size and memory
STOP — Do NOT skip memory optimization for files exceeding 10,000 rows.
Phase 3: Validation
- Open in Excel, LibreOffice, and Google Sheets
- Verify formulas calculate correctly
- Check formatting renders consistently
- Test with edge cases (empty data, max rows)
- Validate data accuracy
Library Decision Table
| Scenario | Library | Why |
|---|---|---|
| Rich formatting (colors, borders, fonts) | openpyxl | Full formatting API |
| Data analysis, aggregation, pivots | pandas | DataFrame operations |
| Formatted report from data analysis | pandas + openpyxl | Combine strengths |
| Reading data only, no formatting needed | pandas | Simplest API |
| Large file (> 10K rows), write-heavy | openpyxl write_only | Streaming writes, low memory |
| Large file (> 10K rows), read-heavy | openpyxl read_only | Streaming reads, low memory |
| CSV to/from Excel conversion | pandas | One-liner operations |
| Charts in spreadsheet | openpyxl | Chart API with full control |
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.
- 6d ago First seen · 373 lines · 76 tokens per session scan A 909d9dbdc110
xlsx-processing is a skill published in the GitHub repository Pixel-Process-UG/superkit-agents (1 stars, last pushed 5mo ago), licensed MIT. It adds 76 tokens to every session and 2,983 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.
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