xlsx

xlsx is a skill for Claude Code, Codex from ginlix-ai/LangAlpha. It costs 39 tokens per session (9,337 once invoked), scanned A, a copy of xlsx, Apache-2.0.

A set of rules for working with spreadsheet files such as Excel workbooks, CSV files, and TSV files. It covers editing, formulas, formatting, charts, and data cleanup.

In plain words
What is it for?
Use it whenever a spreadsheet is the main input or output, including when adding columns, fixing formulas, cleaning data, formatting sheets, or creating charts.
Why use it?
It helps preserve existing spreadsheet layouts, avoid formula errors, and keep financial models understandable and consistent.

Skill for Claude CodeCodex

Written for no agent in particular: nothing here depends on one.

Good fit Use it whenever a spreadsheet is the main input or output, including when adding columns, fixing formulas, cleaning data, formatting sheets, or creating charts.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/ginlix-ai/langalpha/xlsx
About the project

LangAlpha is an agent workspace for researching financial markets and supporting investment decisions through persistent research, news analysis, and parallel subagents. It is for investors who want to develop and update trading theses over time, including generating long-short pair-trade ideas. The catalogue entries provide the skills, instructions, MCP servers, and plugin that make up its agent workflow.

ginlix-ai/LangAlpha · 2,155 stars · on GitHub · langalpha.ai

Install

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.

Any agent
npx skills add ginlix-ai/LangAlpha --skill xlsx
Clone the repo
git clone --depth 1 https://github.com/ginlix-ai/LangAlpha

Made for: Claude Code, Codex.

Wrote 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.

agentmods badge for xlsx

README.md
[![agentmods](https://agentmods.dev/badge/skills/ginlix-ai/langalpha/xlsx/github.svg)](https://agentmods.dev/skills/ginlix-ai/langalpha/xlsx)
Your own site
<a href="https://agentmods.dev/skills/ginlix-ai/langalpha/xlsx"><img src="https://agentmods.dev/badge/skills/ginlix-ai/langalpha/xlsx/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.

agentmods 80×15 button for xlsx

Your own site · 80×15
<a href="https://agentmods.dev/skills/ginlix-ai/langalpha/xlsx"><img src="https://agentmods.dev/badge/skills/ginlix-ai/langalpha/xlsx.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 39 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 9,337 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe.
Origin 91% copy Near-identical to another mod in the catalogue.
Token cost

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.

ModelPer sessionOnce invoked
Fable 5.1 $0.00039 $0.09337
Opus 5.5 $0.00016 $0.03735
Sonnet 5.5 $0.00008 $0.01867
Haiku 4.5 $0.00004 $0.00934

Measured 1mo ago against content hash a1993041cc23, method: parsed. Prices are Anthropic first-party input rates as of 2026-10-07, from the pricing page.

Security

Grade A, and why

xlsx 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.

The scan reads SKILL.md. This mod also ships 5 executable files (scripts/audit.py, scripts/insert.py, scripts/profile.py, …), listed below but not scanned — reading those needs a real analyzer, not pattern matching.

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.

Origin

This is a copy

91% identical to xlsx — 436 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.

plugins/langalpha_deliverables/skills/xlsx/SKILL.md · 280 lines

How it starts

The opening of the file, as written. The whole thing — 280 lines — stays where its author put it; the contents beside it link to each section on GitHub.

XLSX

Build or edit an Excel workbook and write it into the task directory (e.g. dcf_acme/acme_dcf.xlsx). The user opens it in Excel, changes an input, and every dependent number moves. That is the whole point of the format: a workbook the agent delivers is a model, not a table of results. A cell that could be computed from other cells is a formula. A number typed into a formula's place is a defect, even when the value is right today.

This is the right output when the user wants something they will keep working in: a DCF, a comps sheet, a three-statement model, a screen they will re-sort, a schedule they will extend. It is the wrong output for a one-off table (put it in the chat or an HTML report) and for a document that will not be edited (see .agents/skills/html-report/SKILL.md).

User preferences override these defaults. A house colour code, a template workbook, a sheet layout the user has described: those outrank every rule here. Inside a workbook the font colour code below outranks the general house palette in ui-design (green means a cross-sheet link here, not a gain). The rules below are for when nothing has been specified.

Decide: Which Output?

Want Use
A model the user will edit, extend, or plug into their own workbook xlsx (this skill)
A polished document to read, print, or share, possibly with charts html-report
A dataset for another program .csv via pandas, no styling
One table in the conversation markdown table

Workflow

  1. Plan the sheets before writing code: which sheet holds inputs, which holds calculations, which holds outputs. Sketch the row labels and the period columns. A model that is laid out first is a model whose formulas can be copied across.
  2. Write a build script, <task>/build_<name>.py, and run it. Never build a workbook cell by cell in ad-hoc calls. The script is the source of truth; when the user asks for a change, edit the script and rerun.
  3. Recalculate: python .agents/skills/xlsx/scripts/recalc.py <task>/<name>.xlsx 60. Fix every listed error and rerun until "status": "success".
  4. Audit: python .agents/skills/xlsx/scripts/audit.py <task>/<name>.xlsx --strict. Fix every fail; for every warn, either fix it or write the one line in the delivery that says why it stands. --strict is the prescribed form: it exits non-zero on a fail and promotes formula_number_format from a warning.
  5. Render and look: python .agents/skills/xlsx/scripts/render.py <task>/<name>.xlsx, then view the PNGs. Overflowing ### columns, unformatted rates, and headers that do not line up are visible here and nowhere else.
  6. Spot-check three numbers by hand against your own calculation before delivering. A clean recalc proves the formulas evaluate, not that they are the right formulas.
  7. Assert the sensitivity centre in the build script. Where the model has a sensitivity grid, the script reopens the workbook after recalc.py with data_only=True, reads the centre cell of every grid and the headline output it varies, and asserts they are equal. A grid that has come unwired then fails the build instead of shipping. Name the same pair in a Checks row (below): that row is what lets audit.py re-check the equality on a workbook nobody rebuilt, and without it the audit reports sensitivity_unverified rather than deciding for itself which output the grid varies.

Read the full file on GitHub · 280 lines

Files

What ships with it

5 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.

Changes

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.

  1. 1mo ago Changed a1993041cc23
  2. 1mo ago Changed · -15 lines · -162 tokens per session 04cb4cbe24d3
  3. 1mo ago First seen · 295 lines · 201 tokens per session scan A 00b023c6f615

Subscribe to this mod's changes

xlsx is a skill published in the GitHub repository ginlix-ai/LangAlpha (2,155 stars, last pushed today), licensed Apache-2.0. It adds 39 tokens to every session and 9,337 once invoked, about $0.0002 per session on Opus 5.5. A static security scan graded it A with 0 findings. It is 91% identical to xlsx, differing in 436 lines, and is treated as a copy.

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