agentsclimarketplace

Xlsx

Skill ploteddie-bit/skills/xlsx

Collection de compétences agentiques modulables pour Kimi, Aegis et assistants IA

Install
npx -y skills add ploteddie-bit/skills --skill xlsx

Assembled from the repository path, not quoted from the project. Check it against their README if it does not work.

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What its author says it does

Copied from the file, not written here

Use this skill any time a spreadsheet file is the primary input or output. This means any task where the user wants to: open, read, edit, or fix an existing .xlsx, .xlsm, .csv, or .tsv file; create a new spreadsheet from scratch or from other data sources; analyze data and output results as an Excel file with charts; convert between tabular file formats (CSV/JSON/PDF → XLSX or vice versa); clean, merge, pivot, or transform tabular data. Trigger especially when the user references a spreadsheet file by name or path, says 'make a table/report/model', mentions Excel/CSV/数据分析/报表/汇总, or wants data visualization inside a spreadsheet.

The file declares its own license as Proprietary. LICENSE.txt has complete terms. That is the author’s claim about this one file, and it is not the same thing as the license GitHub reports for the repository, which is listed with the other numbers below.

SKILL.md

10.2 KB, ~2.3k tokens by cl100k_base, as published. Nobody here has run it

XLSX — Scene-Driven Spreadsheet Workbench

Quick Setup

bash "$XLSX_SKILL_DIR/setup.sh"    # Interactive environment check + install

Pre-Flight: Intent Gate

Before touching any code, confirm the user actually needs a spreadsheet:

  • Report / analysis summary (述职, 调研报告) → docx skill
  • Presentation (汇报, 演示, pitch deck) → pptx skill
  • Formal print document (合同, 证书, "PDF") → pdf skill
  • Charts only, no data table needed → charts skill
  • User explicitly says a format → respect it

If confirmed xlsx → proceed to Scene Router below.

Request Decomposition (do this every time):

  • Explicit needs: sheets, columns, formulas, metrics the user stated
  • Implicit needs: business context, downstream use (filter? sort? input?)
  • Multi-part requests: generate ALL parts — never silently drop a component

Multi-Intent Detection — some requests combine multiple scenes:

"Create a financial model with charts and export a PDF summary"
 → scenes/finance.md + engines/chart.md + (hand off PDF to pdf skill)

"Analyze this CSV, build a dashboard, and make it look professional"
 → scenes/analyze.md + engines/chart.md + engines/design.md

"Edit this budget file, add a new quarter column, and create a pivot"
 → scenes/edit.md + quality/pipeline.md (pivot command)

"Convert these 5 CSVs into one xlsx with a summary sheet"
 → scenes/convert.md + scenes/create.md (for summary)

When multiple intents detected, load all matching files and execute in logical order: data preparation → analysis → visualization → styling → QA.


Complexity Gate (evaluate BEFORE Scene Router)

Determine task complexity to control file loading depth:

User Request
│
├─ LITE (single aggregation, simple chart, direct conversion, QA-only)
│  → Load: SKILL.md + ONE scene file (lean version)
│  → Skip: engine files (use built-in knowledge for basic styles)
│  → QA: audit + validate only
│  → Target: ≤ 400 lines total context
│
└─ FULL (multi-dimensional analysis, financial model, dashboard, KANO, etc.)
   → Load: SKILL.md + scene + engines (chart.md / design.md) as needed
   → For code patterns: load recipes/templates files ON DEMAND (not upfront)
   → QA: full pipeline (recalc → audit → scan → chart-verify → validate)
   → Target: load recipes/templates only when stuck on implementation

LITE triggers: single groupby, one chart, format conversion, inspect/audit/validate, simple pivot FULL triggers: correlation matrix, multi-sheet dashboard, statistical analysis, financial model, KANO/funnel/cohort


Scene Router

User Request
│
├─ Involves an existing file?
│  ├─ Yes → Modify content or structure?
│  │         ├─ Yes ──────────────────── → scenes/edit.md
│  │         └─ No (read/analyze only) ─ → scenes/analyze.md
│  │
│  └─ Format conversion (CSV↔XLSX, JSON, PDF tables)?
│     └─ Yes ────────────────────────── → scenes/convert.md
│
├─ Create from scratch?
│  ├─ Financial / budget / forecast / cost tracking?
│  │  ├─ Complex (DCF / LBO / three-statement linkage (三表联动) / sensitivity / IB model)?
│  │  │  └─ Yes ─────────────────────── → scenes/finance.md
│  │  └─ Simple (budget table (预算表) / expense report (费用报表) / revenue vs cost (收支对比) / project cost (项目成本) / personal finance (个人记账))?
│  │     └─ Yes ─────────────────────── → scenes/finance_lite.md
│  └─ General table / report / template
│     └─ ──────────────────────────── → scenes/create.md
│
├─ Batch processing / large files / protection / validation?
│  └─ Yes ───────────────────────────── → scenes/advanced.md
│
├─ VBA / macros / automation inside Excel?
│  └─ Yes ───────────────────────────── → scenes/vba.md + engines/vba-templates.md
│
├─ Needs charts or data visualization?
│  └─ Yes ───────────── append ────────→ engines/chart.md
│
└─ Needs styling / design system?
   └─ Yes ───────────── append ────────→ engines/design.md

Mixed requests: load all matching files. Engine files always append to a scene.

Finance detection:

  • finance.md (complex): DCF, LBO, P&L, 利润表, 资产负债, valuation, 估值, IRR, 三表联动, sensitivity, scenario
  • finance_lite.md (simple): 预算, budget, 费用, expense, 收支, 记账, 项目成本, cost tracking, 报销, ROI

VBA detection: 宏, macro, VBA, 自动化, automation, .xlsm, 按钮, button, auto-run, 批量处理脚本


Design Principles

1. Live Formula Guarantee

Every derived value SHOULD be an Excel formula so the spreadsheet stays dynamic.

Exception — Programmatic Verification: When the output file will be verified by Python (not opened in Excel), TOTAL/SUM rows should write computed values instead of formulas, because openpyxl cannot evaluate formulas and data_only=True returns None for newly-written formulas. Optionally add the formula as a cell comment for reference.

2. Zero Error Tolerance

Deliverables must have zero formula errors. All divisions wrapped with IFERROR or IF(denom=0,...). Absolute references ($C$42) for shared denominators.

3. Compatibility First

No dynamic array functions (FILTER, UNIQUE, XLOOKUP, SORT, SORTBY, XMATCH, SEQUENCE, LET, LAMBDA, RANDARRAY). No implicit array formulas — use SUMPRODUCT alternatives.

4. Preserve & Match

When editing existing files: study and exactly match format, style, conventions. Existing patterns always override defaults. Text starting with = must be prefixed with '.

5. Language Mirror

Output language (sheet names, headers, labels) matches user's input language.

6. Data Consistency Over Instructions

When user instructions conflict with the actual data patterns in the existing file:

  • First priority: match the existing data pattern (e.g., if existing data uses 0 for empty, don't switch to -)
  • Second priority: follow user instructions literally
  • Always flag the conflict to the user

Example: User says "show hyphen for zero" but existing data and answer key use numeric 0 → Use 0 and notify user of the discrepancy.


Toolchain

Script Path Setup (MANDATORY before any script call)

All CLI tools live relative to this skill's directory. Before calling any script, resolve the absolute path once:

XLSX_SKILL_DIR="<skill_directory>"   # ← parent directory of this SKILL.md

# Then all commands use absolute paths:
python3 "$XLSX_SKILL_DIR/xlsx.py" inspect data.xlsx --pretty
python3 "$XLSX_SKILL_DIR/xlsx.py" pivot data.xlsx output.xlsx --rows Region --values Revenue
python3 "$XLSX_SKILL_DIR/xlsx.py" validate output.xlsx

For Python imports (when generation code needs to import skill modules):

import sys, os
XLSX_SKILL_DIR = "<skill_directory>"
for sub in [XLSX_SKILL_DIR, os.path.join(XLSX_SKILL_DIR, "templates")]:
    if sub not in sys.path:
        sys.path.insert(0, sub)

⚠️ NEVER use bare python3 xlsx.py ... — it only works if cwd happens to be the skill directory. Always use the absolute path.

Tool Reference

ToolUse
openpyxlFormulas, formatting, charts, cell-level control
pandasData analysis, bulk operations, CSV/TSV
load_workbook(read_only=True)Large file reads
Workbook(write_only=True)Large file writes
templates/base.pyDesign tokens, font resolution, style factories, utilities (single source of truth)
xlsx.pyQA commands (see quality/pipeline.md)

Workbook metadata: wb.properties.creator = "Z.ai"

All code must import from templates/base.py for colors, fonts, and style helpers. Never hardcode hex values or font names.


Quality Gate

Every deliverable must pass the full integrity pipeline before delivery.

Load quality/pipeline.md for the role-based integrity workflow.

Quick reference:

Blueprint → Build & Self-check (per-sheet) → Inspect → Pivot (if needed) → Release

Capability Matrix

CapabilitySupportedScene/Engine
Create from scratchscenes/create
Edit existing filescenes/edit
Data analysis & EDAscenes/analyze
Format conversionscenes/convert
Financial models (DCF/LBO/P&L)scenes/finance
Simple budgets & expensesscenes/finance_lite
VBA macros & automationscenes/vba + engines/vba-templates
Batch processingscenes/advanced
Embedded chartsengines/chart
Smart chart recommendationengines/chart
Design system & stylingengines/design
PivotTable creationquality/pipeline (pivot cmd)
Formula validationquality/pipeline
Structural validationquality/pipeline
Data provenance trackingscenes/analyze
Large file handlingscenes/advanced
Data protection & lockingscenes/advanced

What ships with it: 20 files

203.3 KB alongside SKILL.md, 20 of them executable

engines/

quality/

scenes/

templates/

Keep looking

Skills are one crate of 328,083. Ordering is by how many stacks a row turns up in, so the top of any crate is what has actually been picked rather than what has the most stars.