Agent skill

Excel Debug Extraction

Iteratively debug Excel structure with exploratory scripts before writing extraction logic

Install Excel Debug Extraction

skills CLI

$ npx skills add HKUDS/OpenSpace --skill excel-debug-extraction -a claude-code

Project install by default; add -g for ~/.claude/skills/.

GitHub CLI

$ gh skill install HKUDS/OpenSpace excel-debug-extraction --agent claude-code

Project scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).

Manual copy

$ git clone --depth 1 https://github.com/HKUDS/OpenSpace.git skills-src && mkdir -p .claude/skills && cp -r skills-src/benchmarks/gdpval/skills/excel-debug-extraction .claude/skills/excel-debug-extraction && rm -rf skills-src

Use ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.

Claude Code skills documentation · loads skills from .claude/skills/

Paste into Claude Code

Install the "excel-debug-extraction" agent skill from https://github.com/HKUDS/OpenSpace/tree/main/benchmarks/gdpval/skills/excel-debug-extraction into .claude/skills/excel-debug-extraction/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "excel-debug-extraction", then confirm the skill loads.

Claude Code copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.

$skill-installer

$skill-installer install https://github.com/HKUDS/OpenSpace/tree/main/benchmarks/gdpval/skills/excel-debug-extraction

Type this inside Codex. $skill-installer <name> installs a curated skill from openai/skills. The installer writes to $CODEX_HOME/skills (default ~/.codex/skills). Restart Codex if the skill does not show up.

skills CLI

$ npx skills add HKUDS/OpenSpace --skill excel-debug-extraction -a codex

Project install goes to .agents/skills/; add -g for ~/.codex/skills/.

GitHub CLI

$ gh skill install HKUDS/OpenSpace excel-debug-extraction --agent codex

Project scope by default (.agents/skills/); add --scope user for a personal install.

Manual copy

$ git clone --depth 1 https://github.com/HKUDS/OpenSpace.git skills-src && mkdir -p .agents/skills && cp -r skills-src/benchmarks/gdpval/skills/excel-debug-extraction .agents/skills/excel-debug-extraction && rm -rf skills-src

Use ~/.agents/skills/ instead of .agents/skills for a personal install.

Codex skills documentation · loads skills from .agents/skills/

Paste into Codex

Install the "excel-debug-extraction" agent skill from https://github.com/HKUDS/OpenSpace/tree/main/benchmarks/gdpval/skills/excel-debug-extraction into .agents/skills/excel-debug-extraction/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "excel-debug-extraction", then confirm the skill loads.

Codex copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.

skills CLI

$ npx skills add HKUDS/OpenSpace --skill excel-debug-extraction -a cursor

Project install goes to .agents/skills/; add -g for ~/.cursor/skills/.

GitHub CLI

$ gh skill install HKUDS/OpenSpace excel-debug-extraction --agent cursor

Project scope by default (.agents/skills/); add --scope user for a personal install.

Manual copy

$ git clone --depth 1 https://github.com/HKUDS/OpenSpace.git skills-src && mkdir -p .cursor/skills && cp -r skills-src/benchmarks/gdpval/skills/excel-debug-extraction .cursor/skills/excel-debug-extraction && rm -rf skills-src

Use ~/.cursor/skills/ instead of .cursor/skills for a personal install.

Cursor skills documentation · loads skills from .cursor/skills/, .agents/skills/, .claude/skills/, .codex/skills/

Paste into Cursor

Install the "excel-debug-extraction" agent skill from https://github.com/HKUDS/OpenSpace/tree/main/benchmarks/gdpval/skills/excel-debug-extraction into .cursor/skills/excel-debug-extraction/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "excel-debug-extraction", then confirm the skill loads.

Cursor copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.

gemini skills install

$ gemini skills install https://github.com/HKUDS/OpenSpace.git --path benchmarks/gdpval/skills/excel-debug-extraction

--scope user (default) or --scope workspace; --path is the subfolder of the repo that holds the skill; --consent skips the security confirmation prompt.

skills CLI

$ npx skills add HKUDS/OpenSpace --skill excel-debug-extraction -a gemini-cli

Project install goes to .agents/skills/; add -g for ~/.gemini/skills/.

GitHub CLI

$ gh skill install HKUDS/OpenSpace excel-debug-extraction --agent gemini-cli

Project scope by default (.agents/skills/); add --scope user for a personal install.

Manual copy

$ git clone --depth 1 https://github.com/HKUDS/OpenSpace.git skills-src && mkdir -p .gemini/skills && cp -r skills-src/benchmarks/gdpval/skills/excel-debug-extraction .gemini/skills/excel-debug-extraction && rm -rf skills-src

Use ~/.gemini/skills/ instead of .gemini/skills for a personal install, then run /skills reload.

Gemini CLI skills documentation · loads skills from .gemini/skills/, .agents/skills/

Paste into Gemini CLI

Install the "excel-debug-extraction" agent skill from https://github.com/HKUDS/OpenSpace/tree/main/benchmarks/gdpval/skills/excel-debug-extraction into .gemini/skills/excel-debug-extraction/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "excel-debug-extraction", then confirm the skill loads.

Gemini CLI copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.

GitHub CLI

$ gh skill install HKUDS/OpenSpace excel-debug-extraction

Installs for Copilot at project scope by default; add --scope user for a personal install. Preview a skill first with gh skill preview. Needs GitHub CLI 2.90.0 or later (public preview).

skills CLI

$ npx skills add HKUDS/OpenSpace --skill excel-debug-extraction -a github-copilot

Project install goes to .agents/skills/; add -g for ~/.copilot/skills/.

Manual copy

$ git clone --depth 1 https://github.com/HKUDS/OpenSpace.git skills-src && mkdir -p .github/skills && cp -r skills-src/benchmarks/gdpval/skills/excel-debug-extraction .github/skills/excel-debug-extraction && rm -rf skills-src

Use ~/.copilot/skills/ instead of .github/skills for a personal install. Commit .github/skills so cloud agent and code review can use it.

GitHub Copilot skills documentation · loads skills from .github/skills/, .claude/skills/, .agents/skills/

Paste into GitHub Copilot

Install the "excel-debug-extraction" agent skill from https://github.com/HKUDS/OpenSpace/tree/main/benchmarks/gdpval/skills/excel-debug-extraction into .github/skills/excel-debug-extraction/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "excel-debug-extraction", then confirm the skill loads.

GitHub Copilot copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.

skills CLI

$ npx skills add HKUDS/OpenSpace --skill excel-debug-extraction -a opencode

OpenCode documents no install command of its own. Project install goes to .agents/skills/; add -g for ~/.config/opencode/skills/.

GitHub CLI

$ gh skill install HKUDS/OpenSpace excel-debug-extraction --agent opencode

Project scope by default (.agents/skills/); add --scope user for a personal install.

Manual copy

$ git clone --depth 1 https://github.com/HKUDS/OpenSpace.git skills-src && mkdir -p .opencode/skills && cp -r skills-src/benchmarks/gdpval/skills/excel-debug-extraction .opencode/skills/excel-debug-extraction && rm -rf skills-src

Use ~/.config/opencode/skills/ instead of .opencode/skills for a personal install.

OpenCode skills documentation · loads skills from .opencode/skills/, .claude/skills/, .agents/skills/

Paste into OpenCode

Install the "excel-debug-extraction" agent skill from https://github.com/HKUDS/OpenSpace/tree/main/benchmarks/gdpval/skills/excel-debug-extraction into .opencode/skills/excel-debug-extraction/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "excel-debug-extraction", then confirm the skill loads.

OpenCode copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.

Facts

Skill name: excel-debug-extraction
GitHub stars: 7.7k
Token cost: ~1.3k tokens
SKILL.md length: 313 words
Files: 2
Skills in repo: 199
Repo updated: Aug 12, 2026
First seen: Oct 7, 2026
Licence: MIT

At a glance

Iteratively debug Excel structure with exploratory scripts before writing extraction logic

Works in 5 steps: Initial Structure Reconnaissance → Map Column Positions → Identify Row Patterns → …
Tasks that involve Excel spreadsheets
SKILL.md covers When to Use This Skill, Workflow Steps, Best Practices and Common Pitfalls to Avoid, plus 1 more section
Instructions only: no scripts, shell commands, URLs or credentials in SKILL.md

What it does

Excel Debug Extraction is an agent skill from HKUDS/OpenSpace. Iteratively debug Excel structure with exploratory scripts before writing extraction logic

Its SKILL.md is about 1.3k tokens, which your agent loads only when the skill is triggered. The skill folder holds 1 other file.

It sits in Documents & Office, covering Excel spreadsheets. It works with Microsoft Excel. The repository describes itself as: "OpenSpace: The Skill Management Layer for AI Agents" -- https://open-space.cloud/. The licence is MIT.

When your agent uses it

Tasks that involve Excel spreadsheets

Example prompts

“/excel-debug-extraction”

Requirements

Python 3

Workflow steps

5 steps, taken from the step headings in SKILL.md.

Initial Structure Reconnaissance
Map Column Positions
Identify Row Patterns
Document Findings
Write Extraction Logic

What it can do on your machine

Read from SKILL.md and the folder at commit 3827781. It shows what the files ask for, not the result of running them.

Tool permissions
Pre-approves nothing: there is no allowed-tools line, so your agent's usual permission prompts apply.
From allowed-tools in the SKILL.md frontmatter.
Runs code
No scripts in the folder and no shell commands in SKILL.md (its code samples are python).
From the folder's file list and the shell code blocks in SKILL.md.
Network
No URLs in SKILL.md.
From URLs in SKILL.md, links to its own repository left out.
Credentials
Names no API keys, tokens, secrets or passwords.
From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.

Context cost

Excel Debug Extraction loads about 1.3k tokens when it runs. Until then it costs about 28 tokens; SKILL.md has 313 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it: ~28
When it runs · the whole SKILL.md, loaded when a task matches: ~1.3k

Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.

Safety

Auto-check passed

The automated check found no risky patterns in SKILL.md.

Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); files beside SKILL.md are not scanned.

SKILL.md

The full file from HKUDS/OpenSpace at commit 3827781, republished under its MIT licence (© HKUDS). 313 words, ~1,308 tokens.

Download SKILL.mdSave it as .claude/skills/excel-debug-extraction/SKILL.md (or your agent's skills folder). This skill also uses 1 other file; get the full folder from GitHub.

name: excel-debug-extraction
description: Iteratively debug Excel structure with exploratory scripts before writing extraction logic

Excel Debug-First Extraction Workflow

When working with poorly-structured, complex, or unfamiliar Excel files, use this iterative debugging approach to map the data layout before writing your final extraction logic.

When to Use This Skill

Excel files with inconsistent formatting or merged cells
Files received from external sources with unknown structure
Complex workbooks with multiple sheets and interdependencies
When initial parsing attempts fail or produce unexpected results

Workflow Steps

Step 1: Initial Structure Reconnaissance

Before writing extraction logic, create a debug script to explore the file structure:

python

# debug_structure.py
from openpyxl import load_workbook

wb = load_workbook('file.xlsx')
print(f"Sheets: {wb.sheetnames}")

for sheet_name in wb.sheetnames:
    ws = wb[sheet_name]
    print(f"\n=== Sheet: {sheet_name} ===")
    print(f"Dimensions: {ws.dimensions}")
    
    # Print first 10 rows to understand header structure
    for row in ws.iter_rows(min_row=1, max_row=10, values_only=True):
        print([str(cell)[:50] for cell in row])

Step 2: Map Column Positions

Identify where key data fields are located:

python

# debug_columns.py
from openpyxl import load_workbook

wb = load_workbook('file.xlsx')
ws = wb['Sheet1']

# Examine header row to find column indices
header_row = 1
column_map = {}

for col in ws.iter_cols(min_row=header_row, max_row=header_row):
    for cell in col:
        if cell.value:
            column_map[str(cell.value)] = cell.column_letter

print("Column mapping:", column_map)

# Sample data rows to verify structure
for row_num in range(2, min(6, ws.max_row + 1)):
    row_data = [ws.cell(row=row_num, column=col).value 
                for col in range(1, ws.max_column + 1)]
    print(f"Row {row_num}: {row_data}")

Step 3: Identify Row Patterns

Understand how data rows are structured (e.g., summary rows, detail rows, blank separators):

python

# debug_rows.py
from openpyxl import load_workbook

wb = load_workbook('file.xlsx')
ws = wb['Sheet1']

row_types = []
for row_num in range(1, min(30, ws.max_row + 1)):
    row_values = [ws.cell(row=row_num, column=col).value 
                  for col in range(1, ws.max_column + 1)]
    
    non_empty = sum(1 for v in row_values if v is not None and str(v).strip())
    
    # Classify row type
    if non_empty == 0:
        row_type = "blank"
    elif non_empty == 1:
        row_type = "summary/label"
    elif non_empty == ws.max_column:
        row_type = "full_data"
    else:
        row_type = "partial"
    
    row_types.append((row_num, row_type, row_values[:5]))

for rt in row_types:
    print(f"Row {rt[0]} ({rt[1]}): {rt[2]}")

Step 4: Document Findings

Before writing extraction logic, summarize:

Sheet names and their purposes
Header row location and column mappings
Data row patterns (which rows contain actual data vs. headers/summaries)
Any special formatting (merged cells, blank separators, grouping rows)

Step 5: Write Extraction Logic

Incorporate findings into your final processing script:

python

# extract_data.py
from openpyxl import load_workbook
import pandas as pd

wb = load_workbook('file.xlsx')
ws = wb['Sheet1']

# Use column mappings from debug phase
STORE_COL = 'B'  # Column 2
WEEK1_COL = 'D'  # Column 4
WEEK2_COL = 'E'  # Column 5

# Skip header rows and summary rows based on debug findings
data_rows = []
for row_num in range(5, ws.max_row + 1):  # Start after header based on debug
    # Skip summary/blank rows
    if ws.cell(row=row_num, column=2).value is None:
        continue
    if 'TOTAL' in str(ws.cell(row=row_num, column=2).value).upper():
        continue
    
    row_data = {
        'store': ws.cell(row=row_num, column=2).value,
        'week1': ws.cell(row=row_num, column=4).value,
        'week2': ws.cell(row=row_num, column=5).value,
    }
    data_rows.append(row_data)

df = pd.DataFrame(data_rows)
print(df.head())

Best Practices

Always start with exploration - Never assume Excel structure matches expectations
Save debug scripts - Keep them in your project for future reference and debugging
Print generously - Use verbose output during exploration to catch edge cases
Verify row-by-row - Don't assume all data rows follow the same pattern
Handle merged cells - Check for merged cells that span multiple rows/columns

Common Pitfalls to Avoid

Assuming header is always row 1
Assuming all rows between first and last contain data
Not checking for hidden sheets or protected ranges
Ignoring cell formatting that indicates row type (bold, indentation)
Not handling None values or empty strings consistently

File Naming Convention

Use descriptive names for debug scripts:

debug_structure.py - Overall file/sheet structure
debug_columns.py - Column positions and headers
debug_rows.py - Row patterns and data boundaries
debug_values.py - Value patterns and edge cases

Keep debug scripts alongside your extraction script for maintainability.

Files

SKILL.md and 1 other file in benchmarks/gdpval/skills/excel-debug-extraction of HKUDS/OpenSpace.

SKILL.md
.skill_id

Open the folder on GitHubat commit 3827781

Compare with similar skills

Excel Debug Extraction next to the 5 skills that share the most tags, products or categories with it. Stars are the repository's; “used in” counts other GitHub owners with a copy.

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Questions about Excel Debug Extraction

What does Excel Debug Extraction do?

Iteratively debug Excel structure with exploratory scripts before writing extraction logic. Excel Debug Extraction is an agent skill from HKUDS/OpenSpace.

When should I use Excel Debug Extraction?

Excel Debug Extraction fits situations like: tasks that involve Excel spreadsheets.

How do I install Excel Debug Extraction in Claude Code?

Run `npx skills add HKUDS/OpenSpace --skill excel-debug-extraction -a claude-code`. Or copy the skill folder (benchmarks/gdpval/skills/excel-debug-extraction in HKUDS/OpenSpace) into .claude/skills/excel-debug-extraction in your project. Claude Code loads it when a task matches its description.

How do I install Excel Debug Extraction in Codex?

Run `npx skills add HKUDS/OpenSpace --skill excel-debug-extraction -a codex`. Or copy the skill folder (benchmarks/gdpval/skills/excel-debug-extraction in HKUDS/OpenSpace) into .agents/skills/excel-debug-extraction in your project. Codex loads it when a task matches its description.

Can I use Excel Debug Extraction in Cursor, Gemini CLI or GitHub Copilot?

Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add HKUDS/OpenSpace --skill excel-debug-extraction -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/excel-debug-extraction, .gemini/skills/excel-debug-extraction, .github/skills/excel-debug-extraction and .opencode/skills/excel-debug-extraction in your project.

What does Excel Debug Extraction need to run?

SKILL.md names no scripts, command-line tools or credentials: Excel Debug Extraction is instructions for the agent only. Our summary lists: Python 3.

Does Excel Debug Extraction access the network?

SKILL.md contains no URLs. Any network use would come from the scripts or tools the agent runs. This is read from the text; nothing was executed.

Is Excel Debug Extraction safe to install?

Our automated static check of SKILL.md found no risky patterns, such as piping downloads into a shell, reading credential files or hidden Unicode. It is not a guarantee. Review the folder before installing.

What licence does Excel Debug Extraction use?

Excel Debug Extraction is published under the MIT licence (the repository's licence). It allows redistribution, so the full SKILL.md is shown on this page.

How many tokens does Excel Debug Extraction use?

About 1.3k tokens (SKILL.md is roughly 5.2k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full.

What are the alternatives to Excel Debug Extraction?

Skills that share tags, products or a category with Excel Debug Extraction: Markitdown (ImCa0/just-laws, 781 stars), Data Table Manager (n8n-io/n8n, 207k stars), Docx4j (plutext/docx4j, 2.4k stars) and Instrument Data To Allotrope (aws-samples/amazon-bedrock-agents-healthcare-lifesciences, 274 stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Excel Debug Extraction?

HKUDS (a GitHub organization) maintains it in HKUDS/OpenSpace, which has 7,749 GitHub stars. The repository holds 199 skills in this directory. The repository was last updated on August 12, 2026.

Source: HKUDS/OpenSpace on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.

Install Excel Debug Extraction

Facts

At a glance

What it does

When your agent uses it

Example prompts

Requirements

Workflow steps

What it can do on your machine

Tool permissions

Runs code

Network

Credentials

Context cost

Safety

SKILL.md

Excel Debug-First Extraction Workflow

When to Use This Skill

Workflow Steps

Step 1: Initial Structure Reconnaissance

Step 2: Map Column Positions

Step 3: Identify Row Patterns

Step 4: Document Findings

Step 5: Write Extraction Logic

Best Practices

Common Pitfalls to Avoid

File Naming Convention

Files

Compare with similar skills

Similar skills

More from HKUDS/OpenSpace

Related

Questions about Excel Debug Extraction