Instrument Data To Allotrope
aws-samples/amazon-bedrock-agents-healthcare-lifesciences
Convert laboratory instrument output files (PDF, CSV, Excel, TXT) to Allotrope Simple Model (ASM) JSON format or flattened 2D CSV.
Use direct Python execution for reliable document creation including spreadsheets, PDFs, and structured reports
$ npx skills add HKUDS/OpenSpace --skill document-direct-python -a claude-codeProject install by default; add -g for ~/.claude/skills/.
$ gh skill install HKUDS/OpenSpace document-direct-python --agent claude-codeProject scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).
$ git clone --depth 1 https://github.com/HKUDS/OpenSpace.git skills-src && mkdir -p .claude/skills && cp -r skills-src/benchmarks/gdpval/skills/spreadsheet-direct-python-merged .claude/skills/document-direct-python && rm -rf skills-srcUse ~/.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/
Install the "document-direct-python" agent skill from https://github.com/HKUDS/OpenSpace/tree/main/benchmarks/gdpval/skills/spreadsheet-direct-python-merged into .claude/skills/document-direct-python/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "document-direct-python", 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 install https://github.com/HKUDS/OpenSpace/tree/main/benchmarks/gdpval/skills/spreadsheet-direct-python-mergedType 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.
$ npx skills add HKUDS/OpenSpace --skill document-direct-python -a codexProject install goes to .agents/skills/; add -g for ~/.codex/skills/.
$ gh skill install HKUDS/OpenSpace document-direct-python --agent codexProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/HKUDS/OpenSpace.git skills-src && mkdir -p .agents/skills && cp -r skills-src/benchmarks/gdpval/skills/spreadsheet-direct-python-merged .agents/skills/document-direct-python && rm -rf skills-srcUse ~/.agents/skills/ instead of .agents/skills for a personal install.
Codex skills documentation · loads skills from .agents/skills/
Install the "document-direct-python" agent skill from https://github.com/HKUDS/OpenSpace/tree/main/benchmarks/gdpval/skills/spreadsheet-direct-python-merged into .agents/skills/document-direct-python/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "document-direct-python", 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.
$ npx skills add HKUDS/OpenSpace --skill document-direct-python -a cursorProject install goes to .agents/skills/; add -g for ~/.cursor/skills/.
$ gh skill install HKUDS/OpenSpace document-direct-python --agent cursorProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/HKUDS/OpenSpace.git skills-src && mkdir -p .cursor/skills && cp -r skills-src/benchmarks/gdpval/skills/spreadsheet-direct-python-merged .cursor/skills/document-direct-python && rm -rf skills-srcUse ~/.cursor/skills/ instead of .cursor/skills for a personal install.
Cursor skills documentation · loads skills from .cursor/skills/, .agents/skills/, .claude/skills/, .codex/skills/
Install the "document-direct-python" agent skill from https://github.com/HKUDS/OpenSpace/tree/main/benchmarks/gdpval/skills/spreadsheet-direct-python-merged into .cursor/skills/document-direct-python/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "document-direct-python", 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 https://github.com/HKUDS/OpenSpace.git --path benchmarks/gdpval/skills/spreadsheet-direct-python-merged--scope user (default) or --scope workspace; --path is the subfolder of the repo that holds the skill; --consent skips the security confirmation prompt.
$ npx skills add HKUDS/OpenSpace --skill document-direct-python -a gemini-cliProject install goes to .agents/skills/; add -g for ~/.gemini/skills/.
$ gh skill install HKUDS/OpenSpace document-direct-python --agent gemini-cliProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/HKUDS/OpenSpace.git skills-src && mkdir -p .gemini/skills && cp -r skills-src/benchmarks/gdpval/skills/spreadsheet-direct-python-merged .gemini/skills/document-direct-python && rm -rf skills-srcUse ~/.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/
Install the "document-direct-python" agent skill from https://github.com/HKUDS/OpenSpace/tree/main/benchmarks/gdpval/skills/spreadsheet-direct-python-merged into .gemini/skills/document-direct-python/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "document-direct-python", 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.
$ gh skill install HKUDS/OpenSpace document-direct-pythonInstalls 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).
$ npx skills add HKUDS/OpenSpace --skill document-direct-python -a github-copilotProject install goes to .agents/skills/; add -g for ~/.copilot/skills/.
$ git clone --depth 1 https://github.com/HKUDS/OpenSpace.git skills-src && mkdir -p .github/skills && cp -r skills-src/benchmarks/gdpval/skills/spreadsheet-direct-python-merged .github/skills/document-direct-python && rm -rf skills-srcUse ~/.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/
Install the "document-direct-python" agent skill from https://github.com/HKUDS/OpenSpace/tree/main/benchmarks/gdpval/skills/spreadsheet-direct-python-merged into .github/skills/document-direct-python/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "document-direct-python", 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.
$ npx skills add HKUDS/OpenSpace --skill document-direct-python -a opencodeOpenCode documents no install command of its own. Project install goes to .agents/skills/; add -g for ~/.config/opencode/skills/.
$ gh skill install HKUDS/OpenSpace document-direct-python --agent opencodeProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/HKUDS/OpenSpace.git skills-src && mkdir -p .opencode/skills && cp -r skills-src/benchmarks/gdpval/skills/spreadsheet-direct-python-merged .opencode/skills/document-direct-python && rm -rf skills-srcUse ~/.config/opencode/skills/ instead of .opencode/skills for a personal install.
OpenCode skills documentation · loads skills from .opencode/skills/, .claude/skills/, .agents/skills/
Install the "document-direct-python" agent skill from https://github.com/HKUDS/OpenSpace/tree/main/benchmarks/gdpval/skills/spreadsheet-direct-python-merged into .opencode/skills/document-direct-python/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "document-direct-python", 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.
document-direct-pythonUse direct Python execution for reliable document creation including spreadsheets, PDFs, and structured reports
Document Direct Python is an agent skill from HKUDS/OpenSpace. Use direct Python execution for reliable document creation including spreadsheets, PDFs, and structured reports
Its SKILL.md is about 2.7k 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 and PDF. It works with Python. The repository describes itself as: "OpenSpace: The Skill Management Layer for AI Agents" -- https://open-space.cloud/. The licence is MIT.
4 steps, taken from the first numbered list in SKILL.md.
Read from SKILL.md and the folder at commit 3827781. It shows what the files ask for, not the result of running them.
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.
Shell commands in SKILL.md call:
python3From the folder's file list and the shell code blocks in SKILL.md.
No URLs in SKILL.md.
From URLs in SKILL.md, links to its own repository left out.
Names no API keys, tokens, secrets or passwords.
From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.
Document Direct Python loads about 2.7k tokens when it runs. Until then it costs about 34 tokens; SKILL.md has 766 words of instructions outside code blocks.
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.
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.
The full file from HKUDS/OpenSpace at commit 3827781, republished under its MIT licence (© HKUDS). 766 words, ~2,722 tokens.
.claude/skills/document-direct-python/SKILL.md (or your agent's skills folder). This skill also uses 1 other file; get the full folder from GitHub.Use direct run_shell with Python scripts for document operations when:
openpyxl, pandas, reportlab, FPDF, or similar librariesThe shell_agent tool can:
Direct run_shell with Python is more reliable because it:
.py files first avoids shell_agent parsing issues with heredocsWhen web research tools (search_web, read_webpage) fail or return 'unknown error':
run_shell pattern to generate documents even without web-sourced content.Example contingency workflow for pharmacy compliance:
# When web research fails, proceed with established regulatory knowledge
from reportlab.lib.pagesizes import letter
from reportlab.pdfgen import canvas
checklist_items = [
"Verify pharmacist license is current and displayed",
"Maintain controlled substance inventory logs",
"Ensure proper storage temperatures for medications",
"Keep patient counseling records for controlled substances",
"Display required pharmacy signage and notices"
]
# Generate PDF using these standard compliance itemsThis approach was successfully used in task 045aba2e-4093-42aa-ab7f-159cc538278c_phase2 where all web tools failed but pharmacy compliance PDFs were still created successfully.
For complex multi-line scripts, especially when using shell_agent as executor:
# Step 1: Write the Python script to a file
cat > generate_document.py << 'EOF'
import openpyxl
from openpyxl import Workbook
# Your document code here
wb = openpyxl.load_workbook('file.xlsx')
# ... operations ...
wb.save('output.xlsx')
print('Success')
EOF
# Step 2: Execute the script
python3 generate_document.pyFor short, simple scripts when NOT using shell_agent as the executor:
python3 << 'EOF'
import pandas as pd
df = pd.read_excel('input.xlsx')
df.to_excel('output.xlsx', index=False)
print('Done')
EOFWrite to file first, then execute:
import pandas as pd
# Load data from specific sheet
df = pd.read_excel('input.xlsx', sheet_name='Revenue')
# Apply transformations
df['Net_Revenue'] = df['Gross_Revenue'] * (1 - df['Tax_Rate'])
# Save results
df.to_excel('output.xlsx', index=False, sheet_name='Processed')from openpyxl import load_workbook
wb = load_workbook('tour_data.xlsx')
# Iterate through sheets
for sheet_name in wb.sheetnames:
ws = wb[sheet_name]
# Apply formatting or calculations
for row in ws.iter_rows(min_row=2, max_col=5):
# Process cells
pass
wb.save('tour_data_processed.xlsx')Write to file first, then execute:
from reportlab.lib.pagesizes import letter
from reportlab.pdfgen import canvas
from reportlab.lib.units import inch
def create_checklist(filename, items):
c = canvas.Canvas(filename, pagesize=letter)
width, height = letter
# Title
c.setFont("Helvetica-Bold", 20)
c.drawString(1*inch, height - 1*inch, "Task Checklist")
# Items
c.setFont("Helvetica", 14)
y_position = height - 1.5*inch
for i, item in enumerate(items, 1):
checkbox = "☐" # Empty checkbox
c.drawString(1*inch, y_position, f"{checkbox} {item}")
y_position -= 0.3*inch
c.save()
print(f"Created {filename} with {len(items)} items")
# Usage
items = ["Review requirements", "Complete analysis", "Submit report", "Follow up"]
create_checklist("checklist.pdf", items)from fpdf import FPDF
class PDF(FPDF):
def header(self):
self.set_font('Arial', 'B', 15)
self.cell(0, 10, 'Monthly Report', 0, 1, 'C')
self.ln(10)
def footer(self):
self.set_y(-15)
self.set_font('Arial', 'I', 8)
self.cell(0, 10, f'Page {self.page_no()}', 0, 0, 'C')
def create_report(filename, data):
pdf = PDF()
pdf.add_page()
pdf.set_font('Arial', '', 12)
# Add content
for section, content in data.items():
pdf.set_font('Arial', 'B', 12)
pdf.cell(0, 10, section, 0, 1)
pdf.set_font('Arial', '', 12)
pdf.multi_cell(0, 8, content)
pdf.ln(5)
pdf.output(filename)
print(f"Report saved to {filename}")
# Usage
data = {
"Executive Summary": "This report covers Q4 performance metrics.",
"Key Findings": "Revenue increased by 15% compared to Q3.",
"Recommendations": "Continue current strategy with minor adjustments."
}
create_report("report.pdf", data)import pandas as pd
from reportlab.lib.pagesizes import letter
from reportlab.pdfgen import canvas
from reportlab.platypus import SimpleDocTemplate, Table, TableStyle
from reportlab.lib import colors
# Step 1: Process spreadsheet data
df = pd.read_excel('sales_data.xlsx')
summary = df.groupby('Region')['Revenue'].sum().reset_index()
# Step 2: Generate PDF report
doc = SimpleDocTemplate("sales_report.pdf", pagesize=letter)
elements = []
# Create table from data
data = [['Region', 'Revenue']]
for _, row in summary.iterrows():
data.append([row['Region'], f"${row['Revenue']:,.2f}"])
table = Table(data)
table.setStyle(TableStyle([
('BACKGROUND', (0, 0), (-1, 0), colors.grey),
('TEXTCOLOR', (0, 0), (-1, 0), colors.whitesmoke),
('ALIGN', (0, 0), (-1, -1), 'CENTER'),
('GRID', (0, 0), (-1, -1), 1, colors.black),
]))
elements.append(table)
doc.build(elements)
print("PDF report generated successfully")Write to file first, then execute:
import sys
from openpyxl import load_workbook
try:
wb = load_workbook('data.xlsx')
ws = wb.active
# Your operations here
value = ws['A1'].value
wb.save('output.xlsx')
print(f"Success: Processed {ws.max_row} rows")
except Exception as e:
print(f"Error: {str(e)}", file=sys.stderr)
sys.exit(1).py file first, then execute via run_shell| Library | Best For |
|---|---|
openpyxl | Reading/writing .xlsx files, formatting, formulas |
pandas | Data manipulation, analysis, merging datasets |
xlrd | Reading older .xls files (read-only) |
xlsxwriter | Creating new .xlsx files with advanced formatting |
| Library | Best For |
|---|---|
reportlab | Professional PDF reports with complex layouts |
FPDF | Simple PDF generation with basic formatting |
PyPDF2 / pypdf | Reading, merging, splitting existing PDFs |
pdfplumber | Extracting text and tables from PDFs |
Issue: Heredoc syntax fails with 'unknown error' when using shell_agent
.py file first, then execute it with python3 script.py. This pattern is significantly more reliable than inline heredoc execution when shell_agent is the executor.Issue: FileNotFoundError
os.getcwd() to check current directory if needed.Issue: PermissionError
Issue: MemoryError on large files
chunksize parameter. For PDFs, generate in sections and merge.Issue: Formatting not applying
.copy() for style objects in openpyxl.Issue: PDF text rendering issues
DejaVuSans for Unicode support in reportlab).Issue: Agent fails before first iteration (0 steps)
© HKUDS, MIT. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file
SKILL.md and 1 other file in benchmarks/gdpval/skills/spreadsheet-direct-python-merged of HKUDS/OpenSpace.
Open the folder on GitHubat commit 3827781
Document Direct Python 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.
| Skill | Stars | Used in | Tokens | Auto-check | Licence | Repo updated |
|---|---|---|---|---|---|---|
| Document Direct Python this skillHKUDS/OpenSpace | 7.7k | — | ~2.7k | Automated safety check: Pass | MIT | |
| Instrument Data To Allotropeaws-samples/amazon-bedrock-agents-healthcare-lifesciences | 274 | 2 repos | ~2.7k | Automated safety check: Pass | Apache-2.0 | |
| Doc Cleanernotoriouslab/doc-cleaner | 309 | — | ~712 | Automated safety check: Pass | MIT | |
| MineruNebutra/MinerU-Skill | 122 | — | ~504 | Automated safety check: Pass | MIT | |
| Office To Mdshuyu-labs/WebCode | 278 | — | ~1k | Automated safety check: Notes | Custom licence | |
| Exam IngestZeKaiNie/universal-examprep-skill | 301 | — | ~5.6k | Automated safety check: Pass | MIT |
aws-samples/amazon-bedrock-agents-healthcare-lifesciences
Convert laboratory instrument output files (PDF, CSV, Excel, TXT) to Allotrope Simple Model (ASM) JSON format or flattened 2D CSV.
notoriouslab/doc-cleaner
Convert PDF, DOCX, XLSX, and text files to clean, structured Markdown.
Nebutra/MinerU-Skill
An AI-Native skill for parsing PDF / Office / image files into Markdown with MinerU — a fast, zero-config document parser for AI agents.
shuyu-labs/WebCode
Convert Office documents (Word, Excel, PowerPoint, PDF) to Markdown format.
ZeKaiNie/universal-examprep-skill
从学生上传的课件/大纲/老师勾的重点/真题,一键初始化并验证备考工作区:解析 PDF、DOCX、PPTX、 XLSX、常见独立图片与 txt/md,建立分章节 LLM Wiki、标准题库、结构化接管队列与进度状态;仅在 Python 确实无法运行时 明确降级为手动写盘。当工作区尚未建立、资料发生变化、或建库 readiness 被阻断时使用。
doccker/cc-use-exp
当实现用户驱动的大文件导出或批量序列化(Excel/CSV/JSON/JSONL/PDF,数据量未知或超过 1 万行/10 MB)时触发;普通小文件下载、静态资源下载、非导出 Writer/Report 类不触发。防止 OOM、临时文件残留、同步导出阻塞 HTTP 线程和表格公式注入。
HKUDS/OpenSpace
Walks through producing a master audio track plus stems in Python, from checking a reference file and timing sections by BPM to effects, a zip archive and final verification.
HKUDS/OpenSpace
Handle cascading data retrieval tool failures by falling back to embedded knowledge generation
HKUDS/OpenSpace
Gives an agent a workaround when its code-execution sandbox keeps failing: save the Python script to a file and run it through the shell instead.
HKUDS/OpenSpace
A recovery routine for agents whose sandboxed code runner keeps failing: save the Python script to disk, then run it through the shell and read the output.
HKUDS/OpenSpace
Fallback ladder for failed sandboxed code runs, plus the habit of fixing the working directory first so generated files land in the right place.
HKUDS/OpenSpace
Fallback workflow for executing Python code when executecodesandbox fails repeatedly
Works with
Categories
Use direct Python execution for reliable document creation including spreadsheets, PDFs, and structured reports. Document Direct Python is an agent skill from HKUDS/OpenSpace.
Document Direct Python fits situations like: tasks that involve Excel spreadsheets; tasks that involve PDF.
Run `npx skills add HKUDS/OpenSpace --skill document-direct-python -a claude-code`. Or copy the skill folder (benchmarks/gdpval/skills/spreadsheet-direct-python-merged in HKUDS/OpenSpace) into .claude/skills/document-direct-python in your project. Claude Code loads it when a task matches its description.
Run `npx skills add HKUDS/OpenSpace --skill document-direct-python -a codex`. Or copy the skill folder (benchmarks/gdpval/skills/spreadsheet-direct-python-merged in HKUDS/OpenSpace) into .agents/skills/document-direct-python in your project. Codex loads it when a task matches its description.
Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add HKUDS/OpenSpace --skill document-direct-python -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/document-direct-python, .gemini/skills/document-direct-python, .github/skills/document-direct-python and .opencode/skills/document-direct-python in your project.
Going by SKILL.md and its folder, Document Direct Python needs the command-line tools its instructions call (python3). Our summary lists: Python 3.
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.
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.
Document Direct Python is published under the MIT licence (the repository's licence). It allows redistribution, so the full SKILL.md is shown on this page.
About 2.7k tokens (SKILL.md is roughly 11k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full.
Skills that share tags, products or a category with Document Direct Python: Instrument Data To Allotrope (aws-samples/amazon-bedrock-agents-healthcare-lifesciences, 274 stars), Doc Cleaner (notoriouslab/doc-cleaner, 309 stars), Mineru (Nebutra/MinerU-Skill, 122 stars) and Office To Md (shuyu-labs/WebCode, 278 stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.
HKUDS (a GitHub organization) maintains it in HKUDS/OpenSpace, which has 7,743 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.