spreadsheet-validated-execution

spreadsheet-validated-execution is a skill for Claude Code, Codex from HKUDS/OpenSpace. It costs 20 tokens per session (2,988 once invoked), scanned A, original, MIT.

A Python spreadsheet workflow that checks data sources before processing and records fallback options when a source cannot be used.

In plain words
What is it for?
Use it before reading or writing multi-sheet Excel files, applying formulas or formatting, or transforming spreadsheet data.
Why use it?
It prevents wasted work on missing, inaccessible, incorrectly formatted, or incomplete inputs. The checks confirm that required files and fields are available first.

Skill for Claude CodeCodex

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

Good fit Use it before reading or writing multi-sheet Excel files, applying formulas or formatting, or transforming spreadsheet data.

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Install with agentmods
npx agentmods add skills/hkuds/openspace/spreadsheet-direct-python-enhanced-enhanced
About the project

OpenSpace is a skill-management layer for AI agents that stores, retrieves, evaluates, shares, and improves reusable workflows. It is intended for people using multiple coding agents who want skills to be reused and refined based on task outcomes. The catalogue provides 200 skills for use with OpenSpace and the agents it supports.

HKUDS/OpenSpace · 7,544 stars · on GitHub

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 HKUDS/OpenSpace --skill spreadsheet-direct-python-enhanced-enhanced
Clone the repo
git clone --depth 1 https://github.com/HKUDS/OpenSpace

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 spreadsheet-validated-execution

README.md
[![agentmods](https://agentmods.dev/badge/skills/hkuds/openspace/spreadsheet-direct-python-enhanced-enhanced/github.svg)](https://agentmods.dev/skills/hkuds/openspace/spreadsheet-direct-python-enhanced-enhanced)
Your own site
<a href="https://agentmods.dev/skills/hkuds/openspace/spreadsheet-direct-python-enhanced-enhanced"><img src="https://agentmods.dev/badge/skills/hkuds/openspace/spreadsheet-direct-python-enhanced-enhanced/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 spreadsheet-validated-execution

Your own site · 80×15
<a href="https://agentmods.dev/skills/hkuds/openspace/spreadsheet-direct-python-enhanced-enhanced"><img src="https://agentmods.dev/badge/skills/hkuds/openspace/spreadsheet-direct-python-enhanced-enhanced.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 20 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 2,988 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. Third-party audits
  • NVIDIA SkillSpector pass 7 Sept 2026
How audits are shown
Origin original No closer match found 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 $0.00020 $0.02988
Opus 5 $0.00010 $0.01494
Sonnet 5 $0.00004 $0.00598
Haiku 4.5 $0.00002 $0.00299

Measured 5d ago against content hash 0dedb5ae1e77, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-08, from the pricing page.

Security

Grade A, and why

spreadsheet-validated-execution 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 5d 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.

benchmarks/gdpval/skills/spreadsheet-direct-python-enhanced-enhanced/SKILL.md · 386 lines

How it starts

The opening of the file, as written. The whole thing — 386 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Direct Python Execution for Spreadsheet Tasks

When to Use This Skill

Use this skill for spreadsheet operations that require verified source data:

  • Before processing: Verify data sources are accessible and contain expected data
  • Reading or writing complex Excel files with multiple sheets
  • Applying formulas, formatting, or data transformations
  • Working with openpyxl, pandas, or similar libraries
  • The operation involves multiple steps that could exceed agent step limits
  • You need precise control over error handling and debugging
  • Complex scripts benefit from file-based execution for better reliability

Critical: Data Source Validation First

Always validate data availability before attempting spreadsheet operations. This prevents wasted iterations on unavailable data.

Pre-Execution Validation Checklist

  1. Verify source accessibility: Test connection to data URLs/files before building processing scripts
  2. Confirm data format: Ensure source data matches expected structure (columns, sheets, file type)
  3. Check data completeness: Validate required fields/rows are present
  4. Identify fallback sources: Document alternative data sources if primary is unavailable

Validation Script Pattern

import sys
import os
from pathlib import Path

def validate_source(source_path, required_fields=None):
    """Validate data source before processing"""
    if not Path(source_path).exists():
        return False, f"Source file not found: {source_path}"
    
    try:
        # Check file is readable and non-empty
        if os.path.getsize(source_path) == 0:
            return False, "Source file is empty"
        
        if required_fields:
            # Validate structure using pandas
            import pandas as pd
            df = pd.read_excel(source_path, nrows=1)
            missing = set(required_fields) - set(df.columns)
            if missing:
                return False, f"Missing required columns: {missing}"
        
        return True, "Source validated"
    except Exception as e:
        return False, f"Validation error: {str(e)}"

# Usage
valid, message = validate_source('input.xlsx', ['ID', 'Date', 'Value'])
if not valid:
    print(f"ABORT: {message}", file=sys.stderr)
    sys.exit(1)
print(f"OK: {message}")

Read the full file on GitHub · 386 lines

Files

What ships with it

1 file 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. 5d ago First seen · 386 lines · 0 tokens per session scan A 0dedb5ae1e77

Subscribe to this mod's changes

spreadsheet-validated-execution is a skill published in the GitHub repository HKUDS/OpenSpace (7,544 stars, last pushed 27d ago), licensed MIT. It adds 20 tokens to every session and 2,988 once invoked, about $0.0001 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.