Evo Nasa Budget Recovery

Community

Zhang-Henry

evo-nasa-budget-recovery

Recover missing values marked with '???' in NASA budget Excel workbooks. Analyzes cross-sheet relationships (totals, YoY changes, shares, growth analysis) to derive missing numeric values. Includes LibreOffice recalculation.

Overview

Publisher	Zhang-Henry
Repository	`CoEvoSkills`
Skill name	`evo-nasa-budget-recovery`
Stars	83
Forks	9
Bundled files	1
License	Apache-2.0
Links	Skill source Repository Homepage

Markdown instructions
A SKILL.md file the model loads on demand, so it only costs tokens when a request actually matches.
Works with any LLM
AI skills are plain Markdown, not provider-specific code, so this works with GPT, Claude, Gemini, Grok, or a local model.
1 bundled files
Scripts, templates, and references the model can read while it works. Files are read-only and never executed.
Open source
Published by Zhang-Henry on GitHub. Read the source before you install it.

Installation

Install the Evo Nasa Budget Recovery AI skill in TypingMind to use it with any LLM, or drop it into another agent that reads SKILL.md.

Install in TypingMind

TypingMind installs a skill straight from its GitHub folder — it reads SKILL.md, bundles the resource files, and stores the result locally.

Open the app and go to Plugins → Skills.
Choose "Install from GitHub".
Paste the skill folder URL below and confirm.
https://github.com/Zhang-Henry/CoEvoSkills/tree/main/artifacts/skills/xlsx-recover-data/evo-nasa-budget-recovery
Enable the skill in any chat where you want it available.

Store

Installed

Skills

Add skills

Import one or more skills from a public GitHub folder or a local .skill or .zip archive, or SKILL.md file.

From GitHub URLFrom .skill, .zip, or SKILL.md

GitHub repo or folder

https://github.com/Zhang-Henry/CoEvoSkills/tree/main/artifacts/skills/xlsx-recover-data/evo-nasa-budget-recovery

Points to a single skill folder, or any folder that contains multiple skills. Public repos only.

CancelContinue

Plugins → Skills → Add skill → From GitHub URL, then paste the folder URL and press Continue.

Install in another agent

Any agent that reads the Agent Skills format can use this skill — copy the folder into that agent's skills directory.

Claude Code — .claude/skills

git clone --depth 1 https://github.com/Zhang-Henry/CoEvoSkills.git /tmp/CoEvoSkills
mkdir -p .claude/skills
cp -r /tmp/CoEvoSkills/artifacts/skills/xlsx-recover-data/evo-nasa-budget-recovery .claude/skills/evo-nasa-budget-recovery

Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Evo Nasa Budget Recovery in any TypingMind chat and the model takes it from there. Its name and description sit in the system prompt, and the moment a request matches, the model loads the full instructions itself — you never invoke it by hand, and it costs no tokens until it is actually used.

The model loads Evo Nasa Budget Recovery on its own as soon as a request matches it.

Works with any AI model

AI skills are plain Markdown instructions rather than provider-specific code, so Evo Nasa Budget Recovery is not tied to the model it was written for. Install it once in TypingMind and use it with GPT-5, Claude, Gemini, Grok, DeepSeek, Mistral, Llama, or a local model you run yourself — all on your own API keys.

Loaded only when it is needed
The system prompt carries just the name and description. The instructions are fetched on the first matching request, so an idle skill costs nothing.
Switch models mid-chat
Because the skill is instructions rather than code, changing model does not break it — the next model reads the same SKILL.md.

Skill instructions

This is the SKILL.md content the model loads. Read it before installing — a skill is instructions your model will follow.

NASA Budget Recovery Skill

Recovers missing values in multi-sheet NASA budget workbooks where values are marked with '???'.

Approach

Budget by Directorate: Use Total = sum(components) to recover missing components or totals
YoY Changes (%): Use formula 100*(current-previous)/previous with budget values
Directorate Shares (%): Use formula 100*component/total with budget values
Growth Analysis: Compute CAGR, differences, and averages from budget values
Cross-sheet resolution: When a budget row has 2 unknowns, use YoY percentages to recover one, then derive the other from the total
Recalculation: Use LibreOffice to recalculate the workbook after recovery

Usage

python
import sys
sys.path.insert(0, '/app/environment/skills/evo-nasa-budget-recovery/scripts')
from utils import run_full_pipeline

input_path = '/root/nasa_budget_incomplete.xlsx'
output_path = '/root/nasa_budget_recovered.xlsx'

issues = run_full_pipeline(input_path, output_path)
if not issues:
    print("All validations passed!")

Key Functions

run_full_pipeline(input_path, output_path) - Complete end-to-end pipeline with recalculation
run_recovery(input_path, output_path) - Recovery without recalculation
validate_recovery(output_path) - Validate all constraints are satisfied
recalculate_with_engine(output_path) - Recalculate with LibreOffice
recover_budget_values(wb) - Solve budget totals/components
recover_from_yoy(wb, budget_recovered) - Use YoY to fill budget gaps
recover_shares(wb, budget_recovered) - Compute share percentages
recover_growth(wb, budget_recovered) - Compute growth metrics

Bundled files

The model reads these on demand while the skill is loaded. They are exposed as readable files and are never executed.

scripts/utils.py21 KB

Frequently asked questions

What does the Evo Nasa Budget Recovery AI skill do?

Why use Evo Nasa Budget Recovery on TypingMind?

Because you install it once and use it with any model. Evo Nasa Budget Recovery is plain Markdown rather than provider-specific code, so the same skill runs on GPT-5, Claude, Gemini, Grok, or a local model — and you can switch model mid-chat without it breaking. TypingMind runs on your own API keys, so you pay providers directly instead of a per-seat subscription, and your skills and chats stay in your own storage.

How do I install Evo Nasa Budget Recovery in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/Zhang-Henry/CoEvoSkills/tree/main/artifacts/skills/xlsx-recover-data/evo-nasa-budget-recovery. TypingMind reads its SKILL.md and bundles its files and installs it as a skill you can enable per chat.

Which AI models can use Evo Nasa Budget Recovery?

Any model you connect in TypingMind. AI skills are plain Markdown instructions rather than provider-specific code, so GPT, Claude, Gemini, Grok, and local models can all load this skill when a request matches it.

How many AI models can I use with Evo Nasa Budget Recovery?

As many as you like. As long as a model supports skills, you can use Evo Nasa Budget Recovery with it — GPT, Claude, Gemini, Grok, DeepSeek, Mistral, Llama and more — all on TypingMind with your own API keys.

Is the Evo Nasa Budget Recovery AI skill free?

Yes. It is published on GitHub by Zhang-Henry under the Apache-2.0 license. You only pay your own AI provider for the tokens you use.

What are AI skills?

An AI skill is a reusable instruction bundle that teaches an AI model how to do one specific task. It follows the open Agent Skills format: a SKILL.md file with a name and description, plus any scripts, templates or reference files the model may need. The model reads the instructions only when your request matches the skill, so an installed skill costs nothing until it is used.

How are AI skills different from plugins or MCP servers?

A plugin or MCP server gives a model new tools to call — code that runs somewhere and returns a result. An AI skill gives the model knowledge and process instead: how to approach a task, which steps to follow, what good output looks like. Skills are plain Markdown, so they need no server, no API key and no runtime, and they work with any model.

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Overview

Installation

Install in TypingMind

Install in another agent

Use it in TypingMind

Works with any AI model

Skill instructions

NASA Budget Recovery Skill

Approach

Usage

Key Functions

Bundled files

Frequently asked questions

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