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Grant Budget Justification

该 Skill 提供命令行工具，读取预算条目文件（JSON/CSV），按设备、人员、其他等说明类型以及 NIH/NSF 机构要求生成叙述性预算说明，支持文本、Markdown、docx 输出。脚本本地执行并读写工作区文件，声明不调用外部 API。当前为 Draft 状态，未给出具体模板与评分依据。

aipoch-ai
aipoch-ai
热度 80.95
最近更新 2026-05-11 17:32:41
分类：效率依赖：代码执行 / 读写文件应用场景：财务 / 研究 / 报告撰写

安装技能

复制下面的话术发给你的 Agent，它会通过 secure-skills 检索并安装该技能。

执行命令安装此 skill： npx secure-skills-cli add grant-budget-justification
Metadata
name
grant-budget-justification
description
Generate narrative budget justifications for NIH/NSF applications
version
1.0.0
category
Grant
tags
[]
author
AIPOCH
license
MIT
status
Draft
risk_level
Medium
skill_type
Tool/Script
owner
AIPOCH
reviewer
last_updated
2026-02-06

Grant Budget Justification

Narrative budget explanations for grant proposals.

Use Cases

  • Equipment purchases
  • Personnel costs
  • Supplies and reagents
  • Travel and dissemination

Parameters

Parameter Type Default Required Description
--input, -i string - Yes Path to budget items file (JSON/CSV)
--justification-type string - Yes Type of justification (Equipment, Personnel, Other)
--agency string NIH No Funding agency (NIH, NSF)
--output, -o string stdout No Output file path
--format string text No Output format (text, markdown, docx)

Returns

  • Narrative justification text
  • Cost-benefit rationale
  • Compliance with agency requirements

Example

Input: $50,000 for mass spectrometer Output: Justification emphasizing essentiality and cost-sharing

Risk Assessment

Risk Indicator Assessment Level
Code Execution Python/R scripts executed locally Medium
Network Access No external API calls Low
File System Access Read input files, write output files Medium
Instruction Tampering Standard prompt guidelines Low
Data Exposure Output files saved to workspace Low

Security Checklist

  • No hardcoded credentials or API keys
  • No unauthorized file system access (../)
  • Output does not expose sensitive information
  • Prompt injection protections in place
  • Input file paths validated (no ../ traversal)
  • Output directory restricted to workspace
  • Script execution in sandboxed environment
  • Error messages sanitized (no stack traces exposed)
  • Dependencies audited

Prerequisites

No additional Python packages required.

Evaluation Criteria

Success Metrics

  • Successfully executes main functionality
  • Output meets quality standards
  • Handles edge cases gracefully
  • Performance is acceptable

Test Cases

  1. Basic Functionality: Standard input → Expected output
  2. Edge Case: Invalid input → Graceful error handling
  3. Performance: Large dataset → Acceptable processing time

Lifecycle Status

  • Current Stage: Draft
  • Next Review Date: 2026-03-06
  • Known Issues: None
  • Planned Improvements:
    • Performance optimization
    • Additional feature support