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// Skill profile

Grant Gantt Chart Generator

name: grant-gantt-chart-gen

by aipoch-ai · published 2026-04-01

图像生成数据处理
Total installs
0
Stars
★ 0
Last updated
2026-04
// Install command
$ claw add gh:aipoch-ai/aipoch-ai-grant-gantt-chart-gen
View on GitHub
// Full documentation

---

name: grant-gantt-chart-gen

description: Create project timeline visualizations for grant proposals

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 Gantt Chart Generator

Create project timeline visualizations for grant proposals.

Usage

python scripts/main.py --milestones milestones.csv --duration 36 --output gantt.png

Parameters

| Parameter | Type | Default | Required | Description |

|-----------|------|---------|----------|-------------|

| `--milestones` | string | - | Yes | Path to milestone data file (CSV) |

| `--duration` | int | 36 | No | Project duration in months |

| `--start-date` | string | - | No | Project start date (YYYY-MM-DD) |

| `--output`, `-o` | string | gantt.png | No | Output file path |

| `--format` | string | png | No | Output format (png, pdf, svg) |

Features

  • Timeline visualization
  • Milestone markers
  • Task dependencies
  • Personnel allocation
  • Quarterly breakdown
  • Output

  • Gantt chart image
  • Timeline data (CSV)
  • Milestone summary
  • 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

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