CtrlK
BlogDocsLog inGet started
Tessl Logo

grant-gantt-chart-gen

Create project timeline visualizations for grant proposals

Install with Tessl CLI

npx tessl i github:aipoch/medical-research-skills --skill grant-gantt-chart-gen
What are skills?

41

Does it follow best practices?

Validation for skill structure

SKILL.md
Review
Evals

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

ParameterTypeDefaultRequiredDescription
--milestonesstring-YesPath to milestone data file (CSV)
--durationint36NoProject duration in months
--start-datestring-NoProject start date (YYYY-MM-DD)
--output, -ostringgantt.pngNoOutput file path
--formatstringpngNoOutput 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 IndicatorAssessmentLevel
Code ExecutionPython/R scripts executed locallyMedium
Network AccessNo external API callsLow
File System AccessRead input files, write output filesMedium
Instruction TamperingStandard prompt guidelinesLow
Data ExposureOutput files saved to workspaceLow

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
Repository
aipoch/medical-research-skills
Last updated
Created

Is this your skill?

If you maintain this skill, you can claim it as your own. Once claimed, you can manage eval scenarios, bundle related skills, attach documentation or rules, and ensure cross-agent compatibility.