Tools & Scripts Reference

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Overview

The project includes 15 active scripts and tools, plus 11 archived tools. Scripts in scripts/ handle the core data pipeline (PDF extraction through HTML generation). Tools in tools/ handle GitHub integration, validation, and reporting.

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Core Scripts (scripts/)

extract_pdf.py

• Purpose: Extract all text, tables, and structure from the Innosuisse application PDF
• Input: Application/ folder (PDF file)
• Output: data/extracted_content.json (587 KB, 42 pages, 13 sections, 140 tables)
• Usage: python scripts/extract_pdf.py
• Dependencies: pdfplumber

generate_project_plan.py

• Purpose: Generate month-by-month project plan from extracted PDF data
• Input: data/extracted_content.json
• Output: docs/generated_project_plan.md, data/project_plan_data.json
• Usage: python scripts/generate_project_plan.py
• Notes: Uses work package definitions from PDF Section 5

generate_execution_jsons.py

• Purpose: Create 24 individual monthly execution JSON files with tasks, deliverables, risks
• Input: data/project_plan_data.json
• Output: execution/M01_January2026.json through execution/M24_December2027.json
• Usage: python scripts/generate_execution_jsons.py
• Notes: Generates 314 tasks across 24 months

generate_dashboard.py

• Purpose: Generate interactive HTML dashboard from execution JSONs
• Input: execution/M01-M24 JSON files
• Output: execution/dashboard.html
• Usage: python scripts/generate_dashboard.py

update_wiki.py

• Purpose: Update wiki.html with Project/Plan/Application tabbed views
• Input: data/ JSONs, docs/, deliverables/
• Output: web/wiki.html
• Usage: python scripts/update_wiki.py

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GitHub Integration Tools (tools/)

add_to_project.py

• Purpose: Add all GitHub issues to a GitHub Project board
• Input: GitHub API (requires gh CLI)
• Output: Issues added to project board
• Usage: python tools/add_to_project.py

consolidate_by_partner.py

• Purpose: Create consolidated GitHub issues (2 per month: FHGR + Wecan = 48 total)
• Input: Execution JSON files
• Output: 48 GitHub issues with task checklists
• Usage: python tools/consolidate_by_partner.py
• Notes: Includes retry with exponential backoff

fetch_progress.py

• Purpose: Fetch task completion progress from GitHub issues
• Input: GitHub API (48 consolidated issues)
• Output: data/progress_snapshot.json
• Usage: python tools/fetch_progress.py
• Config: GITHUB_REPO env var (default: wecangroup/wecan-innosuisse-ai)

sync_to_project.py

• Purpose: Sync all issues to GitHub Project board (only adds missing ones)
• Input: GitHub API
• Output: Issues synced to project
• Usage: python tools/sync_to_project.py

update_github_issues.py

• Purpose: Update GitHub issues with enhanced execution data (M19-M24)
• Input: Execution JSON files
• Output: Updated GitHub issues with dependency info and risk summaries
• Usage: python tools/update_github_issues.py

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Reporting Tools (tools/)

generate_monthly_report.py

• Purpose: Generate pre-filled monthly status report from progress data
• Input: data/progress_snapshot.json
• Output: reports/YYYY-MM_progress_report.md
• Usage: python tools/generate_monthly_report.py [month_number]

generate_progress_dashboard.py

• Purpose: Generate HTML progress dashboard from snapshot data
• Input: data/progress_snapshot.json
• Output: web/progress.html
• Usage: python tools/generate_progress_dashboard.py

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Validation Tools (tools/)

validate_all_months.py

• Purpose: Comprehensive validation of all 24 execution JSONs
• Input: execution/M01-M24 JSON files, execution/schema.json
• Output: Validation report (PASS/FAIL with error details)
• Usage: python tools/validate_all_months.py
• Checks: Structural integrity, budget compliance, dependency chains, milestone criteria, deliverable assignments

enhance_execution_jsons.py

• Purpose: Enhance execution JSONs with additional detail (consolidates 4 archived scripts)
• Input: Execution JSON files
• Output: Enhanced execution JSON files
• Usage: python tools/enhance_execution_jsons.py [start_month] [end_month]

create_metainfo.py

• Purpose: Generate metainfo.txt for Quantlet metadata from Python files
• Input: Any .py file
• Output: metainfo.txt following Quantlet standards
• Usage: python tools/create_metainfo.py

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Archived Tools (tools/archive/)

11 tools that have been superseded or were single-use:

Tool	Purpose	Superseded By
create_infrastructure_issues.py	Create GitHub verification infrastructure	consolidate_by_partner.py
reimport_failed.py	Re-import failed GitHub issue imports	One-time use
enhance_m1_m6.py	Enhance months 1-6	enhance_execution_jsons.py
enhance_m7_m12.py	Enhance months 7-12	enhance_execution_jsons.py
enhance_m13_m18.py	Enhance months 13-18	enhance_execution_jsons.py
enhance_m19_m24.py	Enhance months 19-24	enhance_execution_jsons.py
fix_execution_gaps.py	Fix gaps in execution data	One-time use
update_deliverables_v190.py	Update deliverables for v1.9.0	One-time use
update_status_files.py	Update status files	One-time use
update_wiki_v190.py	Update wiki for v1.9.0	update_wiki.py
update_work_packages.py	Update work package docs	One-time use

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Pipeline Flow

The data flows through scripts in this sequence:

1. PDF Extraction: extract_pdf.py reads the Innosuisse application PDF and outputs extracted_content.json
2. Plan Generation: generate_project_plan.py converts extracted data into project_plan_data.json
3. Execution JSONs: generate_execution_jsons.py creates 24 monthly files (M01-M24)
4. Dashboard: generate_dashboard.py creates execution/dashboard.html
5. Wiki: update_wiki.py creates web/wiki.html
6. GitHub Issues: consolidate_by_partner.py creates 48 issues on GitHub
7. Progress Tracking: fetch_progress.py pulls completion data into progress_snapshot.json
8. Progress Dashboard: generate_progress_dashboard.py creates web/progress.html
9. Reports: generate_monthly_report.py creates monthly status reports

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See also: Developer Setup, Data Pipeline