How maluramichael/awesome-reverse-engineer-anything works
This repository is a curated directory of reverse-engineering projects, with scripts that accept submissions, discover candidates, refresh repository metrics, and generate the published README. The main reader workflow is README browsing; the maintainer workflow runs from candidate discovery or project submission through review and list data to the generated directory. The graph reflects calls visible in sampled scripts and documented README behavior; workflow triggers and some storage wiring were not inspected.
Main entry points: refresh.py Metrics refresh · discover.py Candidate discovery · add_from_issue.py Issue submission · github.py GitHub API client
Components 16
Catalog and publishing
- Project directory
README.md - Project records
data/projects - Shared data model
scripts/common.py - README generator
scripts/build_readme.py
Submission and discovery
- Issue submission
scripts/add_from_issue.py - Candidate discovery
scripts/discover.py - Review report
- Human review
Metrics and GitHub
- GitHub API client
scripts/github.py - Repository scoring
scripts/scoring.py - Metrics refresh
scripts/refresh.py - Repository stats
data/stats.json - Star history
data/history.json
Other components
- List reader
- Maintainer
- GitHub
Connections 22
- List reader → Project directory: browses
README.md - Maintainer → Issue submission: submits project
README.md - Issue submission → Shared data model: validates with
scripts/add_from_issue.py - Issue submission → GitHub API client: checks repository
scripts/add_from_issue.py - Issue submission → Project records: writes record
scripts/add_from_issue.py - Maintainer → Candidate discovery: runs search
scripts/discover.py - Candidate discovery → Shared data model: loads list data
scripts/discover.py - Candidate discovery → GitHub API client: searches repositories
scripts/discover.py - Candidate discovery → Repository scoring: scores candidates
scripts/discover.py - Candidate discovery → Review report: writes report
scripts/discover.py - Review report → Human review: presents candidates
- Human review → Project records: selects entries
- GitHub API client → GitHub: requests metadata
scripts/github.py - Maintainer → Metrics refresh: runs refresh
scripts/refresh.py - Metrics refresh → Shared data model: loads and saves
scripts/refresh.py - Metrics refresh → GitHub API client: fetches repository data
scripts/refresh.py - Metrics refresh → Repository scoring: scores health
scripts/refresh.py - Metrics refresh → Repository stats: writes metrics
scripts/refresh.py - Metrics refresh → Star history: updates snapshots
scripts/refresh.py - Maintainer → README generator: generates directory
scripts/build_readme.py - README generator → Shared data model: loads catalog data
scripts/build_readme.py - README generator → Project directory: renders
scripts/build_readme.py