| *Last synthesized: 2026-10-14 | 31 files | 6 concept pages | offline, zero tokens* |
Raw sources -> readmenator wiki -> links (Karpathy LLM Wiki Pattern, deterministic). Start here, then open one community page. Prefer grep over full reads.
The codebase centres on _config.py, _deploy.py, _models.py. Architecturally it is 4 layers, dominant utility (15 files) across 6 import-based communities. Recorded risk surface: 0 security findings and 0 dependency cycles.
Surprising tissue lives between deploynator: _changelog, deploynator: _toml, deploynator: _models: 9 extracted cross-community imports and 10 inferred bridges. Follow connections.json sorted by strength before refactoring.
Open work clusters around documentation (29% file coverage), 0 security findings, 20 taint paths, and 5 suggested exploration questions in queries.md.
| Metric | Value |
|---|---|
| Files | 31 |
| Symbols | 381 |
| Resolved imports | 174 |
| Languages | py, sh |
| Communities | 6 |
| Doc coverage | 29% (9/31 files) |
| Security findings | 0 |
| Estimated read cost | ~3553 tokens (chars/4, offline so $0) |
queries.md for the next question; log the answer there.grep -rn '<keyword>' index.md community_*.md
readmenator query "<question>" --target deploynator
| File | Score |
|---|---|
deploynator/_config.py |
44.6 |
deploynator/_deploy.py |
33.9 |
deploynator/_models.py |
30.7 |
deploynator/_toml.py |
20.4 |
deploynator/_app.py |
17.1 |
connections.json is machine-readable for GraphRAG pipelines.REPORT.md states what was extracted vs inferred and current limits.readmenator . --rebuild (no network, no tokens).