| name | aims-okf-site |
| description | Generate Hugo shadow content from OKF and troubleshoot Hugo publication. |
| disable-model-invocation | false |
AIMS OKF site generation
Run uv run python tools/okf_hugo_adapter.py --src okf --dst content/knowledge --clean, then hugo --gc --minify. Keep content/results/ and content/knowledge/ separate in URLs and navigation.
AIMS paths and commands
- Canonical OKF source:
okf/
- Generated Hugo shadow content:
content/knowledge/
- Daily report output:
content/results/
- Numeric analysis artifacts:
data/analysis/*.json
- Generate:
uv run python tools/okf_hugo_adapter.py --src okf --dst content/knowledge --clean
- Check:
uv run python tools/okf_hugo_adapter.py --src okf --dst content/knowledge --check
- Build:
hugo --gc --minify
Guardrails
- Do not let LLM-authored OKF prose become the source of truth for scores, ranks, dates, prices, risk gates, or data availability.
- Do not hand-edit
content/knowledge/; regenerate it from okf/.
- Keep custom code small and deterministic.
OKF primary references