| name | deep-research-okf-normalize |
| description | Normalize raw deep research outputs into a compact Open Knowledge Format bundle with source, finding, uncertainty, method, index, and log concepts. Use after provider runs when reports need portable structured markdown and citation-preserving validation. |
OKF Normalize Research
Use this skill after a deep research agent returns a report. It turns a raw
report into a portable markdown bundle aligned with Google's Open Knowledge
Format draft: markdown files with YAML frontmatter, a required type field,
optional index.md and log.md, and citations preserved as links where
possible.
Command
python .agents/skills/deep-research-okf-normalize/scripts/normalize_to_okf.py \
--input benchmark/results/perplexity-sonar/meta/q1_output.txt \
--bundle-dir benchmark/results/okf/perplexity-sonar-meta
For ad-hoc text:
python .agents/skills/deep-research-okf-normalize/scripts/normalize_to_okf.py \
--title "Deepresearch the deepresearchers" \
--text "Paste or pipe the report text here" \
--bundle-dir outputs/okf/deepresearchers
Bundle Shape
The generated bundle contains:
index.md - progressive-disclosure entrypoint.report.md - the normalized source report concept.findings.md - extracted claim bullets and citation-bearing lines.uncertainties.md - caveats, conflicts, missing evidence, and stale-data
risks.method.md - provider, prompt, timestamp, and normalization notes.log.md - update history.
Validation
python .agents/skills/deep-research-okf-normalize/scripts/validate_okf.py \
benchmark/results/okf/perplexity-sonar-meta
Normalization Rules
- Preserve raw claims before improving prose.
- Keep citations as markdown links or source URLs.
- Mark assumptions separately from measurements or cited facts.
- Prefer concise concept files over one large report.
- Do not reject unknown frontmatter fields when consuming an OKF bundle.
