deep-research-okf-normalize

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.