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Recipe audit report

Skill flowleap-ai/flowleap-plugins/plugins/flowleap/skills/recipe-audit-report

Governance recipe for producing an auditable record of AI-assisted patent research — reproducible command log, data provenance for every finding, portfolio status verification, and an AI-usage disclosure section suitable for internal or filing-adjacent records. Trigger when the user asks for an audit trail of patent research, an AI-assistance disclosure, or a verifiable methodology write-up of analysis work.From its SKILL.md

Install
npx -y skills add flowleap-ai/flowleap-plugins --skill recipe-audit-report

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SKILL.md

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Recipe: Audit Report (AI-Assisted Research)

Make AI-assisted patent research verifiable: every finding traceable to a command, every command re-runnable.

Step 1: Record the Environment

flowleap --version
flowleap --json doctor        # backend, auth mode, provider-key status

Record: CLI version, backend base URL, date/time of the session, and the auth mode (OAuth session vs. API token) — never token values or key material.

Step 2: Provenance Discipline During Research

For every substantive finding, log the exact command and keep the --json output. The tools facade makes provenance explicit:

flowleap --json tools list                     # capabilities available that day
flowleap --json tools run server_info          # backend identity/version

Note per result: the source system (EPO OPS, USPTO ODP, OpenAlex, Semantic Scholar, legal RAG), the query string, limits and date filters, and the cached flag from the response envelope (cached data may lag live records).

Step 3: Verify Asset Status Claims

Any statement like "patent X is in force" must be backed by a dated check:

flowleap --json summary <patent-number>     # legal status + family + term
flowleap --json timeline <patent-number>    # event history behind the status

Step 4: Reproducibility Pass

Re-run the load-bearing commands at report time and diff against the original outputs. Patent registers move — note any finding that changed between research and reporting, with both dates.

Step 5: AI-Usage Disclosure Section

State plainly:

  • Which steps were AI-assisted (search strategy, summarization, charting) and which tool/model performed them
  • Which outputs a human verified, and how (e.g. claims read in full, legal-status events checked against the register)
  • Known limitations: search recall is not exhaustive; OCR and summarization can introduce errors; results reflect database coverage on the query date

For filings, check the current duty-of-disclosure guidance:

flowleap --json legal search "duty of candor AI assisted tools" --jurisdiction uspto

Visual deliverable

If the research being audited produced a recipe-custom-dashboard bundle, cite it rather than re-deriving its numbers: the bundle's own provenance footer and reproduce block already meet this recipe's Verified-Data Contract bar (sources, parameters, Data Edition where applicable, timestamps), so Steps 1–4 can point at that bundle instead of re-collecting the same evidence by hand.

Output

  • Environment record (versions, backend, date, auth mode)
  • Methodology section (sources, queries, filters — per finding)
  • Status-verification table with check dates
  • Command appendix: every command, in order, with output digests
  • AI-usage disclosure with human-verification points and limitations

What ships with it

Read from the repository

Just SKILL.md. No reference files, no scripts.

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