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Recipe Audit Report by flowleap-ai — Agent Skill

Name: Recipe Audit Report
Author: flowleap-ai

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.

flowleap-ai Updated Sep 17, 2026

File contents

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 health api    # backend apiVersion (the server build)
flowleap --json doctor        # backend, auth mode, provider-key status

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

Both versions matter for re-runnability. The CLI sends its own build as the Client version header (X-FlowLeap-Client: cli/<version>), so a later reader can tell which client produced the log; apiVersion pins the server side of the same pair.

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 — one surface, one envelope, one named tool per capability, so "which system answered this" is never a guess:

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

---name: recipe-audit-reportdescription: 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.---# Recipe: Audit Report (AI-Assisted Research)Make AI-assisted patent research verifiable: every finding traceable to acommand, every command re-runnable.## Step 1: Record the Environment```bashflowleap --versionflowleap --json health api # backend apiVersion (the server build)flowleap --json doctor # backend, auth mode, provider-key status```Record: CLI version, backend `apiVersion`, backend base URL, date/time of thesession, and the auth *mode* (OAuth session vs. API token) — **never tokenvalues or key material**.Both versions matter for re-runnability. The CLI sends its own build as the**Client version header** (`X-FlowLeap-Client: cli/<version>`), so a laterreader can tell which client produced the log; `apiVersion` pins the server sideof the same pair.## Step 2: Provenance Discipline During ResearchFor every substantive finding, log the exact command and keep the `--json`output. The Tools facade makes provenance explicit — one surface, one envelope,one named tool per capability, so "which system answered this" is never a guess:```bashflowleap --json tools list # capabilities available that dayflowleap --json tools run server_info # backend identity/version```Note per result: the source system (EPO OPS, USPTO ODP, OpenAlex, SemanticScholar, 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 ClaimsAny statement like "patent X is in force" must be backed by a dated check:```bashflowleap --json summary <patent-number> # legal status + family + termflowleap --json timeline <patent-number> # event history behind the status```## Step 4: Reproducibility PassRe-run the load-bearing commands at report time and diff against theoriginal outputs. Patent registers move — note any finding that changedbetween research and reporting, with both dates.## Step 5: AI-Usage Disclosure SectionState 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 dateFor filings, check the current duty-of-disclosure guidance:```bashflowleap --json legal search "duty of candor AI assisted tools" --jurisdiction uspto```## Visual deliverableIf the research being audited produced a `recipe-custom-dashboard` bundle,cite it rather than re-deriving its numbers: the bundle's own provenancefooter and reproduce block already meet this recipe's Verified-Data Contractbar (sources, parameters, Data Edition where applicable, timestamps),so Steps 1–4 can point at that bundle instead of re-collecting the sameevidence 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

Frequently asked questions