ve-evidence-auditorlisted

Audit value-engineering AI Skill claims against concrete evidence links, review status, and honest wording boundaries. Use when preparing resumes, portfolios, project reports, best-practice documents, release notes, or management summaries that must distinguish verified work, submitted PRs, pending reviews, assumptions, and claims that should not be made.
onyx679/automotive-ve-ai-skills-kit · ★ 0 · Code & Development · score 72

Install: claude install-skill onyx679/automotive-ve-ai-skills-kit

# VE Evidence Auditor Use this skill to turn project claims into an evidence-backed claim matrix before publishing them in a resume, portfolio, report, or internal best-practice document. ## Inputs Accept any of: - Resume bullets or project descriptions. - GitHub repositories, releases, pull requests, issues, CI runs, or portfolio pages. - Work logs, adoption reports, Skill outputs, SOPs, and demo artifacts. - A CSV claim ledger with `claim`, `source_kind`, `evidence_level`, `verdict`, `evidence_status`, `evidence_url`, `resume_wording`, and `boundary`. ## Workflow 1. Break the text into atomic claims. Each claim should assert one thing only. 2. Attach a concrete evidence URL or file path to every claim. 3. Grade the source: - `source_kind`: `platform-record`, `repository-artifact`, `third-party`, `self-reported`, or `mixed`. - `evidence_level`: `L4` for directly checkable platform/repository records; `L3` for multiple independent sources; `L2` for one credible third-party source; `L1` for self-reported or weak evidence. - `verdict`: `confirmed`, `largely-credible`, `doubtful`, or `debunked`. 4. Mark evidence status: - `verified`: public link or local artifact proves the claim. - `open`: submitted but not merged, approved, or accepted. - `pending-review`: waiting for maintainer, manager, or business review. - `missing`: no evidence yet. 5. Classify claim level: - `resume-ready`: verified evidence exists and wording is not overstated. - `bounda