Turn a vague success claim into one sourced metric, then blur a client name lacking permission.
Forces AI agents to verify every factual claim through live search before output — attaching [SPECULATION] and [UNVERIFIABLE] labels to anything unconfirmed, so fabricated URLs, outdated numbers, and invented citations become visible instead of silent.
Your backtest looks strong. But can you trust the evidence behind it? Check for holdout contamination, time leakage, cost-stress failures, concentration risk, and reproducibility issues — before you rely on the result.
Find, verify, compare, and select open-source AI projects with live read-only Radar evidence, explicit constraints, license checks, alternatives, and candidate stack planning.
Turn pasted AI evaluation cases into an evidence-bounded triage brief that separates expected and observed behavior, hypotheses, and missing checks without claiming a root cause or fix.
Find live creator and editorial topics from a global Radar, then turn one into an evidence-backed brief with research questions, must_verify, avoid_claims, and visual requirements.
This Skill is built on practical expertise in claim-evidence mapping, source authority labeling, quote verification, citation hygiene, recency checks, and hallucination-risk control. It helps AI agents turn research, reports, summaries, briefs, and marketing drafts into auditable claim ledgers where every important claim is matched to a source, date, quote/paraphrase boundary, and confidence label.
