What problem does it solve? When an AI writes answers or reports based on fetched web content, it can hallucinate URLs or attribute claims to sources that never said them. This Skill eliminates that risk by keeping a persistent ledger that owns the URL-to-number mapping, so the model only ever emits small integer ids it was handed at retrieval time, and every citation can be mechanically verified against the ledger. ## Core Features & Use Cases - Citation Ledger: Registers URLs at retrieval time with stable, idempotent numbering, then renders Sources blocks in markdown, plain, footnotes, bibtex, or evidence styles. - Draft Verification: Checks that every [n] in a draft exists in the ledger, that the Sources block matches, and that citation coverage meets a configurable threshold. - Fact-Checking Mode: Attaches verbatim quotes to sources (rejected unless they literally appear in the fetched page text) and fails drafts whose cited sources carry no evidence. - Use Case: While writing a market research report from web searches, Reddit threads, and RSS feeds, register each URL as you fetch it, cite claims inline as [1][2], then run verify before delivering so no fabricated or mismatched citation reaches the reader. ## Quick Start Ask the agent to research a topic across the web and write a cited report, registering every fetched source in the citation ledger and verifying the draft before delivery.
