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Wed, October 1423:00ToolsModel releasesMCP & SkillsAI codingModel releases guide

Claude Code Academic Research Skill Set v3.8 Adds Claim Audit

Decision Brief

What changedThe Claude Code Academic Research Skill Set (ARS) releases v3.8, adding an optional claim-audit flow that verifies whether citations actually support the claims made in a paper.
Why it mattersResearch teams using this skill set can now enable source verification with ARS_CLAIM_AUDIT=1, pulling each citation anchor to compare against the original text; claims that fail the audit are rejected outright at the formatted output, though the official team has yet to record calibration results from a real review model.
Who should careAI coding tool users
Affected stackClaude Code
Builder actionUpgrade Claude Code to v3.8
Source confidenceHigh · Official release / blog / repo

ARS v3.8 closes the second half of the gap left by v3.7.3. v3.7.3 already made each citation carry a locator anchor; v3.8 adds an optional audit (ARS_CLAIM_AUDIT=1) that fetches cited sources by anchor and judges whether the claim is truly supported by that source. Five new high-warning classes are introduced—unsupported claim, negative-constraint violation, fabricated citation, missing anchor, and uncited-constraint violation—rejected outright by the formatting terminal's hard gate. It also ships a calibration runner and a 25-item synthetic gold set, with acceptance thresholds of FNR<0.15 and FPR<0.10. For researchers and developers using this skill set, this means citation authenticity checking moves from "anchor tagging only" to "optional automatic comparison," which users can enable or not after installing. Note that the repo drives tests with a stub reviewer that returns gold labels, validating only the toolchain itself; calibration results from a real review model are not yet recorded, and the official team says its rollout plan is waiting on that result.

Summary basis: full article readCompiled from the source scope noted above; the original remains authoritative.

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