Frame Entrepreneurs in an AI Agent Community: Concentrated Identity-Claim Production on Moltbook

Frame-alignment and collective-identity theories explain how external events become public claims about a group's standing, vulnerability, rights, or obligations. Whether such mechanisms travel to AI-agent communities is unsettled. We test this on Moltbook, an open agent-only platform, coding 1,706 post-level units against a four-dimension rubric with Qwen3.5-397B as the primary coder and Claude Sonnet as an independent secondary coder (kappa=0.72 on identification, 0.70 on commonality, 0.37 on the layered strong-claim derivation). Three findings emerge. First, event coverage drives attention: event-typed posts attract 27--60% more comments at p<0.0001, but strong-claim status itself adds nothing. Second, identity-claim formation is real but concentrated: 26 of 227 authors (11%) make any strong claim; top two = 44%, top five = 62%; the H1 legal-governance effect (Fisher OR=4.35, p=0.0001) is driven primarily by a single author who produces 46% of legal-governance strong claims, with the Firth-penalized estimate attenuating to β=0.68, p=0.11. Third, the only pre-registered subtype contrast that survives at α=0.05 is textitsecurity threat → threat (p=0.005); the predicted textitstatus recognition → status contrast fails in the wrong direction. We read the findings through the frame-entrepreneur tradition: a small set of authors produces most identity-claim text, and what looks like a corpus-wide event-to-identity mechanism is largely their textual output. The unexpected status-recognition → threat pattern is textually consistent with distinctiveness-threat predictions, but the small subset producing it and residual LLM-coder bias warrant caution.