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+---
+title: Claude Science
+created: 2026-06-30
+updated: 2026-06-30
+type: entity
+tags: [llm, agent, automation, tool, evaluation]
+sources: [raw/articles/claude-science-ai-workbench-2026.md]
+confidence: medium
+---
+
+# Claude Science
+
+Claude Science is Anthropic's beta AI workbench for scientific research. It packages Claude as a coordinating agent inside a research environment that connects to scientific databases, packages, local or remote compute, and domain-specific skills. Unlike a general chat assistant, the product emphasizes auditable artifacts: figures, manuscripts, code, environment details, and message history are kept together so results can be validated and reproduced later.^[raw/articles/claude-science-ai-workbench-2026.md]
+
+The product is especially relevant to [[ai-research-automation]] because it turns research work into a persistent, tool-connected loop rather than a one-off answer. Claude Science can run locally on macOS/Linux or against remote machines over SSH/HPC login nodes, ask before reaching new resources, submit jobs, and fork sessions to compare approaches. A reviewer agent checks citations, calculations, untraceable numbers, and figure/code consistency, which connects the product to [[ai-evaluation-infrastructure]] and [[loop-engineering]].
+
+## Design signals
+
+- **Auditable artifacts**: outputs include the code and environment that produced them, plus plain-language explanations and message history.
+- **Compute as part of the loop**: local machines, lab infrastructure, HPC, and Modal-style on-demand compute are treated as execution targets behind explicit review/revoke decisions.
+- **Domain skills and connectors**: the beta ships with 60+ curated skills/connectors for areas such as genomics, single-cell, proteomics, structural biology, and cheminformatics.
+- **Reviewer agents**: separate critic/reviewer agents are used to catch citation and calculation errors, echoing the generator/evaluator split in [[loop-engineering]].
+
+## Open Questions
+
+- How much of the reproducibility guarantee depends on preserving exact execution environments versus preserving narrative provenance?
+- Can the reviewer-agent pattern transfer to personal wiki curation, code review, and scheduled research jobs without becoming too expensive?
+- What privacy boundary is acceptable when sensitive lab data remains local but context is still sent to a hosted model?