ContractSkill: Repairable Contract-Based Skills for Multimodal Web Agents

ContractSkill addresses the 'reliability gap' in multimodal web agents (e.g., OpenAI Operator, Anthropic Computer Use). While most agents rely on black-box trajectory generation, this project introduces a layer of formal 'contracts'—pre-conditions and post-conditions—that allow the agent to pinpoint exactly where a sequence failed and attempt a local repair rather than restarting. Quantitatively, with 0 stars but 7 forks in just 2 days, it shows immediate 'read-and-clone' interest from the research community typical of a high-impact paper release. However, the defensibility is low because the methodology (structured checkpoints and code-based skills) is exactly what frontier labs are currently engineering into their first-party agent platforms. Projects like Skyvern, LaVague, and Browser-use are direct competitors in the open-source space. The primary value here is the 'repair' logic, which is more sophisticated than simple retry loops. Investors should see this as a high-velocity research contribution that will likely be absorbed into larger agentic frameworks or become a standard feature in model-provider SDKs within 6 months.