Composio
Customize tool schemas before agents see them
Composio’s schema modifiers let you rewrite a tool’s schema before it reaches an agent. Use them to adjust descriptions, add or hide parameters, and set defaults when the raw tool schema needs guardrails.
Is this your tool? Claim this listing to manage your content and analytics.
Ask about Composio
Get answers based on Composio's actual documentation
Try asking:
About
Schema Modifiers are a Composio SDK middleware feature for developers building agents with external tools. They sit between your tool registry and the agent, letting you change how a tool appears before the model decides whether and how to use it.
The docs show Python and TypeScript examples, so setup is code-first through the Composio SDK. According to the documentation, this is mainly useful when you want to guide tool usage, reduce mistakes, or adapt a tool schema to a specific workflow.
This is not a standalone agent product; it is a low-level customization layer for Composio tool schemas. It can help when an agent needs clearer instructions or when certain arguments should be required, removed, or given defaults, but it does not itself provide autonomy beyond the surrounding agent setup. The docs also note that if you are building an agent, Composio recommends using sessions instead, since sessions handle tool discovery and execution automatically.
Pricing, deployment model, and model support are not stated on this page. The content also does not mention MCP support or whether the feature is open source. If you are looking for a no-code agent builder or a finished end-user assistant, this is probably not the right fit; it is aimed at developers working directly with tool schemas.
Responds to prompts but takes no autonomous action.
Dimension Breakdown
Categories
Ask about Composio
Try asking:
Pricing not publicly available
Related Tools
Agent Infrastructure
Anyscale is a fully managed Ray platform that removes the infrastructure work from building and deploying AI applications. It helps teams run Ray jobs, services, and workflows with autoscaling, monitoring, and API-driven cluster management.