Tool-output compression
Compress tool output before it becomes your agent's next prompt.
Tool output becomes model context: a test report, a cloud API response, terminal logs, or an MCP result. Tokz selects relevant source spans before the next model call, giving an agent less noise without substituting a generated summary.
import OpenAI from "openai";
import { withTokz } from "@tokz/openai";
const openai = withTokz(new OpenAI(), {
apiKey: process.env.TOKZ_API_KEY!,
});
await openai.chat.completions.create({
model: "gpt-4o",
messages: [
{ role: "user", content: "Which deployment failed?" },
{ role: "tool", tool_call_id: "call_1", content: deploymentJson },
],
});The useful part of a tool result is rarely at one position
A failure identifier may appear at the top, its error detail in the middle, and the retryable resource at the end. A selector can preserve non-contiguous material; head or middle truncation cannot make that choice.
Keep the envelope your agent relies on
Tokz integrations preserve tool-call identity, error status, non-text content blocks, and result envelopes. Structured content is only changed where a caller provides a validator and the transformed copy passes it.
Use explicit intent when the application knows it
A user question, tool name, description, and arguments can bound selection. Explicit queries take priority over derived intent, which makes the policy easier to inspect and test.
Limitations
Compression is not a prompt-injection defense and does not make untrusted data safe. Keep security controls and required-field preservation separate from the token-reduction decision.