Carry your voice into ChatGPT, Claude and your agents

A style prompt is still only an instruction

Telling a model to be “direct, human and punchy” describes almost nobody. Thousands of prompts share those adjectives, and every model interprets them differently.

A portable identity starts with examples owned by the author, then turns their patterns into observable instructions. The prompt translates the reference; it does not create it.

Three layers reduce dependence on one model

Portability works when tools change while the operating contract stays stable.

• the reference: texts and traits defining the intended voice;
• the instruction: a version ChatGPT, Claude or an agent can apply;
• the check: measurement of the result against the same reference.

Measurement closes the loop

Without a check, a voice drifts quietly: one model smooths the vocabulary, another adds transitions, and an agent summarises too aggressively. The output stays acceptable but gradually becomes interchangeable.

Through the API or MCP server, an agent can review its output with the same measurement as Kaneme Studio. It receives a verdict, named gaps and a path to correction rather than a promise of fidelity.