Skill lifecycle

A skill joins the request when the model reads it, and it leaves when newer reads push it out.

A conversation has one transcript, and it is shared by every skill. At most maxLoadedSkills skills (default 3) are loaded; reading one more unloads the least recently used. The table says what happens to a skill’s parts when it unloads:

Part	When the skill unloads
Its instructions and text	Leave `<current_context>`
Its tools	Leave the request. A call of a tool that is not rendered, for this or any other reason, is refused with `Unknown tool`, and the model reads that
Its `useState` and refs	Gone: the component unmounts, and reading the skill again starts from its initial state
Its `createAgentStore` state	Stays, and is there when the skill is read again
Its tool calls and results in the transcript	Stay, including the `contextChanged` lines
What the caller and the agent said while it was active	Stay

Every loaded skill’s tools work, not only the active skill’s. The active skill is the one read last; reading a loaded skill again makes it active. No tool leaves a skill: a skill stays loaded until newer reads push it out.

So tools and instructions unload with a skill, and history does not. A later skill can read what an earlier skill’s tools returned, and the first 200 characters of each line that skill added to the context, until those messages leave the window.

Context per skill

There is no context per skill: no skill has a transcript of its own, and no setting hides history from a skill. What you can scope per skill is what the tree renders: instructions, text, tools and providers.

If a value must not reach a later part of the conversation, keep it out of the transcript: do not return it from a tool, and do not render it as text that a tool call adds. Hold it in a store or in your own system, and let a tool act on it.

How much history the model reads

maxTranscriptMessages (default 60) caps the transcript in each request. It counts messages, not turns or characters: a tool call and its result are two messages, so a tool-heavy call uses the window faster. The oldest messages leave first, whichever skill they came from, and the window always starts at a user message, so no tool result loses its call. Nothing is summarized.

The full transcript is still recorded; only the model’s window is capped. <current_context> is outside the cap, so what is rendered is always there.

Next steps

State and conditional tools: keep what must survive in a store.
What the model receives: the real requests.