ADR-143: Bound every send against the model that actually serves it 

Context 

ADR-107 keeps an agent transcript inside the model's context window. ADR-139 recorded that only two callers used it — ConversationService and ToolLoopService — so which API a consumer happened to call decided whether a long transcript was pruned or handed to the provider whole. That is issue #688.

Reading the code turned up a second, quieter defect in the paths that DID bind a window.

ContextWindowManager::fit() sized the budget from $configuration->getLlmModel(). A criteria-mode configuration carries no model relation — model_uid = 0 — and ConfigurationCallPlanner::resolveModel() deliberately does not write the resolution back, because mutating the entity would mark it dirty and Extbase would persist model_uid, silently converting a dynamic configuration into a fixed one. So on every dynamically-selected call the manager found no model, fell back to its unknown-window default, and sized the budget against a number that had nothing to do with the model on the wire.

Decision 

The window comes from the resolved model. fit() takes the model that will actually serve the send and prefers it over the configuration's relation; the response reserve follows the same model. Passing nothing keeps the entity's model, which is the fixed-mode case and the behaviour every existing caller had.

Every configuration-driven send of a transcript is bounded, at the point that knows the model. The bind sits inside the middleware-pipeline terminal in LlmServiceManager — chat, tool calling and, in its opener, streaming — because that is the first place the resolved model exists. For a stream it runs before the adapter is asked for the first chunk: once a stream is open there is nothing left to prune. A tool-calling send counts its tool schemas against the same budget, because they are on the wire with the transcript.

Embeddings are deliberately not bounded here. They carry neither skills nor snippets nor a transcript, and their size limit is the provider's own input limit rather than a context window to prune turns out of.

A completion reports; it does not prune. A raw prompt is a single unit: there are no older turns to drop, and silently shortening a caller's prompt would change what they asked for, which only the caller can judge. What the path does deliver is the decision being explicit — an overflowing completion is named, with the model and the budget it exceeded, instead of surfacing later as an opaque provider error.

Overflow at the floor still sends. The estimate errs high, so a payload that does not fit may well succeed; if it does not, the provider's own error is what the caller would have received anyway. Refusing here would turn a call that might have worked into one that certainly does not. This matches what ConversationService already did, and it is why the bound is a bound and not a gate.

Consequences 

✓ A criteria-mode configuration is sized against its real model. This is a behaviour change on the paths that already bound a window: a transcript that previously slipped through against a 128k assumption is now pruned against the 4k model actually answering.

✓ Chat and streaming through the generic manager are bounded like a conversation or an agent loop.

✓ Completion overflow is visible before the provider rejects it.

◐ Two fits can run for one send — a conversation or agent loop fits its transcript for its own semantics (dropped_turns is a stored fact, ADR-121), and the send-level bound runs again at dispatch. The second is a no-op when the first already fit, and it costs one estimator pass over a list that is about to cross a network.

◐ LlmServiceManager gained two optional constructor arguments. Both default to null, so every existing construction keeps its exact previous behaviour — a null context window means "bounded by the provider", which is what these paths did.

✕ Not a token guarantee. The estimator is an estimate with a calibration factor; ADR-107's limits are unchanged.

Revisit when 

A consumer needs the send-level fit's decision as data rather than a log line — that is the same surface question the routing decision trace raised (ADR-142), and the two should get one answer, not two.