Extract model-facing context governance from AgentRunner.
Only compact in-flight tool results when the model request is over budget, keep compacted IDs stable within a turn, and allow the newest result to be compacted as a last resort when it is the remaining source of overflow.
maintainer edit: move duplicate tool_use history repair out of AgentRunner and into Anthropic message conversion, reusing the OpenAI-compatible queue-mapping approach locally without broadening the shared runner path.
maintainer edit: remap duplicate tool_use/tool_call ids instead of dropping later calls, so Anthropic-compatible providers that reuse ids for distinct parallel tool calls keep all requested work while still sending unique ids.
Anthropic rejects any request where two tool_use blocks share an id
("messages.N.content.M: tool_use ids must be unique"). A mis-assembled
stream could surface the same tool_use block twice in one assistant turn;
the runner persisted it verbatim, so the malformed message was re-sent on
every subsequent turn and permanently bricked the session — the agent
silently stopped replying.
Fix at two layers:
- AnthropicProvider._parse_response: drop duplicate tool_use ids (keep
first) as the response enters nanobot, so corruption is never persisted.
- AgentRunner._dedup_tool_calls: a new context-governance pass that dedupes
assistant tool_calls and tool results by id before each send, healing any
history that was already corrupted.
Add regression tests covering both the dedup and the no-op fast path.
Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com>
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