aleleba
f4564bc7a0
Gate 2 (tool-calls, 200 held-out): global 95.5% (191/200) on both spec and nospec, matching v2b-bf16's 95.0%. Per-MCP breakdown diverges: spec regresses penpot specifically (91.7% vs bf16's 98.3%, outside the 2-point guard) while preserving atlassian/docmost; nospec preserves penpot (98.3%, matches bf16) but regresses atlassian/docmost instead. Consistent with risk #10 (MTP draft head drift) rather than risk #9 (quantization washing out the LoRA delta) -- if quantization itself hurt penpot, nospec should show the same regression, and it doesn't. Sampling is non-greedy (temperature 0.6), so some of this is ordinary run-to-run variance rather than a clean systematic signal. Gate 3 (21-check adherencia): spec 90.5% (19/21), nospec 71.4% (15/21). Both clear the >=61.9% no-regression bar against the production baseline, but the gap between spec/nospec is real and worth flagging. Gate 4 (E2E against real MCPs, spec only): gitea, docmost, and penpot (high_level_overview) executed successfully on the model's first-shot tool call. github-personal and atlassian failed on this specific attempt due to single-shot argument guesses (empty search query; a plausible but wrong Jira cloudId) -- verified separately that both integrations work fine once given correct arguments, so this reads as ordinary single-shot tool-use limitation, not a broken integration.