SkillOpt v0.1.0: initial release

- Skill optimization framework with training loop analogy
- 11 benchmarks, 4 model backends (Azure OpenAI, Claude, Codex, Qwen)
- WebUI for browser-based training control
- Pluggable architecture for extending benchmarks and backends

configs/spreadsheetbench/default.yaml

@@ -0,0 +1,34 @@
+_base_: ../_base_/default.yaml
+
+model:
+  reasoning_effort: medium
+
+train:
+  train_size: 80
+  batch_size: 40
+  accumulation: 1
+
+gradient:
+  minibatch_size: 8
+  merge_batch_size: 8
+
+optimizer:
+  learning_rate: 4
+
+evaluation:
+  sel_env_num: 0
+  test_env_num: 0
+
+env:
+  name: spreadsheetbench
+  skill_init: skillopt/envs/spreadsheetbench/skills/initial.md
+  split_mode: split_dir
+  split_ratio: "2:1:7"
+  split_dir: data/spreadsheetbench_split
+  data_path: ""
+  split_output_dir: ""
+  data_root: data/spreadsheetbench_verified_400
+  mode: multi
+  max_turns: 30
+  exec_timeout: 600
+  workers: 24