Windows robustness for claude/codex backends (+ hardened JSON fallback) (#79)

* Robustness for the claude/codex backends on Windows: argv overflow, subprocess encoding, tolerant JSON, test-eval dirs

Fixes surfaced running SkillOpt end-to-end on the bundled `claude` backend
(local Claude CLI) on Windows. None changes the OpenAI/GPT happy path.

1. skillopt/engine/trainer.py — the final test-eval directory
   (test_eval_final/) is written to before being created; add
   os.makedirs(..., exist_ok=True), matching the two sibling test-eval dirs.
   Without it, summary.json raises FileNotFoundError when a rollout yields
   zero predictions.

2. skillopt/model/claude_backend.py
   a. Pass the prompt via stdin (not argv): on Windows the whole command line
      is capped at ~32 KB and a large optimizer prompt (the success-analyst
      minibatch carrying several report trajectories) overflows it with
      [WinError 206], killing the run after retries.
   b. Pass the system prompt via --append-system-prompt-file (a temp file),
      not argv. The system prompt here is the skill being optimized, which
      SkillOpt grows over training; since the ~32 KB cap applies to the SUM of
      all argv, a grown skill would re-hit [WinError 206] even with the prompt
      on stdin.
   c. Pin the subprocess encoding to utf-8 (errors="replace"). With text=True
      and no encoding=, stdin is encoded with the system codepage; on a zh-CN
      box (cp936/GBK) a prompt containing an emoji or some Latin-1 characters
      raises UnicodeEncodeError before the CLI even starts, failing every retry.

3. skillopt/model/codex_backend.py — the same utf-8 encoding pin on its
   subprocess.run(input=...) call (identical unpinned-encoding pattern).

4. skillopt/utils/json_utils.py — extract_json() returned None for valid-
   looking JSON that strict json.loads rejects (unescaped ASCII quotes inside
   CJK string values, trailing commas), silently dropping the analyst's edits
   on non-schema backends (Claude/Qwen): reflect produces N edits, 0 applied.
   Add a json_repair fallback, but only on a single unambiguous object — a
   balanced-brace extractor plus a refuse-on-multiple-objects guard — so a
   chain-of-thought "scratch + final" response can't make repair silently
   return the wrong (discarded) object, which would be worse than None (None is
   detectable and retryable; a wrong-but-valid edit is applied blind). Declare
   json_repair in requirements.txt and the claude/qwen optional extras so the
   fallback is actually present (it otherwise no-ops, dropping edits silently).

Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>
(cherry picked from commit dca74a683e)

* fix(json_utils): harden tolerant JSON fallback from PR #77

Follow-up fixes on top of the cherry-picked Windows-robustness change:

1. Make _top_level_brace_objects() fully string-aware in its OUTER scan, not
   just inside an object. A '{' inside quoted prose (e.g. '"set it to {x}"')
   no longer starts a candidate object, so extract_json() returns None for
   prose pseudo-JSON instead of repairing it into a bogus dict — which would
   be strictly worse than dropping the edit, since extract_json feeds the
   optimizer's skill edits.

2. Pick the repair candidate BEFORE importing json_repair, so the missing-
   dependency RuntimeWarning only fires when there is genuinely a single
   malformed object that could have been repaired. Ordinary no-JSON / prose
   replies (the common case) now return None silently instead of warning on
   every call.

3. Resolve dependency-metadata inconsistency: json_repair is optional, so add
   it to the `all` extra (it was already in `claude`/`qwen`) and demote it
   from a hard requirement to an optional/commented entry in requirements.txt,
   matching the project's convention for backend-specific deps.

Adds regression tests for prose-with-braces (-> None), no-warning-on-plain-
text, single-object repair, and multi-object ambiguity. Existing 22 json
tests still pass with and without json_repair installed.

Co-Authored-By: Claude <noreply@anthropic.com>

---------

Co-authored-by: samuelgoofus-boop <260247789+samuelgoofus-boop@users.noreply.github.com>
Co-authored-by: Claude Opus 4.8 (1M context) <noreply@anthropic.com>

skillopt/model/claude_backend.py

@@ -252,13 +252,25 @@ def _run_claude_print(*, system: str, prompt: str, model: str, tools: list[dict[
         if CLAUDE_SETTING_SOURCES:
             cmd.extend(["--setting-sources", CLAUDE_SETTING_SOURCES])
         if system:
-            cmd.extend(["--append-system-prompt", system])
+            # Write the system prompt to a file, not argv: here the skill being
+            # optimized IS the system prompt, and SkillOpt grows it over training,
+            # so past ~30 KB it would re-hit the Windows argv cap (WinError 206).
+            # The CLI reads it via --append-system-prompt-file.
+            system_path = os.path.join(temp_dir, "system_prompt.txt")
+            with open(system_path, "w", encoding="utf-8") as system_fh:
+                system_fh.write(system)
+            cmd.extend(["--append-system-prompt-file", system_path])
         if effort:
             cmd.extend(["--effort", effort])
         structured_output = bool(return_message)
         if structured_output:
             cmd.extend(["--schema", _assistant_message_schema_wrapper()])
-        proc = subprocess.run(cmd + [prompt_for_cli], capture_output=True, text=True, timeout=timeout or 300, cwd=temp_dir)
+        # Feed the prompt via stdin (and the system prompt via a file, above), not
+        # argv: on Windows the whole command line is capped at ~32 KB and large
+        # optimizer prompts / grown skills overflow it → [WinError 206]. Pin UTF-8
+        # so a zh-CN default codepage (cp936) can't raise UnicodeEncodeError on
+        # emoji / non-GBK glyphs before the CLI even starts.
+        proc = subprocess.run(cmd, input=prompt_for_cli, capture_output=True, text=True, encoding="utf-8", errors="replace", timeout=timeout or 300, cwd=temp_dir)
         stderr_text = (proc.stderr or "").strip()
         if proc.returncode != 0:
             _check_claude_error(stderr_text, model)

skillopt/model/codex_backend.py

@@ -328,6 +328,8 @@ def _run_codex_exec(
             command,
             input=prompt,
             text=True,
+            encoding="utf-8",
+            errors="replace",
             capture_output=True,
             timeout=timeout,
             check=False,