Maximize context and output per Anthropic best practices

Per official Anthropic documentation (April 2026):

Output tokens increased to match model capabilities:
- block-yod (discussion): 8K → 32K (Opus supports 128K)
- block-zayin (claims): 4K → 16K
- block-vav (background): 4K → 16K
- claims_extractor: 4K → 8K (fixes truncated JSON)
- qa_validator: 4K → 8K

Source documents sent in full (not truncated):
- Was: 3000 chars per doc, 15K total
- Now: full document text, no truncation
- Reduces hallucinations: "extract word-for-word quotes first"

Prompt structure follows long-context tips:
- Source documents placed FIRST (top of prompt)
- Instructions and query placed LAST
- "Queries at the end improve quality by up to 30%"

Extended thinking uses adaptive mode for Opus 4.6.
Streaming enabled for all requests > 21K tokens.

Unified JSON parsing via parse_llm_json() helper in config.py.
Applied to: classifier, claims_extractor, brainstorm, qa_validator,
learning_loop (5 files).

Also: extractor.py now supports .md files.

Sources:
- https://docs.anthropic.com/en/docs/build-with-claude/extended-thinking
- https://docs.anthropic.com/en/docs/build-with-claude/prompt-engineering/long-context-tips
- https://docs.anthropic.com/en/docs/minimizing-hallucinations
- https://docs.anthropic.com/en/docs/about-claude/models/overview

Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>

mcp-server/src/legal_mcp/services/learning_loop.py

@@ -9,14 +9,13 @@
 
 from __future__ import annotations
 
-import json
 import logging
-import re
 from uuid import UUID
 
 import anthropic
 
 from legal_mcp import config
+from legal_mcp.config import parse_llm_json
 from legal_mcp.services import db
 
 logger = logging.getLogger(__name__)
@@ -112,14 +111,11 @@ async def analyze_changes(draft_text: str, final_text: str) -> dict:
     )
 
     raw = message.content[0].text.strip()
-    try:
-        json_match = re.search(r"\{.*\}", raw, re.DOTALL)
-        if json_match:
-            return json.loads(json_match.group())
-        return json.loads(raw)
-    except json.JSONDecodeError:
+    result = parse_llm_json(raw)
+    if result is None:
         logger.warning("Failed to parse lessons response")
         return {"changes": [], "new_expressions": [], "overall_assessment": raw[:200]}
+    return result
 
 
 async def process_final_version(