#!/bin/bash
# PostToolUse hook: Collect feedback after pipeline completion.
# Bash 3.2 compatible. Uses python3 for JSON parsing and CSV/MD append.
#
# Triggered after a designated "review" tool call completes.
# Reads pipeline output and reviewer score, appends to FEEDBACK.md,
# and detects recurring patterns (3+ rows with same tag = recurring).
#
# Placeholders:
#   {{WORKING_DIR}} - absolute path to project directory
#   {{PIPELINE_NAME}} - name of the pipeline being tracked
#   {{SCORE_THRESHOLD}} - minimum acceptable score (default: 60)

WORKING_DIR="{{WORKING_DIR}}"
PIPELINE_NAME="{{PIPELINE_NAME}}"
SCORE_THRESHOLD="${SCORE_THRESHOLD:-60}"
FEEDBACK_FILE="$WORKING_DIR/FEEDBACK.md"
HOOK_INPUT=$(cat)

# Only act on review tool calls
TOOL_NAME=$(echo "$HOOK_INPUT" | python3 -c "
import sys, json
try:
    data = json.load(sys.stdin)
    print(data.get('tool_name', ''))
except:
    print('')
" 2>/dev/null)

if [ "$TOOL_NAME" != "review_pipeline" ] && [ "$TOOL_NAME" != "score_output" ]; then
  exit 0
fi

# Extract score, agent, issue, resolution, pattern from hook input
python3 << PYEOF
import sys, json, re, os
from datetime import datetime

hook_input = """$HOOK_INPUT"""
feedback_file = "$FEEDBACK_FILE"
pipeline_name = "$PIPELINE_NAME"
score_threshold = int("$SCORE_THRESHOLD")

try:
    data = json.loads(hook_input)
except Exception:
    sys.exit(0)

tool_result = data.get('tool_result', '')
if isinstance(tool_result, dict):
    tool_result = json.dumps(tool_result)

# Parse structured fields from tool result (expects JSON or key:value)
agent_name = os.environ.get('AGENT_NAME', 'unknown')
score = 0
issue = ''
resolution = ''
pattern = ''

try:
    result_data = json.loads(tool_result)
    agent_name = result_data.get('agent', agent_name)
    score = int(result_data.get('score', 0))
    issue = result_data.get('issue', '')
    resolution = result_data.get('resolution', '')
    pattern = result_data.get('pattern', '')
except Exception:
    # Fallback: look for score: N in plain text
    m = re.search(r'score[:\s]+(\d+)', tool_result, re.IGNORECASE)
    if m:
        score = int(m.group(1))
    m = re.search(r'pattern[:\s]+(\S+)', tool_result, re.IGNORECASE)
    if m:
        pattern = m.group(1)

if score == 0 and not issue:
    sys.exit(0)

date_str = datetime.utcnow().strftime('%Y-%m-%d')
row = f"| {date_str} | {pipeline_name} | {agent_name} | {score}/100 | {issue} | {resolution} | {pattern} |"

# Append to feedback table
if not os.path.exists(feedback_file):
    print(f"Warning: {feedback_file} not found -- skipping feedback append")
    sys.exit(0)

with open(feedback_file, 'r') as f:
    content = f.read()

# Insert row after the header row of the table
table_header = '| Date | Pipeline | Agent | Score | Issue | Resolution | Pattern |'
separator = '|------|----------|-------|-------|-------|------------|---------|'
placeholder_row = '| {{DATE}} | {{PIPELINE_NAME}} | {{AGENT_NAME}} | {{SCORE}}/100 | {{ISSUE_DESCRIPTION}} | {{RESOLUTION}} | {{PATTERN_TAG}} |'

if placeholder_row in content:
    # Replace placeholder with real row + keep placeholder for next time
    content = content.replace(placeholder_row, row + '\n' + placeholder_row)
elif separator in content:
    content = content.replace(separator, separator + '\n' + row)
else:
    content += '\n' + row + '\n'

with open(feedback_file, 'w') as f:
    f.write(content)

print(f"Feedback recorded: score={score}, pattern={pattern}")

# Detect recurring patterns
if pattern:
    pattern_count = content.count(f'| {pattern} |')
    if pattern_count >= 3:
        print(f"RECURRING PATTERN DETECTED: '{pattern}' appears {pattern_count} times")
        print(f"Action required: review prompt or pipeline for '{pipeline_name}'")

# Flag low scores
if score < score_threshold and score > 0:
    print(f"LOW SCORE: {score} < threshold {score_threshold} for agent {agent_name}")
PYEOF

exit 0