Subtitle Correction

Name: Subtitle Correction
Author: sugarforever

sugarforever/01coder-agent-skills

497 installs
130 repo stars
Updated June 19, 2026
sugarforever/01coder-agent-skills

subtitle-correction is an agent skill that fixes speech-recognition errors in .srt subtitle files for developers who publish technical video tutorials with domain-specific terminology in Chinese or English.

About

subtitle-correction is a Claude Code agent skill from sugarforever/01coder-agent-skills that proofreads .srt subtitles produced by automatic speech recognition without altering timestamps, sequence numbers, or entry boundaries. The workflow collects domain terminology (frameworks, APIs, code identifiers), applies corrections for phonetic homophones, English-Chinese mixed mistranscriptions, and technical term garbling, then writes a filename-corrected.srt output. A bundled subtitle_tool.py script supports validate, analyze, and word-level diff commands plus HTML comparison reports. The skill ships 2 reference guides and documents 4 error categories. Reach for subtitle-correction when Whisper or similar ASR output mishears LangChain, OpenAI, PyTorch, or Chinese technical vocabulary in course captions.

subtitle-correction

Subtitle Correction by the numbers

497 all-time installs (skills.sh)
+14 installs in the week ending Aug 5, 2026 (Skillselion tracking)
Ranked #832 of 4,347 Backend & APIs skills by installs in the Skillselion catalog
Data as of Aug 5, 2026 (Skillselion catalog sync)

npx skills add https://github.com/sugarforever/01coder-agent-skills --skill subtitle-correction

Add your badge

Show developers this skill is listed on Skillselion. Paste this into your README.

[![Listed on Skillselion](https://skillselion.com/badge/skills/sugarforever/01coder-agent-skills/subtitle-correction.svg)](https://skillselion.com/skills/sugarforever/01coder-agent-skills/subtitle-correction)

Installs	497
repo stars	★ 130
Last updated	June 19, 2026
Repository	sugarforever/01coder-agent-skills ↗

How do you fix ASR errors in .srt subtitles?

Use subtitle-correction for development tasks

Who is it for?

Developers publishing bilingual technical video courses who need accurate captions without re-timing subtitle entries.

Skip if: Developers who need subtitle translation, timing shifts, or non-.srt formats like VTT or ASS should use dedicated subtitle editors instead.

When should I use this skill?

User uploads a .srt subtitle file and asks to correct, fix, proofread, or clean up speech-recognition errors in technical tutorial captions.

What you get

A corrected .srt file with -corrected suffix, optional HTML diff report, and validation confirming unchanged timestamps and entry counts.

filename-corrected.srt
HTML diff report
validation summary

By the numbers

Ships 2 reference guides: srt-format.md and terminology.md
Bundles 1 Python validation script (subtitle_tool.py) with validate, analyze, and diff subcommands
Documents 4 speech-recognition error categories in SKILL.md

Files

SKILL.mdMarkdownGitHub ↗

Subtitle Correction Skill

This skill corrects speech recognition errors in subtitle files while strictly preserving timeline information.

Interactive Workflow

Step 1: Request Terminology from User

IMPORTANT: Before starting any correction, ALWAYS ask the user for domain-specific terms.

Prompt the user with:

在开始修正之前，请提供一些关键术语，帮助我更准确地识别和修正语音识别错误：

1. **专有名词**：人名、品牌名、产品名等（如：Anthropic、Claude）
2. **技术术语**：框架、库、工具名称（如：LangChain、OpenAI、PyTorch）
3. **领域词汇**：行业特定词汇（如：checkpointer、middleware、runtime）
4. **其他关键词**：视频中频繁出现的重要词汇

请用逗号分隔，例如：`LangChain, Agent, OpenAI, checkpointer`

For English users:

Before I begin correction, please provide key terms to help me accurately identify speech recognition errors:

1. **Proper nouns**: Names, brands, products (e.g., Anthropic, Claude)
2. **Technical terms**: Frameworks, libraries, tools (e.g., LangChain, PyTorch)
3. **Domain vocabulary**: Industry-specific terms (e.g., checkpointer, middleware)
4. **Other keywords**: Important words that appear frequently

Please separate with commas, e.g.: `LangChain, Agent, OpenAI, checkpointer`

Step 2: Confirm Understanding

After receiving terms, confirm by: 1. Listing the terms received 2. Identifying the likely domain/context (AI/ML tutorial, web dev, etc.) 3. Asking if there are any additional terms before proceeding

Example response:

收到以下术语：
- 技术框架：LangChain, LangGraph, OpenAI
- 技术概念：Agent, checkpointer, runtime

看起来这是一个 LangChain 智能体开发的教程视频。

还有其他需要补充的术语吗？如果没有，我将开始修正字幕。

Step 3: Process with Terms

Use the provided terms to: 1. Build a mental model of expected vocabulary 2. Identify likely speech recognition errors 3. Apply consistent corrections throughout

When User Doesn't Provide Terms

If user says "没有" / "no" / "直接开始": 1. Proceed with correction using built-in patterns 2. Flag uncertain corrections for user review 3. After completion, ask if any terms were missed

Core Workflow

1. Read the subtitle file - Load the .srt file provided by the user 2. Identify error patterns - Recognize common speech recognition mistakes 3. Apply corrections - Fix errors while preserving timestamps exactly 4. Output corrected file - Return or save based on user's context

Strict Rules

Timeline Preservation

NEVER modify timestamps - Keep all 00:00:00,000 --> 00:00:00,000 lines exactly as-is
NEVER change subtitle numbering - Preserve sequence numbers
NEVER merge or split subtitle entries - One-to-one correspondence

Error Categories

1. Phonetic Errors (同音字/谐音错误)

Common in Chinese speech recognition:

会话 ↔ 绘画 (huìhuà)
元数据 ↔ 源数据 (yuán shùjù)
本课 ↔ 本科 (běnkè)
示例 ↔ 事例 (shìlì)
实践 ↔ 时间 (shíjiàn)

2. Technical Term Errors

Speech recognition often fails on:

Framework names: LangChain, LangGraph, OpenAI, PyTorch, TensorFlow
Programming terms: API, SDK, runtime, checkpointer, middleware
Code identifiers: snake_case names, function names, class names

3. English-Chinese Mixed Content

Luncheon/lunch → langchain
open EI/open Email → OpenAI
land GRAPH → langgraph
a memory Server → MemorySaver

4. Code-Related Terms

Convert spoken descriptions to proper format:

"underscore" → "_" in variable names
"dot" → "." in method calls
Recognize camelCase, snake_case, PascalCase patterns

User-Provided Terminology

When users provide a terminology list, use it as the primary reference for corrections:

用户提供的术语：LangChain,Agent,OpenAI,LangGraph

These terms indicate:

Expected proper spellings of technical terms
Context about the content domain
Hints for identifying speech recognition errors

Processing Strategy

For Long Files (>200 lines)

1. Process in chunks using view_range parameter 2. Maintain context across chunks 3. Build complete corrected file incrementally

For Technical Content

1. Identify the domain (AI/ML, web dev, etc.) 2. Build mental model of expected terminology 3. Apply domain-specific corrections consistently

Quality Checks

Before outputting:

Verify all timestamps unchanged
Verify subtitle count unchanged
Check terminology consistency throughout
Ensure no orphaned corrections (partial fixes)

Common Correction Patterns

Chinese AI/ML Course Content

Error	Correction	Context
蓝犬/蓝卷/Lantern	LangChain	Framework name
绘画	会话	Session/conversation
拖/tour	tool	Tool concept
checkpoint组件	checkpointer组件	Memory component
源数据	元数据	Metadata
大约模型	大模型	Large model
中间键	中间件	Middleware

Code Identifiers

Spoken	Written
user underscore 001	user_001
thread underscore id	thread_id
create underscore agent	create_agent
runtime dot state	runtime.state

Output Format

When saving, use -corrected suffix:

Input: filename.srt
Output: filename-corrected.srt

Validation Script

Use scripts/subtitle_tool.py to validate and analyze subtitle files:

# Validate corrected file preserves structure
python scripts/subtitle_tool.py validate original.srt corrected.srt

# Show word-level diff with colored output (default, changes only)
python scripts/subtitle_tool.py diff original.srt corrected.srt

# Show ALL entries (changed and unchanged) in terminal
python scripts/subtitle_tool.py diff original.srt corrected.srt --all

# Generate HTML diff report (recommended for review)
python scripts/subtitle_tool.py diff original.srt corrected.srt --html report.html

# Show simple line-based diff (original/corrected lines)
python scripts/subtitle_tool.py diff original.srt corrected.srt --simple

# Disable colors for piping to files
python scripts/subtitle_tool.py diff original.srt corrected.srt --no-color

# Analyze file for potential speech recognition errors
python scripts/subtitle_tool.py analyze input.srt --terms "LangChain,OpenAI"

Diff Output Formats

Terminal Output (Default)

Shows word-level changes with colors:

[1] 00:00:01,500 --> 00:00:04,500
  今天我们来学习[-Luncheon-]{+LangChain+}框架

[3] 00:00:08,000 --> 00:00:12,500
  我们可以用它来创建[-绘画-]{+会话+}应用程序

[-deleted-] - Text removed (shown in red in terminal)
{+added+} - Text added (shown in green in terminal)
Use --all to show unchanged entries too

HTML Report (Recommended for Review)

Generates a full comparison report with:

All entries displayed (changed and unchanged)
Side-by-side columns: Original | Corrected | Diff View
Visual highlighting: Red strikethrough for deletions, green for additions
Summary statistics: Total entries, changed count, unchanged count
Jump links: Quick navigation to changed entries
Change indicators: Yellow dot marks changed rows

python scripts/subtitle_tool.py diff original.srt corrected.srt --html diff_report.html

Then open diff_report.html in a browser.

Validation Workflow

1. Before correction: Run analyze to identify potential errors 2. After correction: Run validate to ensure structural integrity 3. Review changes: Run diff --html report.html to generate a visual comparison report

Validation Checks

Entry count matches original
All timestamps unchanged
All sequence numbers preserved
No formatting corruption

Example Interaction

Interaction 1: User uploads file without terms

User: 帮我修正这个字幕文件

Claude:

在开始修正之前，请提供一些关键术语，帮助我更准确地识别语音识别错误：

1. **专有名词**：人名、品牌名、产品名
2. **技术术语**：框架、库、工具名称
3. **领域词汇**：行业特定词汇
4. **其他关键词**：视频中频繁出现的重要词汇

请用逗号分隔，例如：`LangChain, Agent, OpenAI`

User: LangChain, Agent, OpenAI, LangGraph, checkpointer

Claude:

收到以下术语：
- 技术框架：LangChain, LangGraph, OpenAI
- 技术概念：Agent, checkpointer

这是一个 LangChain 相关的技术教程。还有补充吗？

User: 没有了，开始吧

Claude: [Proceeds with correction workflow]

Interaction 2: User provides terms upfront

User: 帮我修正字幕，术语：LangChain, OpenAI, Agent

Claude: [Confirms terms, then proceeds directly]

Correction Process

1. Read uploaded .srt file 2. Run analyze to identify potential errors 3. Apply corrections using provided terms as primary reference 4. Run validate to confirm structural integrity 5. Save corrected file with -corrected suffix 6. Generate diff report and present summary of changes 7. Offer HTML report: Ask user if they want an HTML diff report for easier review

Output: Provide categorized summary of corrections made.

After completion, prompt user:

修正完成！我可以生成一个 HTML 差异报告，方便您在浏览器中查看所有修改。
需要生成 HTML 报告吗？

Correction complete! I can generate an HTML diff report for easier review in your browser.
Would you like me to generate the HTML report?

SRT Format Reference

File Structure

An SRT (SubRip Subtitle) file consists of sequential subtitle entries, each containing:

1
00:00:01,500 --> 00:00:04,500
First line of subtitle text
Optional second line

2
00:00:04,700 --> 00:00:07,666
Next subtitle text

Entry Components

1. Sequence Number

Sequential integer starting from 1
Must be preserved exactly
No gaps or duplicates allowed

2. Timestamp Line

HH:MM:SS,mmm --> HH:MM:SS,mmm

Start time --> End time
Hours:Minutes:Seconds,Milliseconds
Uses comma (,) as decimal separator, NOT period
Must be preserved exactly - NEVER modify

3. Text Content

One or more lines of text
This is the ONLY part to correct
Empty line separates entries

Critical Rules for Subtitle Correction

DO

Correct spelling and terminology errors in text lines
Maintain all line breaks within subtitle text
Preserve empty lines between entries
Keep sequence numbers unchanged
Keep timestamps unchanged

DON'T

Modify timestamp values
Change sequence numbers
Merge multiple entries
Split single entries
Add or remove entries
Change the comma in timestamps to period

Example Correction

Before (with errors):

53
00:02:23,433 --> 00:02:25,833
定义了一款工具summers conversation

54
00:02:26,133 --> 00:02:28,166
这款工具除了用了Lantern

After (corrected):

53
00:02:23,433 --> 00:02:25,833
定义了一款工具summarize_conversation

54
00:02:26,133 --> 00:02:28,166
这款工具除了用了LangChain

Processing Large Files

For files with many entries:

1. Read in chunks using line ranges 2. Track position to ensure complete coverage 3. Verify entry count matches after correction 4. Check continuity - no missing sequence numbers

Validation Checklist

Before outputting corrected file:

[ ] Entry count matches original
[ ] All sequence numbers present (1 to N)
[ ] All timestamps unchanged
[ ] No malformed timestamp lines
[ ] Empty line between each entry
[ ] No trailing whitespace issues

Common Terminology Reference

This reference contains frequently encountered speech recognition errors and their corrections, organized by domain.

AI/ML Frameworks and Tools

LangChain Ecosystem

Speech Recognition Error	Correct Term
蓝犬	LangChain
蓝卷	LangChain
Lantern	LangChain
Luncheon	langchain
lunch	langchain
learning	LangChain
land GRAPH	langgraph
LAN GRAPH	langgraph
Linux (in context)	LangGraph
a memory Server	MemorySaver
AMM Server	MemorySaver
amneserver	MemorySaver
check point	checkpointer
Sharepoint	checkpointer

OpenAI

Speech Recognition Error	Correct Term
open EI	OpenAI
open Email	OpenAI
open AI	OpenAI
GPT store Mini	gpt-4o-mini

General AI Terms

Speech Recognition Error	Correct Term
拖	tool
tour	tool
拖run time	ToolRuntime
wrong time	runtime
TOKEN (in wrong context)	tool
GE组件	记忆组件

Chinese Phonetic Errors (同音字)

Common Pairs

Error	Correction	Pinyin
绘画	会话	huìhuà
源数据	元数据	yuán shùjù
本科	本课	běnkè
事例	示例	shìlì
时间代码	实践代码	shíjiàn
详细的裁剪	消息的裁剪	xiāoxi
中间键	中间件	zhōngjiànjiàn
大约模型	大模型	dà móxíng
希望到	希望得到	xīwàng dédào
名字空间	命名空间	mìngmíng kōngjiān
流逝	流式	liúshì
约着	约定	yuēdìng

Code-Related Corrections

Variable/Function Naming Conventions

Spoken Form	Written Form
user underscore 001	user_001
thread underscore id	thread_id
user underscore level	user_level
create underscore agent	create_agent
trim underscore messages	trim_messages
before underscore model	before_model
remove underscore all underscore messages	remove_all_messages

Method Calls

Spoken Form	Written Form
runtime点state	runtime.state
runtime点context	runtime.context
agent点invoke	agent.invoke
result点get	result.get

Class Names

Error	Correction
agent state	AgentState
custom state	CustomState
user context	UserContext
task manager state	TaskManagerState
tool message	ToolMessage
remove message	RemoveMessage

API Configuration Terms

Config/Configurable

Error	Correction
confict	config
conflict	config
THREAD ID	thread_id
context schemer	context_schema
state schemer	state_schema
text meta data	tags metadata

Domain-Specific: Video Course Content

Course Structure Terms

Error	Correction
第X科	第X课
本科	本课
向消息	消息

Presenter Names (Context-Specific)

When users provide specific names in their terminology list:

These are likely presenter or speaker names
Should be preserved exactly as provided
Use as reference for identifying speech recognition errors

Usage Notes

1. Context Matters: Many errors depend on context

"TOKEN" might be correct in "token数" but wrong in "TOKEN ID" (should be "tool ID")
"客户" vs "客服" depends on who is speaking

2. Consistency: Once a correction is identified, apply it consistently throughout

3. Compound Errors: Watch for multiple errors in one term

"Luncheon open EI" → "langchain-openai"
"open AI underscore API underscore key" → "OPENAI_API_KEY"

4. Case Sensitivity:

Package names: lowercase (langchain, langgraph)
Class names: PascalCase (LangChain, MemorySaver)
Environment variables: UPPER_SNAKE_CASE

#!/usr/bin/env python3
"""
Subtitle Validation and Correction Tool

This script validates corrected subtitle files against originals and can also
assist with the correction process by identifying common speech recognition errors.

Usage:
    # Validate corrected file against original
    python subtitle_tool.py validate original.srt corrected.srt

    # Show diff between files (text changes only)
    python subtitle_tool.py diff original.srt corrected.srt

    # Analyze a file for potential errors
    python subtitle_tool.py analyze input.srt --terms "LangChain,OpenAI,Agent"
"""

import re
import sys
import argparse
from pathlib import Path
from dataclasses import dataclass
from typing import List, Tuple, Optional, Dict
from difflib import SequenceMatcher


# ANSI color codes for terminal output
class Colors:
    RED = '\033[91m'
    GREEN = '\033[92m'
    YELLOW = '\033[93m'
    BLUE = '\033[94m'
    CYAN = '\033[96m'
    BOLD = '\033[1m'
    DIM = '\033[2m'
    STRIKETHROUGH = '\033[9m'
    RESET = '\033[0m'

    @classmethod
    def disable(cls):
        """Disable colors for non-terminal output."""
        cls.RED = cls.GREEN = cls.YELLOW = cls.BLUE = ''
        cls.CYAN = cls.BOLD = cls.DIM = cls.STRIKETHROUGH = cls.RESET = ''


def word_level_diff(original: str, corrected: str, use_color: bool = True) -> str:
    """
    Generate a word-level diff between original and corrected text.

    Returns a string with inline markers showing what changed:
    - Deletions shown in red with strikethrough: [-deleted-]
    - Additions shown in green: {+added+}

    Example:
        original:  "这款工具用了Lantern框架"
        corrected: "这款工具用了LangChain框架"
        output:    "这款工具用了[-Lantern-]{+LangChain+}框架"
    """
    if not use_color:
        Colors.disable()

    # Tokenize: split into words/characters while preserving structure
    # For mixed Chinese/English, we tokenize character-by-character for Chinese
    # and word-by-word for English
    def tokenize(text: str) -> List[str]:
        tokens = []
        current_word = ""
        for char in text:
            if char.isascii() and char.isalnum():
                current_word += char
            else:
                if current_word:
                    tokens.append(current_word)
                    current_word = ""
                if char.strip():  # Non-whitespace
                    tokens.append(char)
                elif char == ' ':
                    tokens.append(char)
        if current_word:
            tokens.append(current_word)
        return tokens

    orig_tokens = tokenize(original)
    corr_tokens = tokenize(corrected)

    matcher = SequenceMatcher(None, orig_tokens, corr_tokens)
    result = []

    for tag, i1, i2, j1, j2 in matcher.get_opcodes():
        if tag == 'equal':
            result.append(''.join(orig_tokens[i1:i2]))
        elif tag == 'delete':
            deleted = ''.join(orig_tokens[i1:i2])
            result.append(f"{Colors.RED}{Colors.STRIKETHROUGH}[-{deleted}-]{Colors.RESET}")
        elif tag == 'insert':
            inserted = ''.join(corr_tokens[j1:j2])
            result.append(f"{Colors.GREEN}{{+{inserted}+}}{Colors.RESET}")
        elif tag == 'replace':
            deleted = ''.join(orig_tokens[i1:i2])
            inserted = ''.join(corr_tokens[j1:j2])
            result.append(f"{Colors.RED}{Colors.STRIKETHROUGH}[-{deleted}-]{Colors.RESET}")
            result.append(f"{Colors.GREEN}{{+{inserted}+}}{Colors.RESET}")

    return ''.join(result)


def word_level_diff_html(original: str, corrected: str) -> str:
    """
    Generate word-level diff as HTML with inline styling.
    Returns HTML string with <del> and <ins> tags for changes.
    """
    def tokenize(text: str) -> List[str]:
        tokens = []
        current_word = ""
        for char in text:
            if char.isascii() and char.isalnum():
                current_word += char
            else:
                if current_word:
                    tokens.append(current_word)
                    current_word = ""
                if char.strip():
                    tokens.append(char)
                elif char == ' ':
                    tokens.append(char)
        if current_word:
            tokens.append(current_word)
        return tokens

    import html
    orig_tokens = tokenize(original)
    corr_tokens = tokenize(corrected)

    matcher = SequenceMatcher(None, orig_tokens, corr_tokens)
    result = []

    for tag, i1, i2, j1, j2 in matcher.get_opcodes():
        if tag == 'equal':
            result.append(html.escape(''.join(orig_tokens[i1:i2])))
        elif tag == 'delete':
            deleted = html.escape(''.join(orig_tokens[i1:i2]))
            result.append(f'<del>{deleted}</del>')
        elif tag == 'insert':
            inserted = html.escape(''.join(corr_tokens[j1:j2]))
            result.append(f'<ins>{inserted}</ins>')
        elif tag == 'replace':
            deleted = html.escape(''.join(orig_tokens[i1:i2]))
            inserted = html.escape(''.join(corr_tokens[j1:j2]))
            result.append(f'<del>{deleted}</del>')
            result.append(f'<ins>{inserted}</ins>')

    return ''.join(result)


def generate_html_diff(original_path: str, corrected_path: str, output_path: str) -> Tuple[int, int]:
    """
    Generate an HTML diff report showing all entries with changes highlighted.

    Returns:
        Tuple of (total_entries, changed_entries)
    """
    import html

    original = parse_srt(original_path)
    corrected = parse_srt(corrected_path)

    # Build lookup for corrected entries
    corr_map = {e.index: e for e in corrected}

    changed_count = 0
    rows = []

    for orig in original:
        corr = corr_map.get(orig.index)
        if corr and orig.text != corr.text:
            changed_count += 1
            is_changed = True
            diff_html = word_level_diff_html(orig.text, corr.text)
        else:
            is_changed = False
            diff_html = html.escape(orig.text) if orig else ""

        rows.append({
            'index': orig.index,
            'timestamp': f"{orig.start_time} --> {orig.end_time}",
            'original': html.escape(orig.text),
            'corrected': html.escape(corr.text) if corr else "",
            'diff': diff_html,
            'changed': is_changed
        })

    # Calculate percentage
    change_percent = round((changed_count / len(original)) * 100, 1) if original else 0

    html_content = f'''<!DOCTYPE html>
<html lang="zh-CN">
<head>
    <meta charset="UTF-8">
    <meta name="viewport" content="width=device-width, initial-scale=1.0">
    <title>Subtitle Diff Report</title>
    <link rel="preconnect" href="https://fonts.googleapis.com">
    <link rel="preconnect" href="https://fonts.gstatic.com" crossorigin>
    <link href="https://fonts.googleapis.com/css2?family=IBM+Plex+Sans:wght@400;500;600;700&family=JetBrains+Mono:wght@400;500;600&display=swap" rel="stylesheet">
    <style>
        :root {{
            --bg-primary: #0F172A;
            --bg-secondary: #1E293B;
            --bg-tertiary: #334155;
            --text-primary: #F1F5F9;
            --text-secondary: #94A3B8;
            --text-muted: #64748B;
            --accent-blue: #3B82F6;
            --accent-cyan: #22D3EE;
            --accent-purple: #A855F7;
            --delete-bg: rgba(239, 68, 68, 0.2);
            --delete-text: #FCA5A5;
            --delete-border: #EF4444;
            --insert-bg: rgba(34, 197, 94, 0.2);
            --insert-text: #86EFAC;
            --insert-border: #22C55E;
            --border-color: #334155;
            --glow-blue: 0 0 20px rgba(59, 130, 246, 0.3);
        }}

        * {{
            box-sizing: border-box;
            margin: 0;
            padding: 0;
        }}

        body {{
            font-family: 'IBM Plex Sans', -apple-system, BlinkMacSystemFont, sans-serif;
            line-height: 1.6;
            background: var(--bg-primary);
            color: var(--text-primary);
            min-height: 100vh;
        }}

        .container {{
            max-width: 1600px;
            margin: 0 auto;
            padding: 24px;
        }}

        /* Header */
        .header {{
            display: flex;
            align-items: center;
            gap: 16px;
            margin-bottom: 32px;
            padding-bottom: 24px;
            border-bottom: 1px solid var(--border-color);
        }}

        .logo {{
            width: 48px;
            height: 48px;
            background: linear-gradient(135deg, var(--accent-blue), var(--accent-purple));
            border-radius: 12px;
            display: flex;
            align-items: center;
            justify-content: center;
            box-shadow: var(--glow-blue);
        }}

        .logo svg {{
            width: 28px;
            height: 28px;
            color: white;
        }}

        .header-text h1 {{
            font-size: 24px;
            font-weight: 700;
            background: linear-gradient(135deg, var(--text-primary), var(--accent-cyan));
            -webkit-background-clip: text;
            -webkit-text-fill-color: transparent;
            background-clip: text;
        }}

        .header-text p {{
            font-size: 14px;
            color: var(--text-secondary);
        }}

        /* File paths */
        .file-paths {{
            display: grid;
            grid-template-columns: repeat(auto-fit, minmax(300px, 1fr));
            gap: 16px;
            margin-bottom: 24px;
        }}

        .file-card {{
            background: var(--bg-secondary);
            border: 1px solid var(--border-color);
            border-radius: 12px;
            padding: 16px;
            display: flex;
            align-items: center;
            gap: 12px;
        }}

        .file-icon {{
            width: 40px;
            height: 40px;
            border-radius: 8px;
            display: flex;
            align-items: center;
            justify-content: center;
            flex-shrink: 0;
        }}

        .file-icon.original {{
            background: rgba(239, 68, 68, 0.1);
            color: var(--delete-text);
        }}

        .file-icon.corrected {{
            background: rgba(34, 197, 94, 0.1);
            color: var(--insert-text);
        }}

        .file-icon svg {{
            width: 20px;
            height: 20px;
        }}

        .file-info {{
            overflow: hidden;
        }}

        .file-label {{
            font-size: 12px;
            color: var(--text-muted);
            text-transform: uppercase;
            letter-spacing: 0.5px;
            margin-bottom: 4px;
        }}

        .file-path {{
            font-family: 'JetBrains Mono', monospace;
            font-size: 13px;
            color: var(--text-secondary);
            white-space: nowrap;
            overflow: hidden;
            text-overflow: ellipsis;
        }}

        /* Stats Grid */
        .stats-grid {{
            display: grid;
            grid-template-columns: repeat(auto-fit, minmax(200px, 1fr));
            gap: 16px;
            margin-bottom: 24px;
        }}

        .stat-card {{
            background: var(--bg-secondary);
            border: 1px solid var(--border-color);
            border-radius: 12px;
            padding: 20px;
            position: relative;
            overflow: hidden;
            transition: transform 0.2s, box-shadow 0.2s;
        }}

        .stat-card:hover {{
            transform: translateY(-2px);
            box-shadow: 0 8px 25px rgba(0, 0, 0, 0.3);
        }}

        .stat-card::before {{
            content: '';
            position: absolute;
            top: 0;
            left: 0;
            right: 0;
            height: 3px;
        }}

        .stat-card.total::before {{
            background: linear-gradient(90deg, var(--accent-blue), var(--accent-cyan));
        }}

        .stat-card.changed::before {{
            background: linear-gradient(90deg, #F59E0B, #EF4444);
        }}

        .stat-card.unchanged::before {{
            background: linear-gradient(90deg, var(--insert-border), var(--accent-cyan));
        }}

        .stat-icon {{
            width: 44px;
            height: 44px;
            border-radius: 10px;
            display: flex;
            align-items: center;
            justify-content: center;
            margin-bottom: 12px;
        }}

        .stat-card.total .stat-icon {{
            background: rgba(59, 130, 246, 0.1);
            color: var(--accent-blue);
        }}

        .stat-card.changed .stat-icon {{
            background: rgba(245, 158, 11, 0.1);
            color: #FBBF24;
        }}

        .stat-card.unchanged .stat-icon {{
            background: rgba(34, 197, 94, 0.1);
            color: var(--insert-border);
        }}

        .stat-icon svg {{
            width: 22px;
            height: 22px;
        }}

        .stat-number {{
            font-size: 32px;
            font-weight: 700;
            color: var(--text-primary);
            line-height: 1;
            margin-bottom: 4px;
        }}

        .stat-label {{
            font-size: 13px;
            color: var(--text-muted);
            text-transform: uppercase;
            letter-spacing: 0.5px;
        }}

        .stat-badge {{
            position: absolute;
            top: 16px;
            right: 16px;
            font-family: 'JetBrains Mono', monospace;
            font-size: 12px;
            padding: 4px 8px;
            border-radius: 6px;
            background: rgba(255, 255, 255, 0.05);
            color: var(--text-secondary);
        }}

        /* Legend & Jump Links */
        .actions-bar {{
            display: flex;
            flex-wrap: wrap;
            gap: 16px;
            align-items: flex-start;
            margin-bottom: 24px;
            padding: 16px;
            background: var(--bg-secondary);
            border: 1px solid var(--border-color);
            border-radius: 12px;
        }}

        .legend {{
            display: flex;
            align-items: center;
            gap: 16px;
            flex-shrink: 0;
        }}

        .legend-item {{
            display: flex;
            align-items: center;
            gap: 8px;
            font-size: 13px;
            color: var(--text-secondary);
        }}

        .legend del {{
            background: var(--delete-bg);
            color: var(--delete-text);
            text-decoration: line-through;
            padding: 2px 8px;
            border-radius: 4px;
            border: 1px solid rgba(239, 68, 68, 0.3);
            font-family: 'JetBrains Mono', monospace;
            font-size: 12px;
        }}

        .legend ins {{
            background: var(--insert-bg);
            color: var(--insert-text);
            text-decoration: none;
            padding: 2px 8px;
            border-radius: 4px;
            border: 1px solid rgba(34, 197, 94, 0.3);
            font-family: 'JetBrains Mono', monospace;
            font-size: 12px;
        }}

        .jump-links {{
            flex: 1;
            display: flex;
            flex-wrap: wrap;
            align-items: center;
            gap: 8px;
        }}

        .jump-label {{
            font-size: 13px;
            color: var(--text-muted);
            margin-right: 4px;
        }}

        .jump-link {{
            display: inline-flex;
            align-items: center;
            justify-content: center;
            min-width: 36px;
            height: 28px;
            padding: 0 10px;
            background: var(--bg-tertiary);
            color: var(--accent-cyan);
            text-decoration: none;
            border-radius: 6px;
            font-family: 'JetBrains Mono', monospace;
            font-size: 12px;
            font-weight: 500;
            transition: all 0.15s;
            border: 1px solid transparent;
        }}

        .jump-link:hover {{
            background: rgba(34, 211, 238, 0.1);
            border-color: var(--accent-cyan);
            transform: translateY(-1px);
        }}

        .no-changes {{
            color: var(--text-muted);
            font-style: italic;
        }}

        /* Table */
        .table-wrapper {{
            background: var(--bg-secondary);
            border: 1px solid var(--border-color);
            border-radius: 12px;
            overflow: hidden;
        }}

        table {{
            width: 100%;
            border-collapse: collapse;
        }}

        thead {{
            background: var(--bg-tertiary);
        }}

        th {{
            padding: 14px 16px;
            text-align: left;
            font-size: 12px;
            font-weight: 600;
            color: var(--text-secondary);
            text-transform: uppercase;
            letter-spacing: 0.5px;
            border-bottom: 1px solid var(--border-color);
        }}

        td {{
            padding: 16px;
            border-bottom: 1px solid var(--border-color);
            vertical-align: top;
            font-size: 14px;
        }}

        tr:last-child td {{
            border-bottom: none;
        }}

        tr {{
            transition: background 0.15s;
        }}

        tr:hover {{
            background: rgba(255, 255, 255, 0.02);
        }}

        tr.changed {{
            background: rgba(245, 158, 11, 0.03);
        }}

        tr.changed:hover {{
            background: rgba(245, 158, 11, 0.06);
        }}

        /* Entry Index */
        .entry-index {{
            display: flex;
            align-items: center;
            gap: 10px;
            font-family: 'JetBrains Mono', monospace;
            font-weight: 600;
            white-space: nowrap;
        }}

        .change-dot {{
            width: 8px;
            height: 8px;
            border-radius: 50%;
            flex-shrink: 0;
        }}

        .change-dot.changed {{
            background: #FBBF24;
            box-shadow: 0 0 8px rgba(251, 191, 36, 0.5);
        }}

        .change-dot.unchanged {{
            background: var(--bg-tertiary);
        }}

        .entry-num {{
            color: var(--accent-blue);
        }}

        /* Timestamp */
        .timestamp {{
            font-family: 'JetBrains Mono', monospace;
            font-size: 12px;
            color: var(--text-muted);
            white-space: nowrap;
            padding: 4px 8px;
            background: var(--bg-primary);
            border-radius: 4px;
        }}

        /* Text cells */
        .text-cell {{
            min-width: 180px;
            word-break: break-word;
            color: var(--text-secondary);
            line-height: 1.7;
        }}

        .diff-cell {{
            min-width: 220px;
            line-height: 1.7;
        }}

        .unchanged-text {{
            color: var(--text-muted);
        }}

        /* Diff styling */
        del {{
            background: var(--delete-bg);
            color: var(--delete-text);
            text-decoration: line-through;
            padding: 1px 4px;
            border-radius: 3px;
            font-family: inherit;
        }}

        ins {{
            background: var(--insert-bg);
            color: var(--insert-text);
            text-decoration: none;
            padding: 1px 4px;
            border-radius: 3px;
            font-family: inherit;
        }}

        /* Scroll to top */
        .scroll-top {{
            position: fixed;
            bottom: 24px;
            right: 24px;
            width: 44px;
            height: 44px;
            background: var(--accent-blue);
            color: white;
            border: none;
            border-radius: 12px;
            cursor: pointer;
            display: flex;
            align-items: center;
            justify-content: center;
            box-shadow: 0 4px 15px rgba(59, 130, 246, 0.4);
            transition: all 0.2s;
            opacity: 0;
            visibility: hidden;
        }}

        .scroll-top.visible {{
            opacity: 1;
            visibility: visible;
        }}

        .scroll-top:hover {{
            transform: translateY(-2px);
            box-shadow: 0 6px 20px rgba(59, 130, 246, 0.5);
        }}

        .scroll-top svg {{
            width: 20px;
            height: 20px;
        }}

        /* Responsive */
        @media (max-width: 768px) {{
            .container {{
                padding: 16px;
            }}

            .stats-grid {{
                grid-template-columns: 1fr;
            }}

            .file-paths {{
                grid-template-columns: 1fr;
            }}

            .actions-bar {{
                flex-direction: column;
            }}

            .table-wrapper {{
                overflow-x: auto;
            }}

            table {{
                min-width: 800px;
            }}
        }}

        /* Smooth scroll */
        html {{
            scroll-behavior: smooth;
        }}

        /* Target highlight animation */
        tr:target {{
            animation: highlight 2s ease-out;
        }}

        @keyframes highlight {{
            0% {{ background: rgba(59, 130, 246, 0.3); }}
            100% {{ background: transparent; }}
        }}
    </style>
</head>
<body>
    <div class="container">
        <!-- Header -->
        <div class="header">
            <div class="logo">
                <svg viewBox="0 0 24 24" fill="none" stroke="currentColor" stroke-width="2">
                    <path d="M14 2H6a2 2 0 0 0-2 2v16a2 2 0 0 0 2 2h12a2 2 0 0 0 2-2V8z"/>
                    <polyline points="14 2 14 8 20 8"/>
                    <line x1="9" y1="15" x2="15" y2="15"/>
                </svg>
            </div>
            <div class="header-text">
                <h1>Subtitle Diff Report</h1>
                <p>Speech recognition correction comparison</p>
            </div>
        </div>

        <!-- File Paths -->
        <div class="file-paths">
            <div class="file-card">
                <div class="file-icon original">
                    <svg viewBox="0 0 24 24" fill="none" stroke="currentColor" stroke-width="2">
                        <path d="M14 2H6a2 2 0 0 0-2 2v16a2 2 0 0 0 2 2h12a2 2 0 0 0 2-2V8z"/>
                        <polyline points="14 2 14 8 20 8"/>
                    </svg>
                </div>
                <div class="file-info">
                    <div class="file-label">Original</div>
                    <div class="file-path">{html.escape(original_path)}</div>
                </div>
            </div>
            <div class="file-card">
                <div class="file-icon corrected">
                    <svg viewBox="0 0 24 24" fill="none" stroke="currentColor" stroke-width="2">
                        <path d="M14 2H6a2 2 0 0 0-2 2v16a2 2 0 0 0 2 2h12a2 2 0 0 0 2-2V8z"/>
                        <polyline points="14 2 14 8 20 8"/>
                        <polyline points="9 15 11 17 15 13"/>
                    </svg>
                </div>
                <div class="file-info">
                    <div class="file-label">Corrected</div>
                    <div class="file-path">{html.escape(corrected_path)}</div>
                </div>
            </div>
        </div>

        <!-- Stats Grid -->
        <div class="stats-grid">
            <div class="stat-card total">
                <div class="stat-icon">
                    <svg viewBox="0 0 24 24" fill="none" stroke="currentColor" stroke-width="2">
                        <rect x="3" y="3" width="7" height="7"/>
                        <rect x="14" y="3" width="7" height="7"/>
                        <rect x="14" y="14" width="7" height="7"/>
                        <rect x="3" y="14" width="7" height="7"/>
                    </svg>
                </div>
                <div class="stat-number">{len(original)}</div>
                <div class="stat-label">Total Entries</div>
            </div>
            <div class="stat-card changed">
                <div class="stat-icon">
                    <svg viewBox="0 0 24 24" fill="none" stroke="currentColor" stroke-width="2">
                        <path d="M11 4H4a2 2 0 0 0-2 2v14a2 2 0 0 0 2 2h14a2 2 0 0 0 2-2v-7"/>
                        <path d="M18.5 2.5a2.121 2.121 0 0 1 3 3L12 15l-4 1 1-4 9.5-9.5z"/>
                    </svg>
                </div>
                <div class="stat-number">{changed_count}</div>
                <div class="stat-label">Changed</div>
                <div class="stat-badge">{change_percent}%</div>
            </div>
            <div class="stat-card unchanged">
                <div class="stat-icon">
                    <svg viewBox="0 0 24 24" fill="none" stroke="currentColor" stroke-width="2">
                        <path d="M22 11.08V12a10 10 0 1 1-5.93-9.14"/>
                        <polyline points="22 4 12 14.01 9 11.01"/>
                    </svg>
                </div>
                <div class="stat-number">{len(original) - changed_count}</div>
                <div class="stat-label">Unchanged</div>
                <div class="stat-badge">{round(100 - change_percent, 1)}%</div>
            </div>
        </div>

        <!-- Actions Bar -->
        <div class="actions-bar">
            <div class="legend">
                <div class="legend-item">
                    <del>removed</del>
                    <span>Deleted</span>
                </div>
                <div class="legend-item">
                    <ins>added</ins>
                    <span>Inserted</span>
                </div>
            </div>
            <div class="jump-links">
                <span class="jump-label">Jump to:</span>
                {''.join(f'<a href="#entry-{r["index"]}" class="jump-link">{r["index"]}</a>' for r in rows if r['changed']) or '<span class="no-changes">No changes detected</span>'}
            </div>
        </div>

        <!-- Table -->
        <div class="table-wrapper">
            <table>
                <thead>
                    <tr>
                        <th style="width: 100px;">#</th>
                        <th style="width: 200px;">Timestamp</th>
                        <th>Original</th>
                        <th>Corrected</th>
                        <th>Diff View</th>
                    </tr>
                </thead>
                <tbody>
'''

    for row in rows:
        changed_class = 'changed' if row['changed'] else ''
        dot_class = 'changed' if row['changed'] else 'unchanged'
        diff_display = row['diff'] if row['changed'] else f'<span class="unchanged-text">{row["original"]}</span>'

        html_content += f'''                <tr id="entry-{row['index']}" class="{changed_class}">
                    <td>
                        <div class="entry-index">
                            <span class="change-dot {dot_class}"></span>
                            <span class="entry-num">{row['index']}</span>
                        </div>
                    </td>
                    <td><span class="timestamp">{row['timestamp']}</span></td>
                    <td class="text-cell">{row['original']}</td>
                    <td class="text-cell">{row['corrected']}</td>
                    <td class="diff-cell">{diff_display}</td>
                </tr>
'''

    html_content += '''                </tbody>
            </table>
        </div>
    </div>

    <!-- Scroll to top button -->
    <button class="scroll-top" onclick="window.scrollTo({top: 0, behavior: 'smooth'})">
        <svg viewBox="0 0 24 24" fill="none" stroke="currentColor" stroke-width="2">
            <polyline points="18 15 12 9 6 15"/>
        </svg>
    </button>

    <script>
        // Show/hide scroll to top button
        window.addEventListener('scroll', () => {
            const btn = document.querySelector('.scroll-top');
            if (window.scrollY > 300) {
                btn.classList.add('visible');
            } else {
                btn.classList.remove('visible');
            }
        });
    </script>
</body>
</html>
'''

    with open(output_path, 'w', encoding='utf-8') as f:
        f.write(html_content)

    return len(original), changed_count


@dataclass
class SubtitleEntry:
    """Represents a single subtitle entry."""
    index: int
    start_time: str
    end_time: str
    text: str
    raw_timestamp_line: str  # Preserve exact formatting


def parse_srt(filepath: str) -> List[SubtitleEntry]:
    """Parse an SRT file into a list of SubtitleEntry objects."""
    with open(filepath, 'r', encoding='utf-8') as f:
        content = f.read()

    entries = []
    # Split by double newlines (or more), handling various line ending styles
    blocks = re.split(r'\n\n+', content.strip())

    for block in blocks:
        lines = block.strip().split('\n')
        if len(lines) < 2:
            continue

        try:
            index = int(lines[0].strip())
        except ValueError:
            continue

        # Parse timestamp line
        timestamp_line = lines[1].strip()
        timestamp_match = re.match(
            r'(\d{2}:\d{2}:\d{2},\d{3})\s*-->\s*(\d{2}:\d{2}:\d{2},\d{3})',
            timestamp_line
        )

        if not timestamp_match:
            continue

        start_time = timestamp_match.group(1)
        end_time = timestamp_match.group(2)
        text = '\n'.join(lines[2:]) if len(lines) > 2 else ''

        entries.append(SubtitleEntry(
            index=index,
            start_time=start_time,
            end_time=end_time,
            text=text,
            raw_timestamp_line=timestamp_line
        ))

    return entries


def validate_correction(original_path: str, corrected_path: str) -> Tuple[bool, List[str]]:
    """
    Validate that a corrected subtitle file maintains structural integrity.

    Returns:
        Tuple of (is_valid, list_of_issues)
    """
    issues = []

    original = parse_srt(original_path)
    corrected = parse_srt(corrected_path)

    # Check 1: Same number of entries
    if len(original) != len(corrected):
        issues.append(f"Entry count mismatch: original={len(original)}, corrected={len(corrected)}")
        return False, issues

    # Check 2: Validate each entry
    for i, (orig, corr) in enumerate(zip(original, corrected)):
        # Check index
        if orig.index != corr.index:
            issues.append(f"Entry {i+1}: Index mismatch (orig={orig.index}, corr={corr.index})")

        # Check timestamps (must be EXACTLY the same)
        if orig.start_time != corr.start_time:
            issues.append(f"Entry {orig.index}: Start time changed from '{orig.start_time}' to '{corr.start_time}'")

        if orig.end_time != corr.end_time:
            issues.append(f"Entry {orig.index}: End time changed from '{orig.end_time}' to '{corr.end_time}'")

        # Check raw timestamp line preservation
        if orig.raw_timestamp_line != corr.raw_timestamp_line:
            issues.append(f"Entry {orig.index}: Timestamp line formatting changed")

    is_valid = len(issues) == 0
    return is_valid, issues


def show_diff(original_path: str, corrected_path: str) -> List[Dict]:
    """
    Show text differences between original and corrected files.
    Only shows entries where text has changed.
    """
    original = parse_srt(original_path)
    corrected = parse_srt(corrected_path)

    diffs = []

    for orig, corr in zip(original, corrected):
        if orig.text != corr.text:
            diffs.append({
                'index': orig.index,
                'timestamp': f"{orig.start_time} --> {orig.end_time}",
                'original': orig.text,
                'corrected': corr.text
            })

    return diffs


# Common speech recognition error patterns
ERROR_PATTERNS = {
    # Chinese phonetic errors
    '绘画': ('会话', 'session/conversation context'),
    '源数据': ('元数据', 'metadata'),
    '本科': ('本课', 'this lesson'),
    '事例': ('示例', 'example'),
    '中间键': ('中间件', 'middleware'),
    '详细': ('消息', 'message (context-dependent)'),

    # LangChain ecosystem
    r'[Ll]uncheon': ('langchain', 'LangChain package'),
    r'蓝[犬卷]': ('LangChain', 'LangChain framework'),
    r'[Ll]antern': ('LangChain', 'LangChain framework'),
    r'land\s*GRAPH': ('langgraph', 'LangGraph package'),
    r'LAN\s*GRAPH': ('langgraph', 'LangGraph package'),

    # OpenAI
    r'open\s*EI': ('OpenAI', 'OpenAI'),
    r'open\s*Email': ('OpenAI', 'OpenAI'),

    # Memory components
    r'[Aa]\s*memory\s*[Ss]erver': ('MemorySaver', 'Memory component'),
    r'amneserver': ('MemorySaver', 'Memory component'),
    r'check\s*point(?!er)': ('checkpointer', 'Checkpointer component'),
    r'Sharepoint': ('checkpointer', 'Checkpointer component'),

    # Code terms
    r'wrong\s*time': ('runtime', 'runtime'),
    r'confict': ('config', 'configuration'),
}


def analyze_file(filepath: str, custom_terms: Optional[List[str]] = None) -> List[Dict]:
    """
    Analyze a subtitle file for potential speech recognition errors.

    Args:
        filepath: Path to the SRT file
        custom_terms: Optional list of expected terms to help identify errors

    Returns:
        List of potential issues found
    """
    entries = parse_srt(filepath)
    potential_issues = []

    for entry in entries:
        text = entry.text
        entry_issues = []

        # Check against known error patterns
        for pattern, (correction, description) in ERROR_PATTERNS.items():
            if re.search(pattern, text):
                entry_issues.append({
                    'pattern': pattern,
                    'suggestion': correction,
                    'description': description
                })

        # Check for "underscore" that should be "_"
        if 'underscore' in text.lower():
            entry_issues.append({
                'pattern': 'underscore',
                'suggestion': '_',
                'description': 'Likely a variable name with underscore'
            })

        if entry_issues:
            potential_issues.append({
                'index': entry.index,
                'timestamp': f"{entry.start_time} --> {entry.end_time}",
                'text': text,
                'issues': entry_issues
            })

    return potential_issues


def main():
    parser = argparse.ArgumentParser(description='Subtitle validation and analysis tool')
    subparsers = parser.add_subparsers(dest='command', help='Commands')

    # Validate command
    validate_parser = subparsers.add_parser('validate', help='Validate corrected file against original')
    validate_parser.add_argument('original', help='Original SRT file')
    validate_parser.add_argument('corrected', help='Corrected SRT file')

    # Diff command
    diff_parser = subparsers.add_parser('diff', help='Show text differences between files')
    diff_parser.add_argument('original', help='Original SRT file')
    diff_parser.add_argument('corrected', help='Corrected SRT file')
    diff_parser.add_argument('--limit', type=int, default=50, help='Max differences to show')
    diff_parser.add_argument('--no-color', action='store_true', help='Disable colored output')
    diff_parser.add_argument('--simple', action='store_true', help='Use simple line-based diff instead of word-level')
    diff_parser.add_argument('--html', metavar='OUTPUT', help='Generate HTML diff report to specified file')
    diff_parser.add_argument('--all', action='store_true', help='Show all entries (not just changed ones) in terminal output')

    # Analyze command
    analyze_parser = subparsers.add_parser('analyze', help='Analyze file for potential errors')
    analyze_parser.add_argument('input', help='Input SRT file')
    analyze_parser.add_argument('--terms', help='Comma-separated list of expected terms')

    args = parser.parse_args()

    if args.command == 'validate':
        print(f"Validating: {args.corrected}")
        print(f"Against:    {args.original}\n")

        is_valid, issues = validate_correction(args.original, args.corrected)

        if is_valid:
            print("✅ Validation PASSED")
            print("   - Entry counts match")
            print("   - All timestamps preserved")
            print("   - All indices preserved")
        else:
            print("❌ Validation FAILED")
            print(f"   Found {len(issues)} issue(s):\n")
            for issue in issues[:20]:  # Limit output
                print(f"   - {issue}")
            if len(issues) > 20:
                print(f"   ... and {len(issues) - 20} more issues")

        sys.exit(0 if is_valid else 1)

    elif args.command == 'diff':
        # HTML output mode
        if args.html:
            total, changed = generate_html_diff(args.original, args.corrected, args.html)
            print(f"✅ HTML diff report generated: {args.html}")
            print(f"   Total entries: {total}")
            print(f"   Changed: {changed}")
            print(f"   Unchanged: {total - changed}")
            print(f"\n   Open in browser to view the full comparison.")
            sys.exit(0)

        # Terminal output mode
        use_color = not args.no_color and sys.stdout.isatty()

        if args.all:
            # Show all entries (changed and unchanged)
            original = parse_srt(args.original)
            corrected = parse_srt(args.corrected)
            corr_map = {e.index: e for e in corrected}

            changed_count = sum(1 for o in original if corr_map.get(o.index) and o.text != corr_map[o.index].text)

            if use_color:
                print(f"{Colors.BOLD}Subtitle Diff Report (Full){Colors.RESET}")
                print(f"{Colors.DIM}Original:  {args.original}{Colors.RESET}")
                print(f"{Colors.DIM}Corrected: {args.corrected}{Colors.RESET}")
                print()
                print(f"Total entries: {len(original)}, Changed: {Colors.CYAN}{changed_count}{Colors.RESET}\n")
                print(f"{Colors.DIM}Legend: {Colors.RED}[-deleted-]{Colors.RESET} {Colors.GREEN}{{+added+}}{Colors.RESET}\n")
            else:
                print(f"Subtitle Diff Report (Full)")
                print(f"Original:  {args.original}")
                print(f"Corrected: {args.corrected}")
                print()
                print(f"Total entries: {len(original)}, Changed: {changed_count}\n")
                print("Legend: [-deleted-] {+added+}\n")

            for orig in original[:args.limit]:
                corr = corr_map.get(orig.index)
                is_changed = corr and orig.text != corr.text

                if use_color:
                    marker = f"{Colors.YELLOW}*{Colors.RESET}" if is_changed else " "
                    print(f"{marker} {Colors.BLUE}[{orig.index}]{Colors.RESET} {Colors.DIM}{orig.start_time} --> {orig.end_time}{Colors.RESET}")
                else:
                    marker = "*" if is_changed else " "
                    print(f"{marker} [{orig.index}] {orig.start_time} --> {orig.end_time}")

                if is_changed:
                    inline_diff = word_level_diff(orig.text, corr.text, use_color)
                    print(f"    {inline_diff}")
                else:
                    if use_color:
                        print(f"    {Colors.DIM}{orig.text}{Colors.RESET}")
                    else:
                        print(f"    {orig.text}")
                print()

            if len(original) > args.limit:
                print(f"... and {len(original) - args.limit} more entries")

        else:
            # Show only changed entries (default)
            diffs = show_diff(args.original, args.corrected)

            if use_color:
                print(f"{Colors.BOLD}Subtitle Diff Report{Colors.RESET}")
                print(f"{Colors.DIM}Original:  {args.original}{Colors.RESET}")
                print(f"{Colors.DIM}Corrected: {args.corrected}{Colors.RESET}")
                print()
                print(f"Found {Colors.CYAN}{len(diffs)}{Colors.RESET} text changes:\n")
                print(f"{Colors.DIM}Legend: {Colors.RED}[-deleted-]{Colors.RESET} {Colors.GREEN}{{+added+}}{Colors.RESET}\n")
            else:
                print(f"Subtitle Diff Report")
                print(f"Original:  {args.original}")
                print(f"Corrected: {args.corrected}")
                print()
                print(f"Found {len(diffs)} text changes:\n")
                print("Legend: [-deleted-] {+added+}\n")

            for diff in diffs[:args.limit]:
                if use_color:
                    print(f"{Colors.BLUE}[{diff['index']}]{Colors.RESET} {Colors.DIM}{diff['timestamp']}{Colors.RESET}")
                else:
                    print(f"[{diff['index']}] {diff['timestamp']}")

                if args.simple:
                    if use_color:
                        print(f"  {Colors.RED}- {diff['original']}{Colors.RESET}")
                        print(f"  {Colors.GREEN}+ {diff['corrected']}{Colors.RESET}")
                    else:
                        print(f"  - {diff['original']}")
                        print(f"  + {diff['corrected']}")
                else:
                    inline_diff = word_level_diff(diff['original'], diff['corrected'], use_color)
                    print(f"  {inline_diff}")
                print()

            if len(diffs) > args.limit:
                print(f"... and {len(diffs) - args.limit} more changes")

            # Hint about HTML output
            if use_color:
                print(f"\n{Colors.DIM}Tip: Use --html report.html to generate a full HTML comparison report{Colors.RESET}")

    elif args.command == 'analyze':
        custom_terms = args.terms.split(',') if args.terms else None
        issues = analyze_file(args.input, custom_terms)

        print(f"Found {len(issues)} entries with potential issues:\n")

        for item in issues[:30]:
            print(f"[{item['index']}] {item['timestamp']}")
            print(f"  Text: {item['text'][:60]}...")
            for issue in item['issues']:
                print(f"    → '{issue['pattern']}' might be '{issue['suggestion']}' ({issue['description']})")
            print()

        if len(issues) > 30:
            print(f"... and {len(issues) - 30} more entries with potential issues")

    else:
        parser.print_help()


if __name__ == '__main__':
    main()

Related skills

Lark Openapi ExplorerInstantly explore, test, and generate calls against the full Lark (Feishu) OpenAPI surface without leaving their agent workflow.493k

Lark EventConsume real-time events from Lark/Feishu as structured NDJSON streams inside AI agent workflows.387k16k

Lark Openapi ExplorerWhen an existing Lark/Feishu skill or CLI command cannot fulfill a specific requirement and they need to discover and invoke the exact native OpenAPI endpoint.386k16k

Just ScrapeQuickly search, crawl, extract structured JSON, or monitor web pages without writing custom scraping code.245k41

Lark AppsQuery the current visibility and permission scope of a Lark (Feishu) app without writing HTTP client code.235k16k

Design An InterfaceGenerate multiple radically different interface or API designs in parallel before committing to one.188k198k

How it compares

Pick subtitle-correction over generic proofreading skills when you need timestamp-safe .srt ASR cleanup with domain terminology and structural validation rather than free-form text editing.

FAQ

Does subtitle-correction change .srt timestamps?

subtitle-correction never modifies .srt timestamps, sequence numbers, or entry boundaries. The skill only fixes spoken-text mistranscriptions inside caption lines and writes output to a -corrected.srt file after subtitle_tool.py validate confirms structural integrity.

What languages does subtitle-correction support?

subtitle-correction supports Chinese and English subtitles, including mixed-language technical content. The skill corrects phonetic homophone errors in Chinese ASR output and common English-Chinese garbling such as Luncheon to LangChain or open EI to OpenAI.

How do you review subtitle changes after correction?

subtitle-correction uses scripts/subtitle_tool.py diff with --html to generate a browser-viewable comparison report showing original, corrected, and word-level diff columns with change counts. Terminal diff and analyze commands are also available before saving.

Backend & APIsbackendintegrations