ac-stop-hook-analyzer
Analyze context and decide on continuation via Stop hook. Use when determining if work should continue, analyzing completion status, making continuation decisions, or implementing the Two-Claude pattern.
Best use case
ac-stop-hook-analyzer is best used when you need a repeatable AI agent workflow instead of a one-off prompt.
Analyze context and decide on continuation via Stop hook. Use when determining if work should continue, analyzing completion status, making continuation decisions, or implementing the Two-Claude pattern.
Teams using ac-stop-hook-analyzer should expect a more consistent output, faster repeated execution, less prompt rewriting.
When to use this skill
- You want a reusable workflow that can be run more than once with consistent structure.
When not to use this skill
- You only need a quick one-off answer and do not need a reusable workflow.
- You cannot install or maintain the underlying files, dependencies, or repository context.
Installation
Claude Code / Cursor / Codex
Manual Installation
- Download SKILL.md from GitHub
- Place it in
.claude/skills/ac-stop-hook-analyzer/SKILL.mdinside your project - Restart your AI agent — it will auto-discover the skill
How ac-stop-hook-analyzer Compares
| Feature / Agent | ac-stop-hook-analyzer | Standard Approach |
|---|---|---|
| Platform Support | Not specified | Limited / Varies |
| Context Awareness | High | Baseline |
| Installation Complexity | Unknown | N/A |
Frequently Asked Questions
What does this skill do?
Analyze context and decide on continuation via Stop hook. Use when determining if work should continue, analyzing completion status, making continuation decisions, or implementing the Two-Claude pattern.
Where can I find the source code?
You can find the source code on GitHub using the link provided at the top of the page.
SKILL.md Source
# AC Stop Hook Analyzer
Analyze context to decide on continuation (Two-Claude Pattern).
## Purpose
Implements the Analyzer role in the Two-Claude Pattern, using Opus 4.5 to intelligently decide whether to continue autonomous operation.
## Quick Start
```python
from scripts.stop_hook_analyzer import StopHookAnalyzer
analyzer = StopHookAnalyzer(project_dir)
decision = await analyzer.should_continue()
# Returns: {"decision": "block", "reason": "Continue with api-003"}
```
## Decision Logic
- Check completion against objective
- Analyze remaining features
- Validate safety limits
- Return continue/stop decision
## API Reference
See `scripts/stop_hook_analyzer.py` for full implementation.Related Skills
add-hook
Create a custom React hook with TypeScript and tests
add-hook-whatifwedigdeeper-application-tracker
Create a custom React hook with TypeScript and tests
add-feature-hook
Creates TanStack Query hooks for API features with authentication. Use when connecting frontend to backend endpoints, creating data fetching hooks.
ab-testing-analyzer
全面的AB测试分析工具，支持实验设计、统计检验、用户分群分析和可视化报告生成。用于分析产品改版、营销活动、功能优化等AB测试结果，提供统计显著性检验和深度洞察。
ab-test-analyzer
Ab Test Analyzer - Auto-activating skill for Data Analytics. Triggers on: ab test analyzer, ab test analyzer Part of the Data Analytics skill category.
meeting-insights-analyzer
Analyzes meeting transcripts and recordings to uncover behavioral patterns, communication insights, and actionable feedback. Identifies when you avoid conflict, use filler words, dominate conversations, or miss opportunities to listen. Perfect for professionals seeking to improve their communication and leadership skills.
whisper-transcribe
Transcribes audio and video files to text using OpenAI's Whisper CLI, enhanced with contextual grounding from local markdown files for improved accuracy.
astro
This skill provides essential Astro framework patterns, focusing on server-side rendering (SSR), static site generation (SSG), middleware, and TypeScript best practices. It helps AI agents implement secure authentication, manage API routes, and debug rendering behaviors within Astro projects.
tech-blog
Generates comprehensive technical blog posts, offering detailed explanations of system internals, architecture, and implementation, either through source code analysis or document-driven research.
grail-miner
This skill assists in setting up, managing, and optimizing Grail miners on Bittensor Subnet 81, handling tasks like environment configuration, R2 storage, model checkpoint management, and performance tuning.
modal-deployment
Run Python code in the cloud with serverless containers, GPUs, and autoscaling using Modal. This skill enables agents to generate code for deploying ML models, running batch jobs, serving APIs, and scaling compute-intensive workloads.
lets-go-rss
A lightweight, full-platform RSS subscription manager that aggregates content from YouTube, Vimeo, Behance, Twitter/X, and Chinese platforms like Bilibili, Weibo, and Douyin, featuring deduplication and AI smart classification.