llm-application-dev-ai-assistant
You are an AI assistant development expert specializing in creating intelligent conversational interfaces, chatbots, and AI-powered applications. Design comprehensive AI assistant solutions with natur
- License 许可
- MIT
- 所属仓库
- agisota/old-one
- 最近更新
- 2026-07-04
- Stars
- ★ 3
- Forks
- 1
01 前言 Front Matter
- name
- llm-application-dev-ai-assistant
- triggers
- [ "llm application dev ai assistant" ]
- description
- You are an AI assistant development expert specializing in creating intelligent conversational interfaces, chatbots, and AI-powered applications. Design comprehensive AI assistant solutions with natur
03 SKILL.md 正文
AI Assistant Development
You are an AI assistant development expert specializing in creating intelligent conversational interfaces, chatbots, and AI-powered applications. Design comprehensive AI assistant solutions with natural language understanding, context management, and seamless integrations.
Context
The user needs to develop an AI assistant or chatbot with natural language capabilities, intelligent responses, and practical functionality. Focus on creating production-ready assistants that provide real value to users.
Requirements
$ARGUMENTS
Instructions
1. AI Assistant Architecture
Design comprehensive assistant architecture:
Assistant Architecture Framework
from typing import Dict, List, Optional, Any
from dataclasses import dataclass
from abc import ABC, abstractmethod
import asyncio
@dataclass
class ConversationContext:
"""Maintains conversation state and context"""
user_id: str
session_id: str
messages: List[Dict[str, Any]]
user_profile: Dict[str, Any]
conversation_state: Dict[str, Any]
metadata: Dict[str, Any]
class AIAssistantArchitecture:
def __init__(self, config: Dict[str, Any]):
self.config = config
self.components = self._initialize_components()
def design_architecture(self):
## Note
Skill content truncated for token efficiency. Full version available in the source repository.
04 同仓库更多 Skills
zoom-out
Tell the agent to zoom out and give broader context or a higher-level perspective. Use when you're unfamiliar with a section of code or need to understand how it fits into the bigger picture.
zeroize-audit
Detects missing zeroization of sensitive data in source code and identifies zeroization removed by compiler optimizations, with assembly-level analysis, and control-flow verification. Use for auditing C/C++/Rust code handling secrets, keys, passwords, or other sensitive data.
yeet
Use only when the user explicitly asks to stage, commit, push, and open a GitHub pull request in one flow using the GitHub CLI (`gh`).
yara-rule-authoring
Guides authoring of high-quality YARA-X detection rules for malware identification. Use when writing, reviewing, or optimizing YARA rules. Covers naming conventions, string selection, performance optimization, migration from legacy YARA, and false positive reduction. Triggers on: YARA, YARA-X, malware detection, threat hunting, IOC, signature, crx module, dex module.
x-twitter-growth
X/Twitter growth engine for building audience, crafting viral content, and analyzing engagement. Use when the user wants to grow on X/Twitter, write tweets or threads, analyze their X profile, research competitors on X, plan a posting strategy, or optimize engagement. Complements social-content (generic multi-platform) with X-specific depth: algorithm mechanics, thread engineering, reply strategy, profile optimization, and competitive intelligence via web search.
x-api
X/Twitter API integration for posting tweets, threads, reading timelines, search, and analytics. Covers OAuth auth patterns, rate limits, and platform-native content posting. Use when the user wants to interact with X programmatically.