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AmnadTaowsoam

Live Chat Implementation

@AmnadTaowsoam/Live Chat Implementation
AmnadTaowsoam
2
0 forks
Updated 4/7/2026
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Live Chat: Live chat implementation enables real-time communication between users and support agents, providing instant customer support and improving user satisfaction. Effective live chat systems handle real-t

Installation

$npx agent-skills-cli install @AmnadTaowsoam/Live Chat Implementation
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Details

Path29-customer-support/live-chat/SKILL.md
Branchmain
Scoped Name@AmnadTaowsoam/Live Chat Implementation

Usage

After installing, this skill will be available to your AI coding assistant.

Verify installation:

npx agent-skills-cli list

Skill Instructions


id: SKL-live-LIVECHAT name: Live Chat description: Live chat implementation enables real-time communication between users and support agents, providing instant customer support and improving user satisfaction. Effective live chat systems handle real-t version: 1.0.0 status: active owner: '@cerebra-team' last_updated: '2026-02-22' category: Backend tags:

  • api
  • backend
  • server
  • database stack:
  • Python
  • Node.js
  • REST API
  • GraphQL difficulty: Intermediate

Live Chat

Skill Profile

(Select at least one profile to enable specific modules)

  • DevOps
  • Backend
  • Frontend
  • AI-RAG
  • Security Critical

Overview

Live chat implementation enables real-time communication between users and support agents, providing instant customer support and improving user satisfaction. Effective live chat systems handle real-time messaging, typing indicators, file sharing, chat history, and agent assignment.



Why This Matters

  • <Benefit>: <short explanation>
  • <Benefit>: <short explanation>
  • <Benefit>: <short explanation>

Core Concepts

Inputs / Outputs / Contracts

  • Inputs:
    • <e.g., env vars, request payload, file paths, schema>
  • Entry Conditions:
    • <Pre-requisites: e.g., Repo initialized, DB running, specific branch checked out>
  • Outputs:
    • <e.g., artifacts (PR diff, docs, tests, dashboard JSON)>
  • Artifacts Required (Deliverables):
    • <e.g., Code Diff, Unit Tests, Migration Script, API Docs>
  • Acceptance Evidence:
    • <e.g., Test Report (screenshot/log), Benchmark Result, Security Scan Report>
  • Success Criteria:
    • <e.g., p95 < 300ms, coverage ≥ 80%>

Skill Composition

  • Depends on: None
  • Compatible with: None
  • Conflicts with: None
  • Related Skills: None

Quick Start

Assumptions / Constraints / Non-goals

  • Assumptions:
    • Development environment is properly configured
    • Required dependencies are available
    • Team has basic understanding of domain
  • Constraints:
    • Must follow existing codebase conventions
    • Time and resource limitations
    • Compatibility requirements
  • Non-goals:
    • This skill does not cover edge cases outside scope
    • Not a replacement for formal training

Compatibility & Prerequisites

  • Supported Versions:
    • Python 3.8+
    • Node.js 16+
    • Modern browsers (Chrome, Firefox, Safari, Edge)
  • Required AI Tools:
    • Code editor (VS Code recommended)
    • Testing framework appropriate for language
    • Version control (Git)
  • Dependencies:
    • Language-specific package manager
    • Build tools
    • Testing libraries
  • Environment Setup:
    • .env.example keys: API_KEY, DATABASE_URL (no values)

Test Scenario Matrix (QA Strategy)

TypeFocus AreaRequired Scenarios / Mocks
UnitCore LogicMust cover primary logic and at least 3 edge/error cases. Target minimum 80% coverage
IntegrationDB / APIAll external API calls or database connections must be mocked during unit tests
E2EUser JourneyCritical user flows to test
PerformanceLatency / LoadBenchmark requirements
SecurityVuln / AuthSAST/DAST or dependency audit
FrontendUX / A11yAccessibility checklist (WCAG), Performance Budget (Lighthouse score)

Technical Guardrails & Security Threat Model

1. Security & Privacy (Threat Model)

  • Top Threats: Injection attacks, authentication bypass, data exposure
  • Data Handling: Sanitize all user inputs to prevent Injection attacks. Never log raw PII
  • Secrets Management: No hardcoded API keys. Use Env Vars/Secrets Manager
  • Authorization: Validate user permissions before state changes

2. Performance & Resources

  • Execution Efficiency: Consider time complexity for algorithms
  • Memory Management: Use streams/pagination for large data
  • Resource Cleanup: Close DB connections/file handlers in finally blocks

3. Architecture & Scalability

  • Design Pattern: Follow SOLID principles, use Dependency Injection
  • Modularity: Decouple logic from UI/Frameworks

4. Observability & Reliability

  • Logging Standards: Structured JSON, include trace IDs request_id
  • Metrics: Track error_rate, latency, queue_depth
  • Error Handling: Standardized error codes, no bare except
  • Observability Artifacts:
    • Log Fields: timestamp, level, message, request_id
    • Metrics: request_count, error_count, response_time
    • Dashboards/Alerts: High Error Rate > 5%

Agent Directives & Error Recovery

(ข้อกำหนดสำหรับ AI Agent ในการคิดและแก้ปัญหาเมื่อเกิดข้อผิดพลาด)

  • Thinking Process: Analyze root cause before fixing. Do not brute-force.
  • Fallback Strategy: Stop after 3 failed test attempts. Output root cause and ask for human intervention/clarification.
  • Self-Review: Check against Guardrails & Anti-patterns before finalizing.
  • Output Constraints: Output ONLY the modified code block. Do not explain unless asked.

Definition of Done (DoD) Checklist

  • Tests passed + coverage met
  • Lint/Typecheck passed
  • Logging/Metrics/Trace implemented
  • Security checks passed
  • Documentation/Changelog updated
  • Accessibility/Performance requirements met (if frontend)

Anti-patterns

Reference Links & Examples

  • Internal documentation and examples
  • Official documentation and best practices
  • Community resources and discussions

Versioning & Changelog

  • Version: 1.0.0
  • Changelog:
    • 2026-02-22: Initial version with complete template structure
Live Chat Implementation by AmnadTaowsoam | Agent Skills