一键在 Manus 中运行任何 Skill

fixing

This skill should be used when fixing bugs, errors, issues, or problems of any complexity. It provides intelligent issue resolution with mode selection (autonomous/human-in-the-loop/quick). The skill auto-classifies issue complexity (simple/moderate/complex/parallel), activates relevant skills (debugging, problem-solving, sequential-thinking, brainstorming, context-engineering), and routes to appropriate workflow. This skill should be activated when users report bugs, test failures, type errors, CI/CD failures, log errors, UI issues, or any code that needs fixing.

在 Manus 中运行

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安装命令

npx skills add https://github.com/hoanghd218/bandoxaynha.ai --skill fixing

复制此命令并粘贴到 Claude Code 中以安装该技能

来源

hoanghd218/bandoxaynha.ai

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更新时间2026年1月24日 01:54

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SKILL.md

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name	fixing
description	This skill should be used when fixing bugs, errors, issues, or problems of any complexity. It provides intelligent issue resolution with mode selection (autonomous/human-in-the-loop/quick). The skill auto-classifies issue complexity (simple/moderate/complex/parallel), activates relevant skills (debugging, problem-solving, sequential-thinking, brainstorming, context-engineering), and routes to appropriate workflow. This skill should be activated when users report bugs, test failures, type errors, CI/CD failures, log errors, UI issues, or any code that needs fixing.
version	1.0.0

Fixing

Unified skill for fixing issues of any complexity with intelligent routing.

Step 0: Mode Selection

First action: Use AskUserQuestion to determine workflow mode:

Option	Recommend When	Behavior
Autonomous	Simple/moderate issues	Auto-approve if score >= 9.5 & 0 critical
Human-in-the-loop	Critical/production code	Pause for approval at each step
Quick	Type errors, lint, trivial bugs	Fast debug → fix → review cycle

See references/mode-selection.md for AskUserQuestion format.

Step 1: Complexity Assessment

Classify before routing. See references/complexity-assessment.md.

Level	Indicators	Workflow
Simple	Single file, clear error, type/lint	`references/workflow-quick.md`
Moderate	Multi-file, root cause unclear	`references/workflow-standard.md`
Complex	System-wide, architecture impact	`references/workflow-deep.md`
Parallel	2+ independent issues	Parallel `fullstack-developer` agents

Skill Activation Matrix

See references/skill-activation-matrix.md for complete matrix.

Always activate: debugging (all workflows) Conditional: problem-solving, sequential-thinking, brainstorming, context-engineering Subagents: debugger, researcher, planner, code-reviewer, tester, git-manager Parallel: Multiple Explore agents for scouting, Bash agents for verification

Output Format

Unified step markers:

✓ Step 0: [Mode] selected - [Complexity] detected
✓ Step 1: Root cause identified - [summary]
✓ Step 2: Fix implemented - [N] files changed
✓ Step 3: Tests [X/X passed]
✓ Step 4: Review [score]/10 - [status]
✓ Step 5: Complete - [action taken]

References

Load as needed:

references/mode-selection.md - AskUserQuestion format for mode
references/complexity-assessment.md - Classification criteria
references/workflow-quick.md - Quick: debug → fix → review
references/workflow-standard.md - Standard: full pipeline
references/workflow-deep.md - Deep: research + brainstorm + plan
references/review-cycle.md - Review logic (autonomous vs HITL)
references/skill-activation-matrix.md - When to activate each skill
references/parallel-exploration.md - Parallel Explore/Bash patterns

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Process and generate multimedia content using Google Gemini API for better vision capabilities. Capabilities include analyze audio files (transcription with timestamps, summarization, speech understanding, music/sound analysis up to 9.5 hours), understand images (better image analysis than Claude models, captioning, reasoning, object detection, design extraction, OCR, visual Q&A, segmentation, handle multiple images), process videos (scene detection, Q&A, temporal analysis, YouTube URLs, up to 6 hours), extract from documents (PDF tables, forms, charts, diagrams, multi-page), generate images (text-to-image with Imagen 4, editing, composition, refinement), generate videos (text-to-video with Veo 3, 8-second clips with native audio). Use when working with audio/video files, analyzing images or screenshots (instead of default vision capabilities of Claude, only fallback to Claude's vision capabilities if needed), processing PDF documents, extracting structured data from media, creating images/videos from text pr

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hoanghd218/bandoxaynha.ai

Browser automation, debugging, and performance analysis using Puppeteer CLI scripts. Use for automating browsers, taking screenshots, analyzing performance, monitoring network traffic, web scraping, form automation, and JavaScript debugging.

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Deploy and manage cloud infrastructure on Cloudflare (Workers, R2, D1, KV, Pages, Durable Objects, Browser Rendering), Docker containers, and Google Cloud Platform (Compute Engine, GKE, Cloud Run, App Engine, Cloud Storage). Use when deploying serverless functions to the edge, configuring edge computing solutions, managing Docker containers and images, setting up CI/CD pipelines, optimizing cloud infrastructure costs, implementing global caching strategies, working with cloud databases, or building cloud-native applications.

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docs-seeker

hoanghd218/bandoxaynha.ai

Search technical documentation using executable scripts to detect query type, fetch from llms.txt sources (context7.com), and analyze results. Use when user needs: (1) Topic-specific documentation (features/components/concepts), (2) Library/framework documentation, (3) GitHub repository analysis, (4) Documentation discovery with automated agent distribution strategy

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mcp-management

hoanghd218/bandoxaynha.ai

Manage Model Context Protocol (MCP) servers - discover, analyze, and execute tools/prompts/resources from configured MCP servers. Use when working with MCP integrations, need to discover available MCP capabilities, filter MCP tools for specific tasks, execute MCP tools programmatically, access MCP prompts/resources, or implement MCP client functionality. Supports intelligent tool selection, multi-server management, and context-efficient capability discovery.

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hoanghd218/bandoxaynha.ai

Implement payment integrations with SePay (Vietnamese payment gateway with VietQR, bank transfers, cards) and Polar (global SaaS monetization platform with subscriptions, usage-based billing, automated benefits). Use when integrating payment processing, implementing checkout flows, managing subscriptions, handling webhooks, processing bank transfers, generating QR codes, automating benefit delivery, or building billing systems. Supports authentication (API keys, OAuth2), product management, customer portals, tax compliance (Polar as MoR), and comprehensive SDK integrations (Node.js, PHP, Python, Go, Laravel, Next.js).

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来源

hoanghd218

hoanghd218/bandoxaynha.ai

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在 Manus 中运行

适用职业SOC

软件开发工程师计算机与数学类职业15-1252L4

name	fixing
description	This skill should be used when fixing bugs, errors, issues, or problems of any complexity. It provides intelligent issue resolution with mode selection (autonomous/human-in-the-loop/quick). The skill auto-classifies issue complexity (simple/moderate/complex/parallel), activates relevant skills (debugging, problem-solving, sequential-thinking, brainstorming, context-engineering), and routes to appropriate workflow. This skill should be activated when users report bugs, test failures, type errors, CI/CD failures, log errors, UI issues, or any code that needs fixing.
version	1.0.0

Fixing

Unified skill for fixing issues of any complexity with intelligent routing.

Step 0: Mode Selection

First action: Use AskUserQuestion to determine workflow mode:

Option	Recommend When	Behavior
Autonomous	Simple/moderate issues	Auto-approve if score >= 9.5 & 0 critical
Human-in-the-loop	Critical/production code	Pause for approval at each step
Quick	Type errors, lint, trivial bugs	Fast debug → fix → review cycle

See references/mode-selection.md for AskUserQuestion format.

Step 1: Complexity Assessment

Classify before routing. See references/complexity-assessment.md.

Level	Indicators	Workflow
Simple	Single file, clear error, type/lint	`references/workflow-quick.md`
Moderate	Multi-file, root cause unclear	`references/workflow-standard.md`
Complex	System-wide, architecture impact	`references/workflow-deep.md`
Parallel	2+ independent issues	Parallel `fullstack-developer` agents

Skill Activation Matrix

See references/skill-activation-matrix.md for complete matrix.

Output Format

Unified step markers:

✓ Step 0: [Mode] selected - [Complexity] detected
✓ Step 1: Root cause identified - [summary]
✓ Step 2: Fix implemented - [N] files changed
✓ Step 3: Tests [X/X passed]
✓ Step 4: Review [score]/10 - [status]
✓ Step 5: Complete - [action taken]

References

Load as needed:

references/mode-selection.md - AskUserQuestion format for mode
references/complexity-assessment.md - Classification criteria
references/workflow-quick.md - Quick: debug → fix → review
references/workflow-standard.md - Standard: full pipeline
references/workflow-deep.md - Deep: research + brainstorm + plan
references/review-cycle.md - Review logic (autonomous vs HITL)
references/skill-activation-matrix.md - When to activate each skill
references/parallel-exploration.md - Parallel Explore/Bash patterns