Quick Fix Suggestion

> Note: If you have mcporter installed locally, you should use mcporter to invoke the MCP tool instead of directly calling the MCP tool. The mcporter CLI provides a more convenient interface and better error handling.

Quick Fix Suggestion via Gitee MCP

Analyze a Gitee Issue and generate intelligent fix suggestions including:

• Identification of files that need to be modified
• Code location hints (line numbers, function names)
• Draft implementation code snippets
• Step-by-step implementation plan

Prerequisites

• Gitee MCP Server configured (tools: get_repo_issue_detail, list_comments (resource_type: issue), search_files_by_content, get_file_content)
• Must be executed in a local clone of the repository
• User must provide: repository owner, repository name, Issue number

Local-First Search Strategy

> Why Local-First? > > This skill prioritizes local file operations over Gitee API for code search: > - Speed: Local searches complete in milliseconds vs. seconds for API calls > - No Rate Limits: No 100 requests/minute restriction > - Real-time: Searches include uncommitted local changes > - Cost: Zero API usage costs

Tool Selection Priority

| Priority | Tool | Availability | |----------|------|--------------| | 1st | glob, grep (built-in) | 100% | | 2nd | ast_grep_search, lsp_find_references | 100% | | 3rd | Git commands (via bash) | ~90% | | Last | Gitee API (search_files_by_content) | Fallback only |

Steps

Step 1: Fetch Issue Details

Use get_repo_issue_detail to retrieve full Issue information:

• Title and description
• Labels (bug/feature/enhancement)
• Existing comments

Step 2: Analyze Issue Content

Identify Issue Type:

• bug: error, crash, broken, not working, 错误, 失败
• feature: add, support, implement, new, 新增, 添加
• enhancement: improve, optimize, 改进, 优化

Extract Code Entities:

• Function names (in backticks or patterns)
• Class names
• File names
• Error messages / stack traces

Step 3: Search Code (Local-First)

Use built-in tools in priority order:

// 1. File name search (fastest)
glob(`**/*${keyword}*.{js,ts,py,go}`, { cwd: localRepoPath })

// 2. Content search
grep({
  pattern: `function\\s+${funcName}`,
  path: localRepoPath,
  output_mode: "content"
})

// 3. AST search (semantic)
ast_grep_search({
  pattern: "function $NAME($$$) { $$$ }",
  lang: "javascript",
  paths: [localRepoPath]
})

// 4. Fallback: Remote search (max 3 calls)
if (localResults.length 
Code Draft

```{language}
// Current:
{existing_code}

// Suggested:
{suggested_code}

Secondary Files (May Need Changes)

• {file_path}: {reason}

Implementation Plan

1. {step 1} - File: {file}, ~{time}
2. {step 2} - File: {file}, ~{time}

Testing Suggestions

• {test suggestion}

Questions for You

1. {uncertainty_question}

### Step 6: Handle User Response

- **Approve**: Summarize and transition to `implement-issue` skill
- **Adjust**: Re-analyze with new information
- **Search More**: Expand search scope
- **Cancel**: Offer other help

## Notes

- Always indicate confidence level - ask for clarification when uncertain
- Follow existing code patterns when suggesting changes
- Warn immediately if Issue mentions credentials/secrets
- If unable to locate relevant code, ask for more context rather than guessing

## References

- [Tool Reference Guide](references/TOOL_REFERENCE.md) - Detailed search patterns and tool usage

## Source & license

This open-source skill is cataloged on AgentStack and links to its original source — we do not rehost the code.

- **Author:** [oschina](https://github.com/oschina)
- **Source:** [oschina/gitee-agent-skills](https://github.com/oschina/gitee-agent-skills)
- **License:** MIT

Install and usage instructions live in the source repository linked above.