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aif-fixaif 修复

Agent Skill

aif-fix 用于查找、检索和筛选相关信息,适合在 Codex、Claude、Cursor、Gemini CLI 中需要根据关键词、任务场景或来源线索快速定位候选结果时使用。可结合来源仓库、安装命令和原始 README 继续核验具体用法。安装前建议确认权限范围、维护状态,以及是否会触发联网、命令执行或文件读写。

总安装

685

周安装

28

GitHub Stars

535

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220
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安装说明

本站只整理中文说明和来源信息,不托管安装包,也不代用户安装。

GitHub

来源数

2

许可证

unknown

最后核验

2026-05-01

来源状态

来源可访问

安装方式

通过对话安装

复制提示词发给支持本地命令或 Skills 的 AI 助手,先确认命令和权限,再让它执行。

请帮我安装这个 Agent Skill:aif-fix(aif 修复)
来源仓库:https://github.com/lee-to/ai-factory
仓库路径:skills/aif-fix
安装命令:
npx skills add https://github.com/lee-to/ai-factory --skill aif-fix
安装前请先检查当前环境是否支持对应 CLI,并向我确认将要执行的命令、安装目录、联网范围和文件读写权限;确认后再执行。

命令行安装

复制命令到本机终端执行。该命令会通过 npx skills 从第三方来源获取 Skill;本站只展示命令,不托管安装包,也不自动执行。

skills.shnpx skills
npx skills add https://github.com/lee-to/ai-factory --skill aif-fix

简介

aif-fix 提供自主修复或计划优先两种 bug 解决工作流。

  • 适合快速定位并修正代码中的逻辑错误或异常行为。
  • 支持 handoff 机制,可在不同代理间传递修复上下文。
  • 修复前会检查 skip-review 标记,决定是否跳过人工审核环节。
  • aif-fix 属于研究检索类 Skill,可作为该场景下的辅助能力补充。

SKILL.md

Fix - Bug Fix Workflow

Fix a specific bug or problem in the codebase. Supports two modes: immediate fix or plan-first approach.

Workflow

Step 0 (pre): Detect Handoff Mode

Determine Handoff mode, task ID, and skip-review flag. If the caller passed HANDOFF_MODE, HANDOFF_TASK_ID, and HANDOFF_SKIP_REVIEW as explicit text in the prompt, use those values. Otherwise, use the Bash tool:

Bash: printenv HANDOFF_MODE || true
Bash: printenv HANDOFF_TASK_ID || true
Bash: printenv HANDOFF_SKIP_REVIEW || true

Then check HANDOFF_MODE:

When HANDOFF_MODE is 1 (autonomous Handoff agent)

The Handoff coordinator already manages status transitions and DB writes directly. Do NOT call MCP tools. Instead:

  • No interactive questions: Do not use AskUserQuestion. If $ARGUMENTS contains --plan-first, use "Plan first" mode. Otherwise default to "Fix now" mode. Always include tests and logging.
  • Plan annotation (MANDATORY): If HANDOFF_TASK_ID is non-empty, you MUST insert <!-- handoff:task:<HANDOFF_TASK_ID> --> as the very first line of the fix plan file, before the title. Omitting this annotation when HANDOFF_TASK_ID is set is a bug — verify before completing. This applies to both Step 1.1 (creating new plan) and any plan rewrite.

When HANDOFF_MODE is NOT 1 (manual Claude Code session)

Handoff sync is handled inline — see Step 0.1 (after reading the fix plan file) for the task ID extraction and MCP sync trigger. The sync points are:

  • Plan first (Step 1.1): "planning""plan_ready" (after save)
  • Fix now (Step 2→5): "implementing" (Step 2 entry) → "done" if HANDOFF_SKIP_REVIEW=1, else "review" (Step 5)
  • Execute existing plan (Step 0.1→5): "implementing" (Step 0.1) → "done" if HANDOFF_SKIP_REVIEW=1, else "review" (Step 5)

CRITICAL: Always pass paused: true with every handoff_sync_status call except done.

When creating a new FIX_PLAN.md: if there is no existing annotation and no Handoff context, do not add the annotation.

Step 0: Load Config and Resolve Paths

FIRST: Read .ai-factory/config.yaml if it exists to resolve:

  • Paths: paths.description, paths.architecture, paths.rules_file, paths.rules, paths.fix_plan, and paths.patches
  • Language: language.ui for prompts
  • Rules: rules.base plus any named rules.<area> entries

If config.yaml doesn't exist, use defaults:

  • DESCRIPTION.md: .ai-factory/DESCRIPTION.md
  • ARCHITECTURE.md: .ai-factory/ARCHITECTURE.md
  • RULES.md: .ai-factory/RULES.md
  • rules/: .ai-factory/rules/
  • FIX_PLAN.md: .ai-factory/FIX_PLAN.md
  • patches/: .ai-factory/patches/
  • Language: en (English)

Step 0.1: Check for Existing Fix Plan

BEFORE anything else after config resolution, check the resolved fix plan path (default: .ai-factory/FIX_PLAN.md).

If the file EXISTS:

  • Read the resolved fix plan file
  • Immediately check the first line for <!-- handoff:task:<uuid> -->:

- If found AND HANDOFF_MODE is NOT 1 (manual session): extract the task ID. Call handoff_sync_status with {taskId: <extracted-id>, newStatus: "implementing", sourceTimestamp: "<current UTC time in ISO 8601 format>", direction: "aif_to_handoff", paused: true}. (Status is "implementing" because we are executing an existing plan, not creating one.) - If found AND HANDOFF_MODE is 1: the Handoff coordinator handles sync — do nothing. - If NOT found: no linked Handoff task — skip all MCP sync for the rest of this session.

  • Inform the user: "Found existing fix plan. Executing fix based on the plan."
  • Skip Step 1 (problem intake/mode choice), but still run Step 0.2 to load context
  • Then continue to Step 2: Investigate the Codebase, using the plan as your guide
  • Follow each step of the plan sequentially
  • After the fix is fully applied and verified, delete the resolved fix plan file: rm <resolved fix plan path>
  • Continue to Step 4 (Verify), Step 5 (Test suggestion), Step 6 (Patch)

If the file DOES NOT exist AND $ARGUMENTS is empty:

  • Tell the user: "No fix plan found and no problem description provided. Please either provide a bug description (/aif-fix <description>) or create a fix plan first."
  • STOP.

If the file DOES NOT exist AND $ARGUMENTS is provided:

  • Continue to Step 0.2 below.

Step 0.2: Load Project Context & Past Experience

THEN: Read .ai-factory/DESCRIPTION.md (use path from config) if it exists to understand:

  • Tech stack (language, framework, database)
  • Project architecture
  • Coding conventions

Also read .ai-factory/ARCHITECTURE.md (use path from config), the resolved RULES.md path, and the configured rules hierarchy when present to avoid fixes that violate project structure or local conventions.

Read .ai-factory/skill-context/aif-fix/SKILL.md — MANDATORY if the file exists.

This file contains project-specific rules accumulated by /aif-evolve from patches, codebase conventions, and tech-stack analysis. These rules are tailored to the current project.

How to apply skill-context rules:

  • Treat them as project-level overrides for this skill's general instructions
  • When a skill-context rule conflicts with a general rule written in this SKILL.md, the skill-context rule wins (more specific context takes priority — same principle as nested CLAUDE.md files)
  • When there is no conflict, apply both: general rules from SKILL.md + project rules from skill-context
  • Do NOT ignore skill-context rules even if they seem to contradict this skill's defaults — they exist because the project's experience proved the default insufficient
  • CRITICAL: skill-context rules apply to ALL outputs of this skill — including the FIX_PLAN.md template and patch files. The FIX_PLAN.md template in Step 1.1 is a base structure. If a skill-context rule says "steps MUST include X" or "plan MUST have section Y" — you MUST augment the template accordingly. Generating a FIX_PLAN.md or patch that violates skill-context rules is a bug.

Enforcement: After generating any output artifact, verify it against all skill-context rules. If any rule is violated — fix the output before presenting it to the user.

Patch fallback (limited, only when skill-context is missing):

  • If .ai-factory/skill-context/aif-fix/SKILL.md does not exist and the resolved patches dir exists:

- Use Glob to find *.md files in <resolved patches dir> - Sort patch filenames ascending (lexical), then select the last 10 (or fewer if less exist) - Read those selected patch files only - Prioritize recurring Root Cause and Prevention patterns

  • If skill-context exists, do not read all patches by default.

- Optionally inspect a small, targeted subset of recent patches when tags/files clearly match the current bug.

Step 1: Understand the Problem & Choose Mode

From $ARGUMENTS, identify:

  • Error message or unexpected behavior
  • Where it occurs (file, function, endpoint)
  • Steps to reproduce (if provided)

If unclear, ask:

To fix this effectively, I need more context:

1. What is the expected behavior?
2. What actually happens?
3. Can you share the error message/stack trace?
4. When did this start happening?

After understanding the problem, ask the user to choose a mode using AskUserQuestion:

Question: "How would you like to proceed with the fix?"

Options:

  1. Fix now — Investigate and apply the fix immediately
  2. Plan first — Create a fix plan for review, then fix later

Based on choice:

  • "Plan first" → Proceed to Step 1.1: Create Fix Plan
  • "Fix now" → Skip Step 1.1, proceed directly to Step 2: Investigate the Codebase

Step 1.1: Create Fix Plan

Handoff sync (manual mode only): If a Handoff task ID is known (from HANDOFF_TASK_ID or an existing annotation) AND HANDOFF_MODE is NOT 1, call handoff_sync_status with {taskId: <id>, newStatus: "planning", sourceTimestamp: "<current UTC time in ISO 8601 format>", direction: "aif_to_handoff", paused: true}.

Investigate the codebase enough to understand the problem and create a plan.

Use the same parallel exploration approach as Step 2 — launch Explore agents to investigate the problem area, related code, and past patterns simultaneously.

After agents return, synthesize findings to:

  1. Identify the root cause (or most likely candidates)
  2. Map affected files and functions
  3. Assess impact scope

Then create the resolved fix plan file (default: .ai-factory/FIX_PLAN.md).

Before writing: If HANDOFF_MODE is 1 and HANDOFF_TASK_ID is non-empty, the very first line of the file MUST be <!-- handoff:task:<HANDOFF_TASK_ID> --> followed by a blank line, then the plan content below. If in manual mode and a task ID was extracted from an existing annotation, preserve it.

Structure:

# Fix Plan: [Brief title]

**Problem:** [What's broken — from user's description]
**Created:** YYYY-MM-DD HH:mm

## Analysis

What was found during investigation:

- Root cause (or suspected root cause)
- Affected files and functions
- Impact scope

## Fix Steps

Step-by-step plan for implementing the fix:

1. [ ] Step one — what to change and why
2. [ ] Step two — ...
3. [ ] Step three — ...

## Files to Modify

- `path/to/file.ts` — what changes are needed
- `path/to/another.ts` — what changes are needed

## Risks & Considerations

- Potential side effects
- Things to verify after the fix
- Edge cases to watch for

## Test Coverage

- What tests should be added
- What edge cases to cover

After creating the plan, output:

## Fix Plan Created ✅

Plan saved to the resolved fix plan path.

Review the plan and when you're ready to execute, run:

/aif-fix

Handoff sync (manual mode only): If a Handoff task ID is known AND HANDOFF_MODE is NOT 1, call handoff_push_plan with {taskId: <id>, planContent: <full fix plan text>}, then handoff_sync_status with {taskId: <id>, newStatus: "plan_ready", sourceTimestamp: "<current UTC time in ISO 8601 format>", direction: "aif_to_handoff", paused: true}.

STOP here. Do NOT apply the fix.

Step 2: Investigate the Codebase

Handoff sync (manual mode, "Fix now" path only): If a Handoff task ID is known AND HANDOFF_MODE is NOT 1, call handoff_sync_status with {taskId: <id>, newStatus: "implementing", sourceTimestamp: "<current UTC time in ISO 8601 format>", direction: "aif_to_handoff", paused: true}.

Use Task tool with subagent_type: Explore to investigate the problem in parallel. This keeps the main context clean and allows simultaneous investigation of multiple angles.

Launch 2-3 Explore agents simultaneously:

Agent 1 — Locate the problem area:
Task(subagent_type: Explore, model: sonnet, prompt:
  "Find code related to [error location / affected functionality].
   Read the relevant functions, trace the data flow.
   Thoroughness: medium.")

Agent 2 — Related code & side effects:
Task(subagent_type: Explore, model: sonnet, prompt:
  "Find all callers/consumers of [affected function/module].
   Identify what else might break or be affected.
   Thoroughness: medium.")

Agent 3 — Similar past patterns (if patches exist):
Task(subagent_type: Explore, model: sonnet, prompt:
  "Search for similar error patterns or related fixes in the codebase.
   Check git log for recent changes to [affected files].
   Thoroughness: quick.")

After agents return, synthesize findings to identify:

  • The root cause (not just symptoms)
  • Related code that might be affected
  • Existing error handling

Fallback: If Task tool is unavailable, investigate directly:

  • Find relevant files using Glob/Grep
  • Read the code around the issue
  • Trace the data flow
  • Check for similar patterns elsewhere

Step 3: Implement the Fix

Apply the fix with logging:

// ✅ REQUIRED: Add logging around the fix
console.log("[FIX] Processing user input", { userId, input });

try {
  // The actual fix
  const result = fixedLogic(input);
  console.log("[FIX] Success", { userId, result });
  return result;
} catch (error) {
  console.error("[FIX] Error in fixedLogic", {
    userId,
    input,
    error: error.message,
    stack: error.stack,
  });
  throw error;
}

Logging is MANDATORY because:

  • User needs to verify the fix works
  • If it doesn't work, logs help debug further
  • Feedback loop: user provides logs → we iterate

Step 4: Verify the Fix

  • Check the code compiles/runs
  • Verify the logic is correct
  • Ensure no regressions introduced

Step 5: Suggest Test Coverage

Handoff sync (manual mode ONLY — skip entirely when HANDOFF_MODE is 1): If a Handoff task ID is known AND HANDOFF_MODE is NOT 1:

  1. Call handoff_push_plan with {taskId: <id>, planContent: <fix summary or updated plan>}.
  2. If HANDOFF_SKIP_REVIEW is 1: call handoff_sync_status with {taskId: <id>, newStatus: "done", sourceTimestamp: "<current UTC time in ISO 8601 format>", direction: "aif_to_handoff", paused: false}.
  3. Otherwise: call handoff_sync_status with {taskId: <id>, newStatus: "review", sourceTimestamp: "<current UTC time in ISO 8601 format>", direction: "aif_to_handoff", paused: true}.

ALWAYS suggest covering this case with a test:

## Fix Applied ✅

The issue was: [brief explanation]
Fixed by: [what was changed]

### Logging Added
The fix includes logging with prefix `[FIX]`.
Please test and share any logs if issues persist.

### Recommended: Add a Test

This bug should be covered by a test to prevent regression:

\`\`\`typescript
describe('functionName', () => {
  it('should handle [the edge case that caused the bug]', () => {
    // Arrange
    const input = /* the problematic input */;

    // Act
    const result = functionName(input);

    // Assert
    expect(result).toBe(/* expected */);
  });
});
\`\`\`

AskUserQuestion: Would you like me to create this test?

Options:
1. Yes, create the test
2. No, skip for now

Handling the user's response:

  • If "Yes, create the test":

1. Create the test file in the appropriate test directory (follow project conventions) 2. Include the suggested test case and any additional edge cases related to the fix 3. Run the test to verify it passes 4. Then proceed to Step 6: Create Self-Improvement Patch

  • If "No, skip for now":

- Proceed directly to Step 6: Create Self-Improvement Patch

Logging Requirements

All fixes MUST include logging:

  1. Log prefix: Use [FIX] or [FIX:<issue-id>] for easy filtering
  2. Log inputs: What data was being processed
  3. Log success: Confirm the fix worked
  4. Log errors: Full context if something fails
  5. Configurable: Use LOG_LEVEL if available
// Pattern for fixes
const LOG_FIX = process.env.LOG_LEVEL === "debug" || process.env.DEBUG_FIX;

function fixedFunction(input) {
  if (LOG_FIX) console.log("[FIX] Input:", input);

  // ... fix logic ...

  if (LOG_FIX) console.log("[FIX] Output:", result);
  return result;
}

Examples

Example 1: Null Reference Error

User: /aif-fix TypeError: Cannot read property 'name' of undefined in UserProfile

Actions:

  1. Search for UserProfile component/function
  2. Find where .name is accessed
  3. Add null check with logging
  4. Suggest test for null user case

Example 2: API Returns Wrong Data

User: /aif-fix /api/orders returns empty array for authenticated users

Actions:

  1. Find orders API endpoint
  2. Trace the query logic
  3. Find the bug (e.g., wrong filter)
  4. Fix with logging
  5. Suggest integration test

Example 3: Form Validation Not Working

User: /aif-fix email validation accepts invalid emails

Actions:

  1. Find email validation logic
  2. Check regex or validation library usage
  3. Fix the validation
  4. Add logging for validation failures
  5. Suggest unit test with edge cases

Important Rules

  1. Check the fix plan first - Always check the resolved fix plan path before anything else
  2. Plan mode = plan only - When user chooses "Plan first", create the plan and STOP. Do NOT fix.
  3. Execute mode = follow the plan - When the resolved fix plan exists, follow it step by step, then delete it
  4. NO reports - Don't create summary documents (patches are learning artifacts, not reports)
  5. ALWAYS log - Every fix must have logging for feedback
  6. ALWAYS suggest tests - Help prevent regressions
  7. Root cause - Fix the actual problem, not symptoms
  8. Minimal changes - Don't refactor unrelated code
  9. One fix at a time - Don't scope creep
  10. Clean up - Delete the resolved fix plan file after successful fix execution
  11. Ownership boundary - /aif-fix owns paths.fix_plan and paths.patches; treat .ai-factory/DESCRIPTION.md, roadmap, rules, and architecture context artifacts as read-only unless the user explicitly requests otherwise
  12. Logging scope - Keep [FIX] logging requirements for fixes; context-gate outputs in this command should use WARN/ERROR and must not change global logging policy in other skills

After Fixing

Use this output template in Step 5 (before the AskUserQuestion about tests):

## Fix Applied ✅

**Issue:** [what was broken]
**Cause:** [why it was broken]
**Fix:** [what was changed]

**Files modified:**
- path/to/file.ts (line X)

**Logging added:** Yes, prefix `[FIX]`

Step 6: Create Self-Improvement Patch

ALWAYS create a patch after every fix. This builds a knowledge base for future fixes.

Create the patch:

  1. Create directory if it doesn't exist: mkdir -p <resolved patches dir>
  2. Create a patch file with the current timestamp as filename. Format: YYYY-MM-DD-HH.mm.md (e.g., 2026-02-07-14.30.md)
  3. Use this template:
# [Brief title describing the fix]

**Date:** YYYY-MM-DD HH:mm
**Files:** list of modified files
**Severity:** low | medium | high | critical

## Problem

What was broken. How it manifested (error message, wrong behavior).
Be specific — include the actual error or symptom.

## Root Cause

WHY the problem occurred. This is the most valuable part.
Not "what was wrong" but "why it was wrong":

- Logic error? Why was the logic incorrect?
- Missing check? Why was it missing?
- Wrong assumption? What was assumed?
- Race condition? What sequence caused it?

## Solution

How the fix was implemented. Key code changes and reasoning.
Include the approach, not just "changed line X".

## Prevention

How to prevent this class of problems in the future:

- What pattern/practice should be followed?
- What should be checked during code review?
- What test would catch this?

## Tags

Space-separated tags for categorization, e.g.:
`#null-check` `#async` `#validation` `#typescript` `#api` `#database`

Example patch:

# Null reference in UserProfile when user has no avatar

**Date:** 2026-02-07 14:30
**Files:** src/components/UserProfile.tsx
**Severity:** medium

## Problem

TypeError: Cannot read property 'url' of undefined when rendering
UserProfile for users without an uploaded avatar.

## Root Cause

The `user.avatar` field is optional in the database schema but the
component accessed `user.avatar.url` without a null check. This was
introduced in commit abc123 when avatar display was added — the
developer tested only with users that had avatars.

## Solution

Added optional chaining: `user.avatar?.url` with a fallback to a
default avatar URL. Also added a null check in the Avatar sub-component.

## Prevention

- Always check if database fields marked as `nullable` / `optional`
  are handled with null checks in the UI layer
- Add test cases for "empty state" — user with minimal data
- Consider a lint rule for accessing nested optional properties

## Tags

`#null-check` `#react` `#optional-field` `#typescript`

This is NOT optional. Every fix generates a patch. The patch is your learning.

Context Cleanup

Suggest the user to free up context space if needed: /clear (full reset) or /compact (compress history).


DO NOT:

  • ❌ Apply a fix when user chose "Plan first" - only create the fix plan and stop
  • ❌ Skip the fix-plan check at the start
  • ❌ Leave the fix plan after successful fix execution - always delete it
  • ❌ Generate reports or summaries (patches are NOT reports — they are learning artifacts)
  • ❌ Refactor unrelated code
  • ❌ Add features while fixing
  • ❌ Skip logging
  • ❌ Skip test suggestion
  • ❌ Skip patch creation

适合场景

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02

需要根据任务场景推荐可安装能力包时

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需要对比不同来源的安装命令和来源信息时

能力概览

能力 1

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能力 2

展示可复制的安装命令

能力 3

保留来源站点、仓库和原始说明,方便继续核验

能力 4

展示第三方安全扫描或审计结果

安装后应在对应宿主中按原始 README 的触发条件使用;具体调用方式请以来源页面和 README 为准。

平台分布

Codex

34.29%
按下载量换算75

Claude

29.79%
按下载量换算66

Cursor

19.53%
按下载量换算43

Gemini CLI

9.84%
按下载量换算22

安全审计

Gen Agent Trust Hub

通过

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通过

Snyk

通过

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