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Agent Skill · 研究检索

aif-fix(aif 修复)

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。

aif-fix 是研究检索类 Agent Skill,可用宿主为 Codex、Claude、Cursor、Gemini CLI,通过GitHub 仓库获取,权限为调用外部服务;许可证信息还不明确,第三方扫描已通过,按安装量在研究检索类的 73,675 个 Skill 里排第 48,496。

总安装 685周安装 28GitHub Stars 535下载 220核验 2026-05-01

安装说明

本站只整理中文说明,不托管安装包,也不代用户安装。
GitHub
许可证
unknown

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

这个 Skill 是做什么的

研究检索类 Skill 主要解决「找资料、核对事实、把来源整理清楚」的问题,通常会让助手先检索再总结。

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。

来源仓库内路径:skills/aif-fix

上手步骤

4 步
  1. 1

    确认自己的宿主工具

    公开资料标注支持 Codex、Claude、Cursor、Gemini CLI;先确认自己用的是其中之一,再按对应工具的 Skills 目录放置。

  2. 2

    拿到安装命令

    可以直接复制的命令是 npx skills add https://github.com/lee-to/ai-factory --skill aif-fix;命令里的占位符换成自己的路径或密钥再执行。

  3. 3

    安装后重启宿主

    命令执行完要完全退出宿主工具再打开,让新装的 Skill 被重新扫描到,否则列表里可能看不到。

  4. 4

    按最小权限试用

    它需要调用外部服务,先在测试目录或测试账号里跑,确认没问题再放到正式项目。

常见问题

6 条

aif-fix 怎么安装?

在终端执行 npx skills add https://github.com/lee-to/ai-factory --skill aif-fix。装完完全退出宿主工具再打开,让它重新扫描本地 Skill。

aif-fix 支持哪些 AI 工具?

公开资料标注支持 Codex、Claude、Cursor、Gemini CLI。其他工具只要能读取本地 Skill 目录,一般也能手动放进去,但要自己确认触发方式是否一致。

aif-fix 需要什么权限?

权限级别是调用外部服务。该 Skill 可能调用第三方服务、云服务或外部模型 API,使用前需要确认账号、额度、数据发送范围和服务条款。

aif-fix 是免费的吗?

公开资料没有标注明确许可证,收费和商用限制都无法确认。正式使用前请到来源仓库核对授权说明。

aif-fix 用的人多吗?

公开数据是累计安装 685 次,近一周安装 28 次,下载 220 次,GitHub 535 星。这些数字来自第三方目录统计,只能当作热度参考,不代表质量或安全性。

aif-fix 安全吗?

第三方扫描结果为通过,但这只覆盖已知的静态检查项,不能替代自己读一遍源码和安装命令。

值得选的地方和要先想清楚的地方

值得选的地方

  • 同时适配 4 种工具,换客户端不用重新找替代品。
  • 第三方扫描已通过,常见的高风险行为没有命中。

先想清楚的地方

  • 许可证没有明确标注,能不能商用、能不能再分发都不确定。
  • 第三方目录整理,版本更新和行为细节以来源仓库为准。

适不适合你

更适合

  • 已经在用 Codex,想直接扩展它能力的人。
  • 需要处理研究检索类任务、又不想每次都手写提示词的人。

不太适合

  • 需要明确授权才能用到公司项目里的场景。
  • 需要厂商级技术支持和 SLA 的生产系统。

研究检索类 Skill 对比

6 个同类
Skill总安装GitHub 星权限许可证扫描
find-skills

寻找技能 · Codex、Claude

31,199,81316,486操作浏览器MIT有提醒
self-improving-agent

自我改进 Agent · OpenClaw

16,464,0023,396接触敏感数据MIT-0通过
soultrace

灵魂追踪 · Codex、Claude

7,588,94412需要联网未明确有提醒
self-improving

自我完善 · OpenClaw

6,829,2841,046需要联网MIT-0通过
microsoft-foundry

微软代工厂 · Codex、Claude

6,614,144764调用外部服务未明确有提醒
aif-fix

aif 修复 · 本页

685535调用外部服务未明确通过

按安装量取同分类前几名;数字来自第三方目录统计,只作热度参考,不代表质量结论。

SKILL.md 原文

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

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Codex

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Gemini CLI

9.84%
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安全审计

Gen Agent Trust Hub

通过

Socket

通过

Snyk

通过

权限和风险

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安装前确认

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