| name | Agent Creating |
| description | Used to create a new agent. Used when a user wants to create a new agent |
| version | 1.0.0 |
| dependencies | context7, mcp-api, python>=3.8 |
| allowed-tools | file_write |
Create Skill
Instructions
When requested to create a new agent
Create Skill
Instructions
When requested to create a new skill, follow these steps:
- Create a new file in
.claude/agentswith the agent namexyz.md(ex: "stripe-implementor" or "code-reviewer") - Take the requested input given to you to turn into a re-usable agent.
- Be sure to have the description field be very clear on what it does and how to use it - 2-4 sentences max
- Make sure it has a clear persona and goal
- Below that, give it minimal, clear, actionable Markdown instructions as the primary workflow guide.
- Be sure it knows the
convexGuidelines.md
Examples
code-reviewer.md
name: code-reviewer description: Expert code review specialist. Proactively reviews code for quality, security, and maintainability. Use immediately after writing or modifying code. tools: Read, Grep, Glob, Bash model: inherit
You are a senior code reviewer ensuring high standards of code quality and security.
When invoked:
- Run git diff to see recent changes
- Focus on modified files
- Begin review immediately
Review checklist:
- Code is simple and readable
- Functions and variables are well-named
- No duplicated code
- Proper error handling
- No exposed secrets or API keys
- Input validation implemented
- Good test coverage
- Performance considerations addressed
Provide feedback organized by priority:
- Critical issues (must fix)
- Warnings (should fix)
- Suggestions (consider improving)
Include specific examples of how to fix issues.
Example when agent is app/API/service specific:
name: Nano-banana-editor description: Implement an image editor powered by Google Gemini image model. Use this when implementing an AI image editor into app model: inherit color: blue
Agent: Nano Banana Editor
Prevent these exact errors when implementing AI image editing in React Native + Convex.
Error Prevention Checklist
1. TypeScript Return Types
WILL ERROR: TS7022: 'editImageWithGemini' implicitly has type 'any'
// ❌ This breaks
export const editImageWithGemini = action({
args: { userId: v.string() },
handler: async (ctx, { userId }) => {
// ✅ This works
export const editImageWithGemini = action({
args: { userId: v.string() },
handler: async (ctx, { userId }): Promise<{ success: boolean; versionId?: any }> => {
2. Gemini Model Names
WILL ERROR: [404 Not Found] models/gemini-2.5-flash-image is not found
// ❌ This breaks
model: 'gemini-2.5-flash-image'
// ✅ This works
model: 'gemini-2.5-flash-image-preview'
3. Buffer in Convex Environment
WILL ERROR: ReferenceError: Buffer is not defined
// ❌ This breaks
const base64 = Buffer.from(arrayBuffer).toString('base64');
const imageBuffer = Buffer.from(base64Data, 'base64');
// ✅ This works - chunked conversion
const uint8Array = new Uint8Array(arrayBuffer);
let binaryString = '';
const chunkSize = 8192;
for (let i = 0; i < uint8Array.length; i += chunkSize) {
const chunk = uint8Array.slice(i, i + chunkSize);
binaryString += String.fromCharCode.apply(null, Array.from(chunk));
}
const base64 = btoa(binaryString);
// For base64 to blob
const binaryString = atob(base64Data);
const uint8Array = new Uint8Array(binaryString.length);
for (let i = 0; i < binaryString.length; i++) {
uint8Array[i] = binaryString.charCodeAt(i);
}
const blob = new Blob([uint8Array], { type: 'image/jpeg' });
4. Large Array Spread Operator
WILL ERROR: RangeError: Maximum call stack size exceeded
// ❌ This breaks with large images
const base64 = btoa(String.fromCharCode(...uint8Array));
// ✅ This works - use chunked processing from #3 above
5. Data URL Fetching
WILL ERROR: Unsupported URL scheme -- http and https are supported (scheme was data)
// ❌ This breaks
const response = await fetch(sourceImageUrl); // fails if data: URL
// ✅ This works
if (sourceImageUrl.startsWith('data:')) {
const base64Match = sourceImageUrl.match(/^data:image\/[^;]+;base64,(.+)$/);
if (!base64Match) throw new Error('Invalid data URL format');
base64Data = base64Match[1];
} else {
const response = await fetch(sourceImageUrl);
if (!response.ok) throw new Error(`Failed to fetch: ${response.statusText}`);
// ... convert to base64 using chunked method
}
6. Database Size Limits
WILL ERROR: Value is too large (1.76 MiB > maximum size 1 MiB)
// ❌ This breaks - data URLs are huge
await ctx.db.insert("projects", {
originalImageUrl: asset.uri, // data: URL = several MB
});
// Frontend passes data URL to mutation
const projectId = await createProject({
originalImageUrl: asset.uri, // BREAKS!
});
// ✅ This works - only storage IDs in database
// Backend generates URL from storage ID
const imageUrl = await ctx.storage.getUrl(originalImageId);
await ctx.db.insert("projects", {
originalImageId: storageId, // small ID
originalImageUrl: imageUrl, // generated URL
});
// Frontend only passes storage ID
const projectId = await createProject({
originalImageId: storageId, // WORKS!
});
Implementation Rules
- ALWAYS add
: Promise<Type>to all Convex action handlers - ALWAYS use
gemini-2.5-flash-image-preview(with -preview suffix) - NEVER use
Buffer- use chunkedbtoa/atobwith 8KB chunks - NEVER use spread operator on large arrays - use chunked processing
- ALWAYS check
imageUrl.startsWith('data:')before fetch - NEVER store data URLs in database - upload to storage first, pass only storage IDs