AI Prompts Library

Review this MCP server design before it ships. You are looking for the failure modes that only appear once an agent is driving it, not a human.

Check each of these and report concretely:

1. TOOL NAMING: are names unambiguous to a model that only sees the name and description? Flag any pair a model could confuse.
2. DESCRIPTIONS: does each description say when NOT to use the tool? Missing negative guidance is the top cause of wrong tool selection.
3. PARAMETER SCHEMAS: are required and optional correct? Any parameter a model will have to guess at?
4. ERROR MESSAGES: does a failure tell the model what to do differently, or just that something broke?
5. RESPONSE SIZE: which tool can return an unbounded payload and blow out the context window? Every one of them needs a limit.
6. DESTRUCTIVE OPERATIONS: which calls are irreversible, and is that obvious from the description alone?
7. IDEMPOTENCY: what happens if the agent retries after a timeout that actually succeeded?

For each finding: severity, the concrete failure scenario, and the fix.

Server definition:
[PASTE TOOL DEFINITIONS]

Review this AI feature spec before engineering starts. Most AI features fail on the same handful of unanswered questions.

Check each and report GAP or OK with a one-line justification:

1. What happens when the model is wrong? Is there a recovery path, or does the user just get a bad answer?
2. What does the user see while waiting?
3. How is quality measured after launch? Name the metric.
4. What is the cost per user per month at the projected volume?
5. What untrusted content enters the prompt, and what stops it from carrying instructions?
6. Which decisions does the model make that a human should approve?
7. What is the fallback if the provider has an outage?
8. Is any user data sent to the provider, and does the privacy policy cover it?
9. What is the rollback plan if quality regresses after a provider model update?

Then name the single largest risk and what would de-risk it cheapest.

Spec:
[PASTE]

You are an expert code reviewer with deep knowledge of security, performance, and best practices across multiple programming languages.

Your task is to review the following code and provide:
1. **Security Analysis**: Identify any security vulnerabilities (SQL injection, XSS, CSRF, authentication issues, etc.)
2. **Performance Review**: Highlight performance bottlenecks and suggest optimizations
3. **Code Quality**: Assess readability, maintainability, and adherence to best practices
4. **Bug Detection**: Point out logical errors, edge cases, and potential runtime issues
5. **Recommendations**: Provide specific, actionable improvements with code examples

For each issue found, specify:
- Severity (Critical, High, Medium, Low)
- Location (file, line number if available)
- Detailed explanation of the problem
- Concrete solution with improved code

Code to review:
[PASTE YOUR CODE HERE]