Install
$ agentstack add skill-matthewbspeicher-remembr-dev-code-review-checklist ✓ scanned · ✓ verified, works with Claude Code, Cursor, and more.
Security review
✓ PassedNo issues found. Passed automated security review. · v0.1.0 How review works →
- ✓ Prompt-injection patterns
- ✓ Secret / credential exfiltration
- ✓ Dangerous shell & filesystem operations
- ✓ Untrusted network calls
- ✓ Known-malicious package signatures
Verified badge
Passed review? Show it. Paste this badge into your README, it links to the public security report.
Reliability & compatibility
Declared compatibility
Compatibility is declared by the source manifest. End-to-end runtime verification is coming, see below.
We're building live execution health for every listing: tool-call success rate, median latency, uptime, and last-checked timestamps, measured, not self-reported. It isn't live yet, so we don't show numbers we can't stand behind.
How agent discovery & health will work →About
Code Review Checklist
Quick Review Checklist
Correctness
- [ ] Code does what it's supposed to do
- [ ] Edge cases handled
- [ ] Error handling in place
- [ ] No obvious bugs
Security
- [ ] Input validated and sanitized
- [ ] No SQL/NoSQL injection vulnerabilities
- [ ] No XSS or CSRF vulnerabilities
- [ ] No hardcoded secrets or sensitive credentials
- [ ] AI-Specific: Protection against Prompt Injection (if applicable)
- [ ] AI-Specific: Outputs are sanitized before being used in critical sinks
Performance
- [ ] No N+1 queries
- [ ] No unnecessary loops
- [ ] Appropriate caching
- [ ] Bundle size impact considered
Code Quality
- [ ] Clear naming
- [ ] DRY - no duplicate code
- [ ] SOLID principles followed
- [ ] Appropriate abstraction level
Testing
- [ ] Unit tests for new code
- [ ] Edge cases tested
- [ ] Tests readable and maintainable
Documentation
- [ ] Complex logic commented
- [ ] Public APIs documented
- [ ] README updated if needed
AI & LLM Review Patterns (2025)
Logic & Hallucinations
- [ ] Chain of Thought: Does the logic follow a verifiable path?
- [ ] Edge Cases: Did the AI account for empty states, timeouts, and partial failures?
- [ ] External State: Is the code making safe assumptions about file systems or networks?
Prompt Engineering Review
// ❌ Vague prompt in code
const response = await ai.generate(userInput);
// ✅ Structured & Safe prompt
const response = await ai.generate({
system: "You are a specialized parser...",
input: sanitize(userInput),
schema: ResponseSchema
});
Anti-Patterns to Flag
// ❌ Magic numbers
if (status === 3) { ... }
// ✅ Named constants
if (status === Status.ACTIVE) { ... }
// ❌ Deep nesting
if (a) { if (b) { if (c) { ... } } }
// ✅ Early returns
if (!a) return;
if (!b) return;
if (!c) return;
// do work
// ❌ Long functions (100+ lines)
// ✅ Small, focused functions
// ❌ any type
const data: any = ...
// ✅ Proper types
const data: UserData = ...
Review Comments Guide
// Blocking issues use 🔴
🔴 BLOCKING: SQL injection vulnerability here
// Important suggestions use 🟡
🟡 SUGGESTION: Consider using useMemo for performance
// Minor nits use 🟢
🟢 NIT: Prefer const over let for immutable variable
// Questions use ❓
❓ QUESTION: What happens if user is null here?
Source & license
This open-source skill is cataloged on AgentStack and links to its original source — we do not rehost the code.
- Author: matthewbspeicher
- Source: matthewbspeicher/remembr-dev
- License: MIT
Install and usage instructions live in the source repository linked above.
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Versions
- v0.1.0 Imported from the upstream source.