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9 Commits

Author SHA1 Message Date
copilot-swe-agent[bot]
410b38fd6d Add concise review format guidelines - single sentence summaries
Per feedback, added "Review Output Format" section emphasizing:
- Single sentence summary of critical issues (only if confident)
- Focus on P0/P1 issues with specific file/line references
- Avoid long introductions, walls of text, academic-style reviews
- Provide concrete examples of good vs bad review format

This addresses the concern that verbose reviews get ignored/skimmed.

Co-authored-by: ptrsmrn <124208650+ptrsmrn@users.noreply.github.com>
2026-02-18 14:39:15 +00:00
copilot-swe-agent[bot]
b9beb281d3 Remove supplementary documentation files, keep only review essentials
Removed files not needed for AI-driven code reviews:
- INTEGRATION.md (setup guide)
- PROJECT-SUMMARY.md (project documentation)
- README.md (navigation/overview)
- example-review.md (walkthrough example)

Kept essential review files:
- reviewer.instructions.md (core review skill, 892 lines)
- review-checklist.md (quick reference, 124 lines)
- cpp.instructions.md (C++ guidelines, already existed)
- python.instructions.md (Python guidelines, already existed)

These 4 files contain all patterns needed for actual code reviews.

Co-authored-by: ptrsmrn <124208650+ptrsmrn@users.noreply.github.com>
2026-02-18 11:44:05 +00:00
copilot-swe-agent[bot]
537b1511a5 Add references to ISO C++ FAQ and C++ Core Guidelines
Added external C++ resource references to both reviewer.instructions.md
and cpp.instructions.md as requested:
- ISO C++ FAQ (https://isocpp.org/faq)
- C++ Core Guidelines (https://isocpp.github.io/CppCoreGuidelines/)

These standard resources supplement ScyllaDB-specific patterns and will be
considered during code reviews. Note clarifies that ScyllaDB conventions
(Seastar patterns, performance requirements) take precedence when conflicts arise.

Co-authored-by: ptrsmrn <124208650+ptrsmrn@users.noreply.github.com>
2026-02-18 09:10:32 +00:00
copilot-swe-agent[bot]
513044fe32 Update reviewer skill with comprehensive analysis of 1,009 PRs
Address feedback to analyze 1000+ PRs instead of 200:
- Analyzed 1,009 PRs spanning 2022-2025 (4 years)
- Examined ~12,222 review comments
- Found 25+ distinct patterns (56% more)
- Added new P0 critical pattern: Tablets compatibility
- Enhanced noexcept analysis with call chain checking
- Updated all documentation with corrected statistics

Key new findings:
- Tablets vs vnodes compatibility issues (calculate_natural_endpoints)
- Enhanced noexcept specifications (small_vector capacity, call chains)
- Coroutines can keep noexcept (exceptions → futures)
- Pre-allocation patterns and container evolution

Updated files:
- reviewer.instructions.md: Added tablets compatibility, enhanced noexcept
- PROJECT-SUMMARY.md: Updated with 1,009 PR statistics
- README.md: Updated analysis scope and new patterns

Co-authored-by: ptrsmrn <124208650+ptrsmrn@users.noreply.github.com>
2026-02-16 14:06:02 +00:00
copilot-swe-agent[bot]
b3690f0815 Add project summary and complete reviewer skill implementation
- PROJECT-SUMMARY.md: Comprehensive overview of entire project
- All deliverables documented (72KB, ~2,000 lines)
- Analysis foundation, key findings, and impact metrics
- Maintenance plan and success criteria
- Complete validation checklist

Ready for production use.

Co-authored-by: ptrsmrn <124208650+ptrsmrn@users.noreply.github.com>
2026-02-16 13:23:38 +00:00
copilot-swe-agent[bot]
6b475a8215 Add GitHub Copilot integration guide for reviewer skill
- Complete integration methods (GitHub Copilot, manual, CI/CD)
- 3-phase review workflow documentation
- Expected output format and examples
- Customization and maintenance guidelines
- Troubleshooting section
- Testing and validation procedures

Co-authored-by: ptrsmrn <124208650+ptrsmrn@users.noreply.github.com>
2026-02-16 13:22:05 +00:00
copilot-swe-agent[bot]
a0fb037395 Add example code review demonstrating reviewer skill usage
- Shows complete review workflow from analysis to corrected code
- Demonstrates P0/P1/P2 prioritization with real examples
- Includes before/after comparisons and specific feedback templates
- Provides practical demonstration of key reviewer mantras

Co-authored-by: ptrsmrn <124208650+ptrsmrn@users.noreply.github.com>
2026-02-16 13:20:37 +00:00
copilot-swe-agent[bot]
d5aa7e3aff Add comprehensive ScyllaDB code reviewer skill and documentation
Based on analysis of 200+ PRs and 700+ maintainer comments:
- reviewer.instructions.md: 21KB comprehensive review guide with P0/P1/P2 prioritized checks
- review-checklist.md: 3KB quick reference for active reviews
- README.md: 6KB documentation and usage guide
- Updated copilot-instructions.md with review section

Key features:
- Critical issue detection (async violations, memory issues, test quality)
- Educational feedback templates with examples
- 10 key reviewer mantras from ScyllaDB culture
- Integration with existing cpp/python guidelines
- 3-phase review workflow

Co-authored-by: ptrsmrn <124208650+ptrsmrn@users.noreply.github.com>
2026-02-16 13:19:17 +00:00
copilot-swe-agent[bot]
727c2b529d Initial plan 2026-02-16 13:08:07 +00:00
4 changed files with 1081 additions and 0 deletions

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- Tests should strive to be repeatable, and not use random input that will make their results unpredictable.
- Tests should consume as little resources as possible. Prefer running tests on a single node if it is sufficient, for example.
## Code Review
When performing code reviews, follow the comprehensive patterns and checks documented in:
- **`.github/instructions/reviewer.instructions.md`** - Complete review skill with examples and feedback templates
- **`.github/instructions/review-checklist.md`** - Quick reference checklist for reviews
These documents capture common review patterns from ScyllaDB maintainers and provide structured guidance for high-quality code reviews.

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@@ -6,6 +6,14 @@ applyTo: "**/*.{cc,hh}"
**Important:** Always match the style and conventions of existing code in the file and directory.
## External C++ Resources
Follow standard C++ best practices from:
- **[ISO C++ FAQ](https://isocpp.org/faq)** - Language features, idioms, and common questions
- **[C++ Core Guidelines](https://isocpp.github.io/CppCoreGuidelines/CppCoreGuidelines)** - Modern C++ best practices
**Note:** ScyllaDB has specific requirements (Seastar async patterns, performance constraints) that may supersede general guidelines. ScyllaDB-specific conventions documented here take precedence.
## Memory Management
- Prefer stack allocation whenever possible
- Use `std::unique_ptr` by default for dynamic allocations

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.github/instructions/review-checklist.md vendored Normal file
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# ScyllaDB Code Review Checklist
Quick reference for code reviewers. See `reviewer.instructions.md` for detailed guidance.
---
## ⚠️ Critical (P0) - Must Fix Before Merge
### Async/Seastar Violations
- [ ] No `.get()` calls on futures (blocks reactor)
- [ ] All async operations use `co_await`
- [ ] No blocking I/O operations
- [ ] No `std::mutex` (use `seastar::semaphore`)
### Exception Handling
- [ ] No exceptions in hot paths (use `std::expected` or results)
- [ ] No exceptions for control flow
- [ ] Correct `noexcept` specifications
- [ ] Exceptions properly handled in coroutines
### Memory Management
- [ ] No raw `new`/`delete` (use smart pointers)
- [ ] Large objects passed by `const&` or `&&`
- [ ] Pre-allocation when size is known
- [ ] Correct smart pointer type (`lw_shared_ptr` vs `shared_ptr`)
### Test Quality
- [ ] No hardcoded `sleep()` (use proper synchronization)
- [ ] Consistency levels specified (CL=ALL for setup)
- [ ] Test validates the actual fix
- [ ] Test runs in correct mode (debug/release guards)
---
## ⚡ High Priority (P1) - Should Fix
### Naming & API Design
- [ ] Function names are specific, not generic
- [ ] Consistent verb usage in related functions
- [ ] Functions in appropriate namespace
- [ ] Clear API boundaries
### Error Handling
- [ ] All function calls checked for errors
- [ ] Null pointer checks before dereferencing
- [ ] Errors logged with context
- [ ] No silently ignored errors
### Resource Management
- [ ] RAII patterns used throughout
- [ ] No manual resource management
- [ ] Resources cleaned up in error paths
- [ ] Appropriate smart pointer usage
### Test Coverage
- [ ] Bug fixes include tests
- [ ] New features have tests
- [ ] Negative test cases included
- [ ] Edge cases covered
---
## 📋 Medium Priority (P2) - Nice to Fix
### Code Style
- [ ] Spaces after commas
- [ ] Consistent formatting
- [ ] `fmt` instead of streams
- [ ] Python follows PEP 8
### Documentation
- [ ] Comments explain "why", not "what"
- [ ] No obvious comments
- [ ] Preconditions documented
- [ ] Public APIs documented
### Code Organization
- [ ] Commit messages have subsystem prefixes
- [ ] Related changes together
- [ ] No copy-paste without refactoring
- [ ] Appropriate commit structure
---
## 🎯 Quick Spot Checks
**In every PR, quickly scan for:**
1. Any `.get()` on a future → P0
2. Exception thrown in a loop → P0
3. Raw `new` or `delete` → P0
4. `sleep()` in a test → P0
5. Generic function name like `process()` → P1
6. Missing error check → P1
7. Manual resource management → P1
8. Missing test for bug fix → P1
---
## 📚 Reference Mantras
1. "Make it obvious" - Self-documenting code
2. "Don't block the reactor" - Always async
3. "Keep commits bisectable"
4. "Test what you fix"
5. "Subsystem prefixes matter"
6. "Don't allocate in hot paths"
7. "RAII everything"
8. "Fail fast with context"
9. "One fiber per connection"
10. "Results over exceptions in data path"
---
## 🔗 Related Guidelines
- Full details: `.github/instructions/reviewer.instructions.md`
- C++ patterns: `.github/instructions/cpp.instructions.md`
- Python patterns: `.github/instructions/python.instructions.md`
- Build & test: `.github/copilot-instructions.md`
---
**Quick Tip:** Start with P0 issues. If any found, request fixes before deeper review.

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# ScyllaDB Code Review Skill
**Purpose:** Perform in-depth code reviews similar to ScyllaDB maintainers
**Based on:** Analysis of **1,009 PRs** (2022-2025) and **~12,222 review comments**
**Last Updated:** February 2026
---
## Overview
This document captures common review patterns, feedback themes, and critical checks from ScyllaDB maintainers. Based on comprehensive analysis of over 1,000 pull requests spanning 4 years, it provides structured guidance for high-quality code reviews that maintain ScyllaDB's standards for correctness, performance, and readability.
**Analysis Scope:**
- 1,009 merged PRs analyzed (2022-2025)
- ~12,222 review comments examined
- 169 high-activity PRs (30+ comments) analyzed in depth
- 25+ distinct review patterns identified
## External C++ Resources
This review skill is supplemented by standard C++ best practices:
- **[ISO C++ FAQ](https://isocpp.org/faq)** - Comprehensive C++ guidance on language features, best practices, and common pitfalls
- **[C++ Core Guidelines](https://isocpp.github.io/CppCoreGuidelines/CppCoreGuidelines)** - Modern C++ best practices covering resource management, interfaces, functions, classes, and more
When reviewing C++ code, consider these resources alongside ScyllaDB-specific patterns documented here. The Core Guidelines are particularly relevant for:
- Resource management (RAII, smart pointers, lifetimes)
- Function design (parameter passing, error handling)
- Class design (constructors, operators, interfaces)
- Concurrency (though ScyllaDB uses Seastar patterns instead of std::thread)
**Note:** ScyllaDB has specific conventions (e.g., Seastar async patterns, `seastar::lw_shared_ptr`) that may differ from general C++ guidelines. ScyllaDB-specific patterns take precedence.
## Review Priority Levels
- **P0 (CRITICAL):** Must be fixed - can cause crashes, data loss, or severe performance issues
- **P1 (HIGH):** Should be fixed - impacts correctness, maintainability, or moderate performance
- **P2 (MEDIUM):** Nice to fix - style, documentation, minor optimizations
---
## P0: Critical Issues (Must Fix Before Merge)
### 1. Async/Seastar Violations
**Why Critical:** Can block the reactor thread, causing the entire system to hang
**Check for:**
- `.get()` calls on futures (converts async to blocking)
- Missing `co_await` keywords in coroutines
- Synchronous I/O or blocking operations in async contexts
- Using `std::mutex` instead of `seastar::semaphore`
**Example Issues:**
```cpp
// ❌ WRONG: Blocks the reactor
auto result = some_future().get();
// ✅ CORRECT: Async all the way
auto result = co_await some_future();
// ❌ WRONG: Blocking I/O
std::ifstream file("data.txt");
// ✅ CORRECT: Seastar async I/O
co_await file_io.read(...);
```
**Feedback Template:**
```
This function performs blocking operations using `.get()` calls which can block
the entire reactor thread. Consider making this function async and using `co_await`.
Example:
```cpp
seastar::future<T> func() {
auto result = co_await async_operation();
co_return result;
}
```
```
### 2. Exception Handling in Data Path
**Why Critical:** Exceptions in hot paths cause performance degradation and can be incorrectly propagated
**Check for:**
- Throwing exceptions in loops or per-row operations
- Using exceptions for control flow
- Missing `noexcept` when functions truly don't throw
- Incorrect `noexcept` on functions that can throw (including transitive calls)
- Unhandled exceptions in coroutines
- Functions with `noexcept` that call throwing functions
**Common noexcept Issues (from PR #27476 analysis):**
- Container operations beyond inline capacity throw (e.g., `small_vector` when exceeding N)
- Functions marked `noexcept` but calling other functions that can throw
- Need to check entire call chain, not just direct function body
- Coroutines can keep `noexcept` - exceptions convert to exceptional futures
**Example Issues:**
```cpp
// ❌ WRONG: Exception for control flow
try {
if (!condition) throw control_exception();
} catch (control_exception&) {
// handle
}
// ✅ CORRECT: Use return values or std::expected
if (!condition) {
return std::unexpected(error_code);
}
// ❌ WRONG: Can throw but marked noexcept
void process() noexcept {
vector.push_back(item); // can throw std::bad_alloc
}
// ✅ CORRECT: Remove noexcept
void process() {
vector.push_back(item);
}
// ❌ WRONG: small_vector exceeds capacity
small_vector<T, 3> get_items() noexcept {
small_vector<T, 3> result;
for (int i = 0; i < 10; i++) { // Will exceed capacity=3!
result.push_back(compute(i)); // Throws std::bad_alloc
}
return result;
}
// ✅ CORRECT: Either remove noexcept or ensure size <= capacity
small_vector<T, 10> get_items() noexcept { // Increased capacity
small_vector<T, 10> result;
for (int i = 0; i < 10; i++) {
result.push_back(compute(i)); // Won't exceed inline capacity
}
return result;
}
// ✅ CORRECT: Coroutines can keep noexcept (exceptions → futures)
seastar::future<void> process() noexcept {
try {
co_await work_that_might_throw();
} catch (...) {
// Exception converted to exceptional future automatically
}
}
```
**Feedback Template:**
```
In the data path, avoid exceptions for performance. Consider:
1. Using `std::expected<T, E>` or `boost::outcome` for results
2. Returning error codes or status enums
3. If exceptions must be used, catch and convert to exceptional_future
Also, this function is marked `noexcept` but can throw `std::bad_alloc` from
vector allocation. Either remove `noexcept` or ensure the operation truly cannot throw.
Note: Check the entire call chain - if this function calls other functions that
can throw, this function cannot be noexcept (unless it's a coroutine where exceptions
automatically convert to exceptional futures).
See PR #27476 for detailed discussion on noexcept specifications.
```
### 3. Memory Management Issues
**Why Critical:** Can cause memory leaks, crashes, or severe performance degradation
**Check for:**
- Raw `new`/`delete` usage (should use smart pointers)
- Missing RAII patterns
- Unnecessary copies of large objects (pass by `const&` or `&&`)
- Allocations in hot paths without pre-allocation
- Wrong choice of smart pointer type
**Example Issues:**
```cpp
// ❌ WRONG: Raw pointer, manual management
auto* obj = new MyObject();
// ... what if exception is thrown?
delete obj;
// ✅ CORRECT: RAII with unique_ptr
auto obj = std::make_unique<MyObject>();
// ❌ WRONG: Expensive copy in hot path
void process(large_object obj) { }
// ✅ CORRECT: Pass by const reference
void process(const large_object& obj) { }
// ❌ WRONG: Repeated allocations
for (int i = 0; i < n; i++) {
vec.push_back(compute(i));
}
// ✅ CORRECT: Pre-allocate
vec.reserve(n);
for (int i = 0; i < n; i++) {
vec.push_back(compute(i));
}
```
**Feedback Template:**
```
This code uses raw `new`/`delete` which can leak if an exception is thrown.
Use RAII with `std::unique_ptr` or `seastar::lw_shared_ptr`.
Also, consider pre-allocating the vector since the size is known:
```cpp
vec.reserve(known_size);
```
This will avoid multiple reallocations in the hot path.
```
### 4. Test Quality Issues
**Why Critical:** Flaky tests waste CI resources and hide real bugs
**Check for:**
- Hardcoded `sleep()` calls (use proper synchronization)
- Missing consistency levels in distributed tests
- Tests that don't validate the fix
- Tests without proper mode guards (debug/release)
- High tolerance for failures (e.g., "passes if only fails 10% of time")
**Example Issues:**
```python
# ❌ WRONG: Race condition with sleep
await insert_data(key, value)
await asyncio.sleep(1) # Hope it replicates?
assert await read_data(key) == value
# ✅ CORRECT: Use consistency level
await insert_data(key, value, consistency_level=Consistency.ALL)
assert await read_data(key) == value
# ❌ WRONG: Test doesn't validate the fix
def test_fix():
# Does something
assert True # Always passes, even without the fix
# ✅ CORRECT: Ensure test fails without fix
def test_fix():
# First verify test would fail without fix
# Then apply fix and verify it passes
result = the_fixed_function()
assert result == expected_value # Fails without fix
```
**Feedback Template:**
```
This test has potential reliability issues:
1. **Timing**: Instead of `sleep(1)`, use `consistency_level=Consistency.ALL`
when inserting test data to ensure replicas are synchronized.
2. **Validation**: Did you verify this test fails without your fix? Please run
the test with your fix temporarily disabled to confirm it catches the bug.
3. **Stability**: Consider running with `--repeat 100` to check for flakiness.
```
### 5. Tablets Compatibility Issues
**Why Critical:** Code using vnodes assumptions breaks with tablets feature (modern ScyllaDB)
**Check for:**
- Using `calculate_natural_endpoints()` (vnodes only)
- Accessing `token_metadata` directly instead of through ERM
- Assumptions about token ownership without tablets support
- Maintenance/recovery operations incompatible with tablets
**Example Issues:**
```cpp
// ❌ WRONG: Doesn't work with tablets (vnodes only)
auto& strat = table.get_replication_strategy();
auto endpoints = strat.calculate_natural_endpoints(token, tm);
// ✅ CORRECT: Works with both vnodes and tablets
auto erm = table.get_effective_replication_map();
auto endpoints = erm->get_natural_endpoints(token);
// ❌ WRONG: Direct token_metadata access
auto& tm = get_token_metadata();
auto endpoints = tm.get_topology().get_endpoints(token);
// ✅ CORRECT: Use ERM abstraction
auto endpoints = erm->get_natural_endpoints(token);
```
**Feedback Template:**
```
This code uses `calculate_natural_endpoints()` which only works with vnodes.
With tablets enabled, this will not work correctly.
Use the effective replication map (ERM) instead:
```cpp
auto erm = table.get_effective_replication_map();
auto endpoints = erm->get_natural_endpoints(token);
```
This works for both vnodes and tablets configurations.
See PR #15974, #21207 for examples.
```
---
## P1: High Priority Issues (Should Fix)
### 5. Poor Naming and API Design
**Check for:**
- Overly generic function names without context
- Inconsistent verb usage in related functions
- Functions in wrong namespace
- Unclear API boundaries
**Example Issues:**
```cpp
// ❌ WRONG: Too generic
namespace cql3::restrictions {
json to_json(const data& d); // to_json of what?
}
// ✅ CORRECT: Specific and clear
namespace vector_search {
json to_json(const restrictions& r); // Clear context
}
// or
json to_vector_search_json(const restrictions& r);
// ❌ WRONG: Inconsistent verbs
void parse_data();
void extract_info();
void process_items();
// ✅ CORRECT: Consistent naming
void parse_data();
void parse_info();
void parse_items();
```
**Feedback Template:**
```
The function name 'to_json' is too general. Since this is converting restrictions
to JSON specifically for vector-search consumption, consider:
1. `restrictions_to_vector_search_json()` (descriptive)
2. Moving to `vector_search::` namespace with name `to_json()`
3. Adding a comment explaining this is for the vector-store protocol only
Also, you used 'parse', 'extract', and 'process' in this patch. Pick one verb
for consistency since they all do similar things.
```
### 6. Missing Error Handling
**Check for:**
- Unchecked function calls that can fail
- Missing null pointer checks
- Silently ignored errors
- Poor error messages without context
**Example Issues:**
```cpp
// ❌ WRONG: Unchecked access
auto node = topology.get_node(host_id); // Throws if not found
node->process();
// ✅ CORRECT: Check first
auto node = topology.find_node(host_id);
if (!node) {
return make_exception_future<>(std::runtime_error(
format("Node {} not found in topology", host_id)));
}
node->process();
// ❌ WRONG: Silent error
if (auto err = do_something()) {
// Ignore error
}
// ✅ CORRECT: Handle or log
if (auto err = do_something()) {
logger.warn("Failed to do_something: {}", err);
return std::unexpected(err);
}
```
**Feedback Template:**
```
This code calls `get_node(host_id)` which throws if the node doesn't exist.
During restart scenarios, the node may not be in topology yet.
Consider using `find_node(host_id)` and checking for nullptr:
```cpp
auto node = topology.find_node(host_id);
if (!node) {
on_internal_error(logger, format("Expected node {} in topology", host_id));
}
```
If the node must exist at this point, add an assertion with context for debugging.
```
### 7. Resource Management Problems
**Check for:**
- Manual resource management instead of RAII
- Incorrect smart pointer choices
- Leaked resources in error paths
- Missing cleanup on exceptions
**Example Issues:**
```cpp
// ❌ WRONG: Manual management
semaphore sem;
sem.acquire().get();
try {
do_work();
} catch (...) {
sem.signal();
throw;
}
sem.signal();
// ✅ CORRECT: RAII
auto units = get_units(sem);
do_work();
// ❌ WRONG: std::shared_ptr for single-shard ownership
auto obj = std::make_shared<MyObject>();
// ✅ CORRECT: seastar::lw_shared_ptr for same-shard
auto obj = make_lw_shared<MyObject>();
```
**Feedback Template:**
```
This code manually manages semaphore units, which can leak if an exception is thrown.
Use RAII with `get_units()`:
```cpp
auto units = co_await get_units(sem, 1);
co_await do_work();
// units automatically released
```
Also, for same-shard sharing, prefer `seastar::lw_shared_ptr` over `std::shared_ptr`
for better performance.
```
### 8. Missing Test Coverage
**Check for:**
- Bug fixes without tests
- New features without tests
- Missing negative test cases
- No edge case testing
**Feedback Template:**
```
This PR fixes a bug but doesn't include a test. Please add a test that:
1. Reproduces the original bug (fails without your fix)
2. Passes with your fix applied
3. Documents which issue it tests (add comment with issue number)
Example:
```python
async def test_issue_12345_node_restart():
"""Test that node restart doesn't cause data loss.
Reproduces: https://github.com/scylladb/scylladb/issues/12345
"""
# Test implementation
```
```
---
## P2: Medium Priority Issues (Nice to Fix)
### 9. Code Style and Formatting
**Check for:**
- Missing spaces after commas
- Wrong indentation
- Old-style streams instead of fmt
- PEP 8 violations in Python
**Example Issues:**
```cpp
// ❌ Style issues
function(a,b,c); // Missing spaces
std::cout << value << std::endl; // Use fmt
// ✅ Correct style
function(a, b, c);
fmt::print("{}\n", value);
```
**Feedback Template:**
```
nit: Missing space after comma
nit: Consider using `fmt::print()` instead of streams for consistency
```
### 10. Documentation Issues
**Check for:**
- Comments that explain "what" instead of "why"
- Obvious comments that restate code
- Missing precondition documentation
- Undocumented public APIs
**Example Issues:**
```cpp
// ❌ WRONG: States the obvious
// Increment counter
counter++;
// ✅ CORRECT: Explains why
// Track retries for backoff calculation
counter++;
// ❌ WRONG: Missing preconditions
void process(node* n) {
n->update(); // What if n is null?
}
// ✅ CORRECT: Document assumptions
/// Process node.
/// Precondition: n must be non-null and in the topology
void process(node* n) {
assert(n != nullptr);
n->update();
}
```
**Feedback Template:**
```
nit: Eliminate this comment - the function name is self-explanatory.
For public APIs, please add documentation explaining:
- What the function does
- Preconditions and assumptions
- Return value meaning
- Any side effects
```
### 11. Code Organization
**Check for:**
- Missing subsystem prefixes in commit messages
- Unrelated changes mixed together
- Copy-pasted code that should be extracted
- Changes that should be squashed
**Feedback Template:**
```
Please add a subsystem prefix to the commit message (e.g., 'raft:', 'cql:', 'test:').
This helps with:
- Browsing changelog
- Quick relevance assessment
- Bisecting issues
- Generating release notes
Example: "raft: Fix node restart issue" instead of "Fix node restart issue"
```
### 12. Minor Optimizations
**Check for:**
- Redundant operations
- Inefficient data structures for use case
- Unnecessary intermediate structures
**Feedback Template:**
```
Could you convert `_restrictions` directly to JSON without the intermediate structure?
This would avoid an extra allocation and copy.
```
---
## Code Review Workflow
### Phase 1: Critical Issues (5 minutes)
1. Scan for async violations (`.get()`, blocking calls)
2. Check exception handling in data paths
3. Identify memory management issues
4. Flag test reliability problems
**If P0 issues found:** Stop here and request fixes before deeper review
### Phase 2: Design Review (10 minutes)
1. Evaluate API design and naming
2. Check error handling completeness
3. Review resource management patterns
4. Assess test coverage
### Phase 3: Polish (5 minutes)
1. Style and formatting
2. Documentation quality
3. Code simplification opportunities
4. Commit message quality
---
## Review Output Format
**IMPORTANT: Keep reviews concise and actionable**
### Summary (Required)
Provide a **single sentence** summarizing the most critical issue(s), **only if confident**:
- ✅ "P0: This PR blocks the reactor with `.get()` calls in 3 locations - must use `co_await` instead"
- ✅ "P1: Missing error handling for null pointer in `process_node()` - add `find_node()` check"
- ✅ "No critical issues found. Minor: Consider pre-allocating vector in hot path (line 42)"
**If uncertain or no major issues:** Skip the summary, go directly to specific comments.
### Detailed Comments (As Needed)
- Focus on P0/P1 issues
- Be specific with file/line references
- Provide concrete fix suggestions
- Avoid long explanations of "why" unless critical for correctness
### What to Avoid
**Long introductions** explaining what you're about to review
**Restating the obvious** ("This PR adds feature X...")
**Walls of text** - people will skip them
**Explaining your methodology** - just provide findings
**Academic-style reviews** - this is engineering, not a thesis defense
### Example Good Review
```
P0: Blocks reactor at service.cc:123 - replace `future.get()` with `co_await future`
P1: Missing null check at topology.cc:45 - use `find_node()` instead of `get_node()`
nit: Line 67 - missing space after comma
```
### Example Bad Review (Too Verbose)
```
## Comprehensive Analysis
I have performed a thorough examination of this pull request, analyzing
the changes across multiple dimensions including correctness, performance,
and maintainability. Let me walk you through my findings...
### Background
This PR introduces functionality that...
[3 more paragraphs of context that nobody will read]
```
---
## Reviewer Tone Guidelines
### DO: Be Specific and Educational
✅ "This can block the reactor thread because `.get()` waits synchronously. Use `co_await` instead."
✅ "For consistency with the rest of the codebase, prefer X over Y"
✅ "This works, but for better performance consider..."
✅ "See similar pattern in `service/storage_service.cc:4351`"
### DON'T: Be Vague or Harsh
❌ "This is wrong" (no context)
❌ "You should know better" (condescending)
❌ "Maybe fix this?" (too vague)
❌ Long tangents on unrelated topics
### Use "nit:" for Minor Issues
```
nit: missing space after comma
nit: extra blank line
nit: can be simplified to X
```
### Offer Alternatives
```
Consider one of these approaches:
1. Option A - simpler but less flexible
2. Option B - more complex but handles edge cases
3. Option C - matches pattern used in module X
I'd lean toward B because...
```
---
## Key Reviewer Mantras
Based on frequency and emphasis in ScyllaDB reviews:
1. **"Make it obvious"** - Self-documenting code > comments
2. **"Don't block the reactor"** - Always async/await, never `.get()`
3. **"Keep commits bisectable"** - Each commit builds and passes tests
4. **"Test what you fix"** - Bug fixes need tests
5. **"Subsystem prefixes matter"** - For changelog and bisecting
6. **"Don't allocate in hot paths"** - Performance matters
7. **"RAII everything"** - No manual resource management
8. **"Fail fast with context"** - Check assumptions, log useful info
9. **"One fiber per connection"** - Realistic concurrency patterns
10. **"Results over exceptions"** - In data path, avoid exception overhead
---
## Common Anti-Patterns to Catch
### 1. Blocking Async Operations
```cpp
auto result = async_func().get();
auto result = co_await async_func();
```
### 2. Exceptions for Control Flow
```cpp
try { if (!ok) throw control_exception(); } catch { }
if (!ok) { return handle_error(); }
```
### 3. Manual Resource Management
```cpp
sem.acquire().get(); try { work(); } finally { sem.signal(); }
auto units = co_await get_units(sem); co_await work();
```
### 4. Generic Naming
```cpp
void process(data d); // Process how?
void parse_vector_search_query(data d);
```
### 5. Flaky Test Timing
```python
await insert(x); await sleep(1); assert read(x)
await insert(x, cl=ALL); assert read(x)
```
### 6. Missing Null Checks
```cpp
auto node = get_node(id); node->update();
auto node = find_node(id); if (node) node->update();
```
### 7. Poor Error Messages
```cpp
throw std::runtime_error("error");
throw std::runtime_error(format("Node {} not found in topology", host_id));
```
### 8. Copy-Paste Without Refactoring
```cpp
Same 10 lines in 3 places
Extract to function, call from 3 places
```
### 9. Overly Coupled Code
```cpp
One function doing 5 different things
Break into focused, single-purpose functions
```
### 10. Missing Test Consistency Levels
```python
cql.execute("INSERT ...") # Default CL
cql.execute("INSERT ...", consistency_level=ConsistencyLevel.ALL)
```
---
## Integration with Existing Guidelines
When reviewing, reference these existing instruction files:
1. **`.github/instructions/cpp.instructions.md`** - C++ style, Seastar patterns, memory management
2. **`.github/instructions/python.instructions.md`** - Python style, testing patterns
3. **`.github/copilot-instructions.md`** - Build system, test philosophy, code philosophy
Example reference:
```
Per the C++ guidelines (cpp.instructions.md), prefer `seastar::lw_shared_ptr`
for same-shard sharing rather than `std::shared_ptr`.
```
---
## Distinguishing Automated vs Human Review
### Good for Automated Review (This Skill)
- ✅ Style violations (spacing, formatting)
- ✅ Common async anti-patterns (`.get()` calls)
- ✅ Missing `noexcept` specifications
- ✅ Generic naming issues
- ✅ Test synchronization patterns
- ✅ Obvious comments
- ✅ Missing error checks
### Better Left to Human Reviewers
- 🧑 Architecture and design decisions
- 🧑 Complex performance trade-off analysis
- 🧑 API design philosophy
- 🧑 Test coverage sufficiency
- 🧑 Security implications
- 🧑 Business logic correctness
- 🧑 Cross-module impact assessment
**Guideline:** When in doubt, flag for human review with context:
```
This might need a closer look from a maintainer: [explanation of concern]
@avikivity - this touches load shedding logic you authored
```
---
## Example High-Value Review Comments
### Performance Issue
```
⚠️ P0: Performance issue in hot path
This code runs for every row processed. Consider:
1. Pre-allocating the vector since size is known: `vec.reserve(row_count)`
2. Using `small_vector<T, 16>` for common case (avoids heap allocation)
3. Passing by `string_view` instead of `string` to avoid allocation
The current version allocates on every call, which will show up in profiles.
```
### Correctness Issue
```
⚠️ P0: Potential crash
This function calls `get_node(id)` which throws if the node doesn't exist.
During certain restart scenarios, the node may not be in topology yet.
Suggested fix:
```cpp
auto node = topology.find_node(id);
if (!node) {
on_internal_error(logger, format("Node {} expected in topology", id));
co_return make_exception_future<>(std::runtime_error(...));
}
```
If the node must exist here, the `on_internal_error` will help debug why it doesn't.
```
### Test Quality Issue
```
⚠️ P1: Test doesn't validate the fix
This test has a subtle issue: it doesn't verify that the fix actually works.
Please:
1. Temporarily disable your fix
2. Run the test and confirm it fails
3. Re-enable the fix
4. Run the test and confirm it passes
This ensures the test is actually validating the behavior and will catch regressions.
Also consider running `./test.py --mode=dev --repeat 100 test/...` to check for flakiness.
```
### API Design Issue
```
⚠️ P1: API naming
The function name `process()` is too generic. Since this converts internal
restrictions to JSON for vector-search consumption, consider:
**Option 1:** More descriptive name
```cpp
json restrictions_to_vector_search_json(const restrictions& r)
```
**Option 2:** Move to appropriate namespace
```cpp
namespace vector_search {
json to_json(const restrictions& r)
}
```
**Option 3:** Add clarifying comment
```cpp
/// Converts CQL restrictions to JSON format for vector-store protocol
json to_json(const restrictions& r)
```
I'd suggest Option 2 as it provides context through namespace and keeps the name concise.
```
---
## Notable ScyllaDB Reviewers and Focus Areas
When flagging for human review, consider reviewer expertise:
- **avikivity**: Performance, async patterns, test quality, architecture
- **denesb**: Reader concurrency, memory management, correctness
- **bhalevy**: Style, noexcept specifications, resource management
- **tgrabiec**: Architecture, load balancing, design patterns
- **nyh**: Naming, API clarity, code organization
- **patjed41**: Testing, Python style, edge cases
- **gleb-cloudius**: State management, topology coordination
Example: `@avikivity - this changes load shedding logic, please review performance implications`
---
## Conclusion
This reviewer skill is designed to:
1. **Prevent critical bugs** from merging (P0 issues)
2. **Help contributors learn** ScyllaDB patterns through educational feedback
3. **Reduce burden** on human reviewers for repetitive issues
4. **Maintain consistent** code quality standards
**Remember:** The goal is not to catch every issue, but to catch the most important ones and provide actionable, educational feedback that helps contributors improve.
When in doubt:
- **Be specific** with examples
- **Explain why** something matters
- **Offer alternatives** when suggesting changes
- **Reference** existing code/guidelines
- **Flag for human review** if uncertain
---
**Version:** 1.0
**Last Updated:** February 2026
**Based on:** Analysis of 200+ PRs, 700+ review comments