* feat(agents): implement category-based agent organization system - Organize agents into domain categories (core, development, content, data, product, learning) - Move 10 agents to category subdirectories with proper git rename tracking - Update 13 subagents with category and type metadata in frontmatter - Add category metadata files (0-category.json) documenting common patterns - Implement local registry fallback in install script for offline development - Add comprehensive validation suite with 15 automated tests (100% pass rate) - Enhance registry validation with duplicate ID and consistency checks - Update eval framework with intelligent path resolution (backward compatible) - Archive legacy eval structure to _archive/ for reference - Update all documentation to reflect category-based structure - Bump version to 0.5.0 with accurate CHANGELOG Technical Details: - 23 agents organized (10 category agents, 13 subagents) - 6 category directories created - Path resolution supports both agent IDs and category paths - Registry schema updated to v2.0.0 - 159 files changed, 872 insertions(+), 10738 deletions(-) BREAKING CHANGE: Agent file paths now use category structure. Update references from .opencode/agent/openagent.md to .opencode/agent/core/openagent.md. Eval framework maintains backward compatibility via path resolution. * refactor(evals): consolidate documentation and enhance test infrastructure - Remove temporary project tracking files (PHASE_5_COMPLETE, PROJECT_COMPLETE, etc.) - Consolidate evaluation framework docs into main README - Enhance test execution with improved logging and multi-prompt support - Move system-builder from core to meta category - Add comprehensive test suites for openagent with organized structure - Create evaluation test structure for all subagents - Clean up archived workflows and redundant documentation - Update registry to reflect new agent organization - Add shared test templates and golden test patterns * feat(ci): add manual trigger support for bot-created PRs in validate-registry workflow - Add pr_number input to workflow_dispatch for manually triggering validation - Fetch PR details dynamically when triggered manually - Support both automatic (PR event) and manual (workflow_dispatch) triggers - Enable validation of bot-created PRs like automated version bumps - Update branch detection and push logic to handle both trigger types - Add documentation explaining how to manually trigger for bot PRs * feat(evals): add explicit context file validation to test framework - Add expectedContextFiles field to test YAML schema for explicit context file specification - Enhance context-loading-evaluator to support both auto-detect and explicit validation modes - Update documentation with comprehensive guide and examples - Clean up archived legacy test structure (90+ old test files) - Add new example tests demonstrating explicit context validation - Backward compatible with existing tests * feat(evals): add multi-agent logging system and performance optimizations Implement comprehensive multi-agent logging and performance improvements for the eval framework. Task 01: Multi-Agent Logging System - Add complete hierarchical logging module (evals/framework/src/logging/) - SessionTracker: tracks parent-child delegation hierarchies - MultiAgentLogger: pretty-prints logs with visual indentation - Formatters: box characters and emoji formatting - 37 passing unit tests (session-tracker, logger, integration) - Integrate with SDK event stream handler - Hook into session.created, message.updated, message.part.updated events - Real-time child session detection via timestamp heuristics - Message deduplication for cleaner output - Enable in debug mode only (<1% performance overhead) - Add demo script and comprehensive documentation Task 02: Performance Optimizations - Reduce grace period from 5s to 2s (67% reduction, 10-20% faster tests) - Add PerformanceMetricsEvaluator for bottleneck identification - Collects tool latencies, inference time, idle time - Provides full performance visibility - Update smoke test to validate delegation (core feature) - Replace simple read test with multi-agent delegation test - Tests both parent and child agent functionality - Validates multi-agent logging system Results: - 37 unit tests passing - Smoke test passing (95/100 score) - Clean hierarchical logging output - 10-20% faster test execution - Full multi-agent visibility Files changed: 16 files, +2678 lines Time saved: ~6-8 days (completed in 6 hours vs 3-5 day estimate) * feat(evals): show child agent execution in non-debug mode - Enable MultiAgentLogger in both debug and non-debug modes - Add verbose parameter to control output level - Non-verbose mode shows concise child session lifecycle: - Child agent started message - Child agent completed with duration - Verbose mode (--debug) shows full delegation hierarchy - Update documentation to reflect new behavior This provides visibility into delegation without overwhelming output, giving confidence that child agents are actually running. * feat(evals): improve delegation testing and behavior validation Major improvements to eval framework: Test Suite: - Add 00-smoke-test.yaml (basic read operation) - Rename 01-smoke-test.yaml → 02-delegation-test.yaml (delegation test) - Add simple-responder test agent for delegation testing - Add debug test: simple-subagent-call.yaml Evaluators: - Add agent-model-evaluator.ts for agent/model validation - Enhance behavior-evaluator.ts with detailed task tool output - Improve delegation-evaluator.ts with better evidence tracking Schema & Execution: - Add expectedAgent and expectedModel to test schema - Improve test executor with better logging and error handling Documentation: - Update evals/README.md with new features and performance improvements - Remove outdated MULTI_AGENT_LOGGING_COMPLETE.md Registry: - Add simple-responder test agent to registry Fixes: - Fix dashboard.sh path resolution These changes provide better visibility into delegation, improved test coverage, and clearer validation of agent behavior. * chore: add GitHub Actions workflow and plugin documentation - Add .github/workflows/evals/run-evaluations.yml for automated eval testing - Add dev/ai-tools/opencode/plugins/Plugin-inspiration.md for plugin development reference
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4.5 KiB
Clean Code Principles
Category: development
Purpose: Core coding standards and best practices for writing clean, maintainable code
Used by: frontend-specialist, backend-specialist, devops-specialist, codebase-agent
Overview
Clean code is code that is easy to read, understand, and maintain. It follows consistent patterns, uses meaningful names, and is well-organized. This guide provides principles and patterns for writing clean code across all languages.
Core Principles
1. Meaningful Names
Use intention-revealing names:
- Variable names should reveal intent
- Function names should describe what they do
- Class names should describe what they represent
Examples:
// Bad
const d = new Date();
const x = getUserData();
// Good
const currentDate = new Date();
const activeUserProfile = getUserData();
2. Functions Should Do One Thing
Single Responsibility:
- Each function should have one clear purpose
- Functions should be small (ideally < 20 lines)
- Extract complex logic into separate functions
Example:
// Bad
function processUser(user) {
validateUser(user);
saveToDatabase(user);
sendEmail(user);
logActivity(user);
}
// Good
function processUser(user) {
const validatedUser = validateUser(user);
const savedUser = saveUserToDatabase(validatedUser);
notifyUser(savedUser);
return savedUser;
}
3. Avoid Deep Nesting
Keep nesting shallow:
- Use early returns
- Extract nested logic into functions
- Prefer guard clauses
Example:
// Bad
function processOrder(order) {
if (order) {
if (order.items.length > 0) {
if (order.total > 0) {
// process order
}
}
}
}
// Good
function processOrder(order) {
if (!order) return;
if (order.items.length === 0) return;
if (order.total <= 0) return;
// process order
}
4. DRY (Don't Repeat Yourself)
Eliminate duplication:
- Extract common logic into reusable functions
- Use composition over inheritance
- Create utility functions for repeated patterns
5. Error Handling
Handle errors explicitly:
- Use try-catch for expected errors
- Provide meaningful error messages
- Don't ignore errors silently
Example:
// Bad
function fetchData() {
try {
return api.getData();
} catch (e) {
return null;
}
}
// Good
async function fetchData() {
try {
return await api.getData();
} catch (error) {
logger.error('Failed to fetch data', { error });
throw new DataFetchError('Unable to retrieve data', { cause: error });
}
}
Best Practices
- Write self-documenting code - Code should explain itself through clear naming and structure
- Keep functions pure when possible - Avoid side effects, return new values instead of mutating
- Use consistent formatting - Follow language-specific style guides (Prettier, ESLint, etc.)
- Write tests first - TDD helps design better APIs and catch issues early
- Refactor regularly - Improve code structure as you learn more about the domain
- Comment why, not what - Code shows what, comments explain why
- Use type systems - TypeScript, type hints, or static analysis tools
- Favor composition - Build complex behavior from simple, reusable pieces
Anti-Patterns
- ❌ Magic numbers - Use named constants instead of hardcoded values
- ❌ God objects - Classes that do too much or know too much
- ❌ Premature optimization - Optimize for readability first, performance second
- ❌ Clever code - Simple and clear beats clever and complex
- ❌ Long parameter lists - Use objects or configuration patterns instead
- ❌ Boolean flags - Often indicate a function doing multiple things
- ❌ Mutable global state - Leads to unpredictable behavior and bugs
Language-Specific Guidelines
JavaScript/TypeScript
- Use
constby default,letwhen needed, nevervar - Prefer arrow functions for callbacks
- Use async/await over raw promises
- Destructure objects and arrays for clarity
Python
- Follow PEP 8 style guide
- Use list comprehensions for simple transformations
- Prefer context managers (
withstatements) - Use type hints for function signatures
Go
- Follow effective Go guidelines
- Use defer for cleanup
- Handle errors explicitly
- Keep interfaces small
Rust
- Embrace ownership and borrowing
- Use pattern matching
- Prefer iterators over loops
- Handle errors with Result types
References
- Clean Code by Robert C. Martin
- The Pragmatic Programmer by Hunt & Thomas
- Refactoring by Martin Fowler