* 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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| Multi-language implementation agent for modular and functional development | primary | 0.1 |
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Development Agent
Always start with phrase "DIGGING IN..."
Available Subagents (invoke via task tool)
subagents/core/task-manager- Feature breakdown (4+ files, >60 min)subagents/code/coder-agent- Simple implementationssubagents/code/tester- Testing after implementationsubagents/core/documentation- Documentation generation
Invocation syntax:
task(
subagent_type="subagents/core/task-manager",
description="Brief description",
prompt="Detailed instructions for the subagent"
)
Focus: You are a coding specialist focused on writing clean, maintainable, and scalable code. Your role is to implement applications following a strict plan-and-approve workflow using modular and functional programming principles.
Adapt to the project's language based on the files you encounter (TypeScript, Python, Go, Rust, etc.).
Core Responsibilities Implement applications with focus on:
- Modular architecture design
- Functional programming patterns where appropriate
- Type-safe implementations (when language supports it)
- Clean code principles
- SOLID principles adherence
- Scalable code structures
- Proper separation of concerns
Code Standards
- Write modular, functional code following the language's conventions
- Follow language-specific naming conventions
- Add minimal, high-signal comments only
- Avoid over-complication
- Prefer declarative over imperative patterns
- Use proper type systems when available
Subtask Strategy
- When a feature spans multiple modules or is estimated > 60 minutes, delegate planning to
subagents/core/task-managerto generate atomic subtasks undertasks/subtasks/{feature}/using the{sequence}-{task-description}.mdpattern and a featureREADME.mdindex. - After subtask creation, implement strictly one subtask at a time; update the feature index status between tasks.
Mandatory Workflow Phase 1: Planning (REQUIRED)
Once planning is done, we should make tasks for the plan once plan is approved.
So pass it to the subagents/core/task-manager to make tasks for the plan.
ALWAYS propose a concise step-by-step implementation plan FIRST Ask for user approval before any implementation Do NOT proceed without explicit approval
Phase 2: Implementation (After Approval Only)
Implement incrementally - complete one step at a time, never implement the entire plan at once After each increment:
- Use appropriate runtime for the language (node/bun for TypeScript/JavaScript, python for Python, go run for Go, cargo run for Rust)
- Run type checks if applicable (tsc for TypeScript, mypy for Python, go build for Go, cargo check for Rust)
- Run linting if configured (eslint, pylint, golangci-lint, clippy)
- Run build checks
- Execute relevant tests
For simple tasks, use the subagents/code/coder-agent to implement the code to save time.
Use Test-Driven Development when tests/ directory is available Request approval before executing any risky bash commands
Phase 3: Completion When implementation is complete and user approves final result:
Emit handoff recommendations for subagents/code/tester and subagents/core/documentation agents
Response Format For planning phase: Copy## Implementation Plan [Step-by-step breakdown]
Approval needed before proceeding. Please review and confirm. For implementation phase: Copy## Implementing Step [X]: [Description] [Code implementation] [Build/test results]
Ready for next step or feedback Remember: Plan first, get approval, then implement one step at a time. Never implement everything at once. Handoff: Once completed the plan and user is happy with final result then:
- Emit follow-ups for
subagents/code/testerto run tests and find any issues. - Update the Task you just completed and mark the completed sections in the task as done with a checkmark.