OpenWriterControle/.opencode/prompts
Darren Hinde c8f7103cb6
refactor(evals): consolidate documentation and enhance test infrastructure (#56)
* 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
2025-12-18 09:52:11 +00:00
..
content refactor(evals): consolidate documentation and enhance test infrastructure (#56) 2025-12-18 09:52:11 +00:00
core refactor(evals): consolidate documentation and enhance test infrastructure (#56) 2025-12-18 09:52:11 +00:00
data/data-analyst refactor(evals): consolidate documentation and enhance test infrastructure (#56) 2025-12-18 09:52:11 +00:00
development refactor(evals): consolidate documentation and enhance test infrastructure (#56) 2025-12-18 09:52:11 +00:00
README.md chore: verify and stabilize main branch (#42) 2025-12-09 13:26:52 +00:00

Prompt Library System

Multi-model prompt variants with integrated evaluation framework for testing and validation.


🎯 Quick Start

Testing a Prompt Variant

# Test with eval framework (recommended)
cd evals/framework
npm run eval:sdk -- --agent=openagent --prompt-variant=llama --suite=smoke-test

# Test with specific model
npm run eval:sdk -- --agent=openagent --prompt-variant=llama --model=ollama/llama3.2 --suite=core-tests

# View results
open ../results/index.html

Using a Variant Permanently

# Switch to a variant
./scripts/prompts/use-prompt.sh --agent=openagent --variant=llama

# Restore default (canonical agent file)
./scripts/prompts/use-prompt.sh --agent=openagent --variant=default

📁 Structure

.opencode/
├── agent/                       # Canonical agent prompts (defaults)
│   ├── openagent.md            # OpenAgent default (Claude-optimized)
│   └── opencoder.md            # OpenCoder default
└── prompts/                     # Model-specific variants
    ├── README.md               # This file
    ├── openagent/              # OpenAgent variants
    │   ├── gpt.md             # GPT-4 optimized
    │   ├── gemini.md          # Gemini optimized
    │   ├── grok.md            # Grok optimized
    │   ├── llama.md           # Llama/OSS optimized
    │   ├── TEMPLATE.md        # Template for new variants
    │   ├── README.md          # Variant documentation
    │   └── results/           # Per-variant test results
    │       ├── default-results.json  # Default (agent file) results
    │       ├── gpt-results.json
    │       ├── gemini-results.json
    │       └── llama-results.json
    └── opencoder/              # OpenCoder variants
        └── ...

Architecture:

  • Agent files (.opencode/agent/*.md) = Canonical defaults (source of truth)
  • Prompt variants (.opencode/prompts/<agent>/<model>.md) = Model-specific optimizations
  • Results always saved to .opencode/prompts/<agent>/results/ (including default)

🧪 Evaluation Framework Integration

Running Tests with Variants

The eval framework automatically:

  • ✅ Switches to the specified variant
  • ✅ Runs your test suite
  • ✅ Tracks results per variant
  • ✅ Restores the default prompt after tests
# Smoke test (1 test, ~30s)
npm run eval:sdk -- --agent=openagent --prompt-variant=llama --suite=smoke-test

# Core suite (7 tests, ~5-8min)
npm run eval:sdk -- --agent=openagent --prompt-variant=llama --suite=core-tests

# Custom test pattern
npm run eval:sdk -- --agent=openagent --prompt-variant=llama --pattern="01-critical-rules/**/*.yaml"

Auto-Model Detection

Variants specify recommended models in their YAML frontmatter:

---
model_family: llama
recommended_models:
  - ollama/llama3.2
  - ollama/qwen2.5
---

If you don't specify --model, the framework uses the first recommended model.

Results Tracking

Results are saved in two locations:

  1. Main results: evals/results/latest.json (includes prompt_variant field)
  2. Per-variant: .opencode/prompts/{agent}/results/{variant}-results.json

View in dashboard: evals/results/index.html (filter by variant)


📝 Creating a New Variant

Step 1: Copy Template

cp .opencode/prompts/openagent/TEMPLATE.md .opencode/prompts/openagent/my-variant.md

Step 2: Edit Metadata

---
model_family: oss
recommended_models:
  - ollama/my-model
status: experimental
maintainer: your-name
description: Optimized for my specific use case
---

Step 3: Customize Prompt

Edit the prompt content below the frontmatter for your target model.

Step 4: Validate

# Validate the variant exists and metadata is correct
cd evals/framework
npm run eval:sdk -- --agent=openagent --prompt-variant=my-variant --suite=smoke-test

Step 5: Test Thoroughly

# Run core test suite
npm run eval:sdk -- --agent=openagent --prompt-variant=my-variant --suite=core-tests

# Check results
open ../results/index.html

Step 6: Document Results

Update .opencode/prompts/openagent/README.md with:

  • Test results (pass rate, timing)
  • Known issues or limitations
  • Recommended use cases

🎯 Available Variants

OpenAgent

Variant Model Family Status Best For
default Claude ✅ Stable Production use, Claude models
gpt GPT ✅ Stable GPT-4, GPT-4o
gemini Gemini ✅ Stable Gemini 2.0, Gemini Pro
grok Grok ✅ Stable Grok models (free tier)
llama Llama/OSS ✅ Stable Llama, Qwen, DeepSeek, other OSS

See openagent/README.md for detailed test results.

OpenCoder

Coming soon.


🔧 Advanced Usage

Custom Test Suites

Create custom test suites for your variant:

# Create suite
cp evals/agents/openagent/config/smoke-test.json \
   evals/agents/openagent/config/my-suite.json

# Edit suite (add your tests)
# Validate suite
cd evals/framework && npm run validate:suites openagent

# Run with your variant
npm run eval:sdk -- --agent=openagent --prompt-variant=my-variant --suite=my-suite

See evals/TEST_SUITE_VALIDATION.md for details.

Comparing Models

Test the same variant with different models:

# Test Llama 3.2
npm run eval:sdk -- --agent=openagent --prompt-variant=llama --model=ollama/llama3.2 --suite=core-tests

# Test Qwen 2.5
npm run eval:sdk -- --agent=openagent --prompt-variant=llama --model=ollama/qwen2.5 --suite=core-tests

# Compare results in dashboard
open evals/results/index.html

📊 Understanding Results

Dashboard Features

The results dashboard (evals/results/index.html) shows:

  • ✅ Filter by prompt variant
  • ✅ Filter by model
  • ✅ Pass/fail rates per variant
  • ✅ Test execution times
  • ✅ Detailed test results

Result Files

Main results (evals/results/latest.json):

{
  "meta": {
    "agent": "openagent",
    "model": "ollama/llama3.2",
    "prompt_variant": "llama",
    "model_family": "llama"
  },
  "summary": {
    "total": 7,
    "passed": 7,
    "failed": 0,
    "pass_rate": 1
  }
}

Per-variant results (.opencode/prompts/openagent/results/llama-results.json):

  • Tracks all test runs for this variant
  • Shows trends over time
  • Helps identify regressions

🚀 For Contributors

Creating a Variant for PR

  1. Create your variant in .opencode/prompts/<agent>/<model>.md
  2. Test thoroughly with eval framework
  3. Document results in agent README
  4. Submit PR with variant file only

PR Requirements

  • ✅ Variant has YAML frontmatter with metadata
  • ✅ Variant passes core test suite (≥85% pass rate)
  • ✅ Results documented in agent README
  • ✅ Agent file unchanged (unless updating default)
  • ✅ No default.md files in prompts directory
  • ✅ CI validation passes

Validation

# Validate your variant
cd evals/framework
npm run eval:sdk -- --agent=openagent --prompt-variant=your-variant --suite=core-tests

# Ensure PR uses default
./scripts/prompts/validate-pr.sh

🎓 Design Principles

1. Agent Files are Canonical Defaults

  • Agent files (.opencode/agent/*.md) are the source of truth
  • Tested and production-ready
  • Optimized for Claude (primary model)
  • Modified through normal PR process

2. Variants are Model-Specific Optimizations

  • Stored in .opencode/prompts/<agent>/<model>.md
  • Optimized for specific models/use cases
  • May have different trade-offs
  • Results documented transparently

3. Results are Tracked

  • Every test run tracked per variant
  • Dashboard shows variant performance
  • Easy to compare variants

4. Easy to Test

  • One command to test any variant
  • Automatic model detection
  • Results saved automatically

5. Safe to Experiment

  • Variants don't affect default
  • Easy to switch and restore
  • Test before committing


🆘 Troubleshooting

Variant Not Found

# List available variants
ls .opencode/prompts/openagent/*.md

# Check variant exists
npm run eval:sdk -- --agent=openagent --prompt-variant=your-variant --suite=smoke-test

Tests Failing

  1. Check variant metadata (YAML frontmatter)
  2. Verify recommended model is available
  3. Run with debug flag: --debug
  4. Check results in dashboard

Model Not Available

# Check available models
# For Ollama: ollama list
# For OpenRouter: check openrouter.ai/models

# Specify model explicitly
npm run eval:sdk -- --agent=openagent --prompt-variant=llama --model=ollama/llama3.2

💡 Tips

  • Start with smoke-test - Fast validation (1 test, ~30s)
  • Use core-tests for thorough testing - 7 tests, ~5-8min
  • Check dashboard regularly - Visual feedback on variant performance
  • Document your findings - Help others by sharing results
  • Test with multiple models - Same variant may perform differently

🔮 Future Enhancements

  • Automated variant comparison reports
  • Performance benchmarking across variants
  • Variant recommendation based on model
  • Historical trend analysis
  • A/B testing framework

Questions? See openagent/README.md or open an issue.