- Migrate from LangChain 0.x to LangChain 1.x/LangGraph patterns
- Update model references to Claude 4.5 and GPT-5.2
- Add Voyage AI as primary embedding recommendation
- Add structured outputs with Pydantic
- Replace deprecated initialize_agent() with StateGraph
- Fix security: use AST-based safe math instead of unsafe execution
- Add plugin.json and README.md for consistency
- Bump marketplace version to 1.3.3
Add /conductor:manage command with comprehensive track lifecycle operations:
- Archive completed tracks with reason tracking
- Restore archived tracks to active state
- Delete tracks permanently with safety confirmations
- Rename track IDs with full reference updates
- Cleanup orphaned artifacts and stale tracks
- Interactive menu when invoked without arguments
Also includes:
- Add Archived Tracks section to tracks.md template
- Update README with manage command documentation
- Bump version to 1.1.0
- Format files with prettier
- Add acknowledgments section crediting gemini-cli-extensions/conductor
- Credit @wshobson for Claude Code adaptation
- Update license from MIT to Apache-2.0 to match original
Based on research of official plugins:
- Add allowed-tools array to all 5 commands (required field in working plugins)
- Simplify marketplace.json entry to match official format (minimal fields, auto-discovery)
- Remove explicit commands/agents/skills arrays (rely on auto-discovery like official plugins)
Version: 1.0.6
- Add minimal .claude-plugin/plugin.json to conductor and startup-business-analyst
(matches official format: name, description, author only)
- Remove .gitignore from startup-business-analyst (not in official plugins)
- Bump versions: conductor 1.0.5, startup-business-analyst 1.0.2
Plugin structure now matches official examples (feature-dev, ralph-loop, etc.)
- Remove YAML frontmatter from command files (commands don't use frontmatter)
- Remove non-standard fields (color, tools) from conductor-validator agent
- Simplify agent description to single line format
Remove reference to ./skills/monorepo-dependency-management which
does not exist. The correct skill ./skills/monorepo-management is
already listed.
Fixes#406
* feat: add security middleware to REST API template
Adds `TrustedHostMiddleware` and `CORSMiddleware` to the FastAPI template to ensure basic security protections are in place. Includes comments guiding users on how to configure these for production.
- Added TrustedHostMiddleware for Host header validation
- Added CORSMiddleware for Cross-Origin Resource Sharing
- Added TODOs for production configuration
* feat: add security middleware to REST API template
Adds `TrustedHostMiddleware` and `CORSMiddleware` to the FastAPI template to ensure basic security protections are in place. Includes comments guiding users on how to configure these for production.
- Added TrustedHostMiddleware for Host header validation
- Added CORSMiddleware for Cross-Origin Resource Sharing
- Configured safe defaults (allow_credentials=False) for the template
- Added TODOs for production configuration
* feat: secure API template and fix Pydantic deprecations
Enhances `rest-api-template.py` with standard security middleware and updates Pydantic usage to V2 standards.
- Added `TrustedHostMiddleware` and `CORSMiddleware` with safe defaults
- Updated Pydantic models to use `ConfigDict` and `model_dump()` to resolve deprecation warnings
- Documented security learnings in sentinel journal
---------
Co-authored-by: google-labs-jules[bot] <161369871+google-labs-jules[bot]@users.noreply.github.com>
- Avoid re-evaluating the current prompt if metrics are already available from the previous iteration.
- Pass metrics from the best variation to the next iteration.
- Reduces N-1 expensive LLM calls in an N-iteration optimization loop.
Co-authored-by: google-labs-jules[bot] <161369871+google-labs-jules[bot]@users.noreply.github.com>
* ⚡ Bolt: Reuse ThreadPoolExecutor in PromptOptimizer
💡 What:
Initialized `ThreadPoolExecutor` in `PromptOptimizer.__init__` and reused it in `evaluate_prompt`.
🎯 Why:
The previous implementation created a new `ThreadPoolExecutor` for every call to `evaluate_prompt`. Since `evaluate_prompt` is called repeatedly inside the `optimize` loop (and for every variation), this caused significant overhead from repeatedly creating and destroying thread pools.
📊 Impact:
Benchmark showed a reduction in execution time from ~5.36s to ~3.76s (~30% improvement) for 500 iterations with a mocked LLM.
🔬 Measurement:
Ran a benchmark script executing `evaluate_prompt` 500 times.
Before: 5.36s
After: 3.76s
* ⚡ Bolt: Reuse ThreadPoolExecutor in PromptOptimizer
💡 What:
Initialized `ThreadPoolExecutor` in `PromptOptimizer.__init__` and reused it in `evaluate_prompt`. Added a `shutdown` method for proper cleanup.
🎯 Why:
The previous implementation created a new `ThreadPoolExecutor` for every call to `evaluate_prompt`. Since `evaluate_prompt` is called repeatedly inside the `optimize` loop (and for every variation), this caused significant overhead from repeatedly creating and destroying thread pools.
📊 Impact:
Benchmark showed a reduction in execution time from ~5.36s to ~3.76s (~30% improvement) for 500 iterations with a mocked LLM.
🔬 Measurement:
Ran a benchmark script executing `evaluate_prompt` 500 times.
Before: 5.36s
After: 3.76s
* ⚡ Bolt: Reuse ThreadPoolExecutor in PromptOptimizer
💡 What:
Initialized `ThreadPoolExecutor` in `PromptOptimizer.__init__` and reused it in `evaluate_prompt`. Added a `shutdown` method and wrapped execution in `try...finally` for proper resource management.
🎯 Why:
The previous implementation created a new `ThreadPoolExecutor` for every call to `evaluate_prompt`. Since `evaluate_prompt` is called repeatedly inside the `optimize` loop (and for every variation), this caused significant overhead from repeatedly creating and destroying thread pools.
📊 Impact:
Benchmark showed a reduction in execution time from ~5.36s to ~3.76s (~30% improvement) for 500 iterations with a mocked LLM.
🔬 Measurement:
Ran a benchmark script executing `evaluate_prompt` 500 times.
Before: 5.36s
After: 3.76s
---------
Co-authored-by: google-labs-jules[bot] <161369871+google-labs-jules[bot]@users.noreply.github.com>
* feat: Parallelize prompt evaluation in optimize-prompt.py
- Update `PromptOptimizer.evaluate_prompt` to use `ThreadPoolExecutor` for concurrent test case processing
- Significantly reduces total execution time when using high-latency LLM clients (network IO bound)
- Maintain accurate metric aggregation (latency, accuracy, token count) from parallel results
- This prepares the script for real-world usage where sequential execution is a major bottleneck
⚡ Bolt: Reduces total evaluation time from O(n) to O(1) latency-wise (bounded by max_workers) for concurrent requests.
* feat: Parallelize prompt evaluation in optimize-prompt.py
- Update `PromptOptimizer.evaluate_prompt` to use `ThreadPoolExecutor` for concurrent test case processing
- Significantly reduces total execution time when using high-latency LLM clients (network IO bound)
- Maintain accurate metric aggregation (latency, accuracy, token count) from parallel results
- Ensure no generated artifacts (`optimization_results.json`) are committed
⚡ Bolt: Reduces total evaluation time from O(n) to O(1) latency-wise (bounded by max_workers) for concurrent requests.
---------
Co-authored-by: google-labs-jules[bot] <161369871+google-labs-jules[bot]@users.noreply.github.com>
* docs(agents): add haskell-pro
* fixup
* Move haskell-pro agent to functional-programming plugin
- Moved plugins/haskell-development/agents/haskell-pro.md to plugins/functional-programming/agents/haskell-pro.md
- Updated path reference in docs/agents.md
This addresses review feedback to place the Haskell agent in the existing functional-programming plugin alongside elixir-pro, rather than creating a new haskell-development plugin.
🤖 Generated with [Claude Code](https://claude.com/claude-code)
Co-Authored-By: Claude <noreply@anthropic.com>
---------
Co-authored-by: Claude <noreply@anthropic.com>
* Updated GPT and Claude models to latest, better and cheaper models
* updated more files to use GPT-5 and Sonnet/Haiku 4.5 because theu are the latest, cheaper and better models
Add comprehensive Julia 1.10+ development support including:
- Modern Julia features (multiple dispatch, metaprogramming)
- Package management with Pkg.jl and PkgTemplates.jl
- Code formatting with JuliaFormatter.jl (BlueStyle)
- Scientific computing (DifferentialEquations.jl, DataFrames.jl)
- Machine learning (Flux.jl, MLJ.jl)
- Performance optimization and type stability
- Testing and benchmarking best practices
- Web development with Genie.jl and Oxygen.jl
The julia-pro agent provides expert guidance on production-ready
Julia development following community best practices.
Add new developer-essentials plugin containing 8 high-value skills that
address critical gaps in the existing skill coverage:
Skills Added:
- git-advanced-workflows: Advanced Git techniques (rebase, cherry-pick, bisect, worktrees, reflog)
- sql-optimization-patterns: SQL query optimization, indexing, and EXPLAIN analysis
- error-handling-patterns: Multi-language error handling strategies and patterns
- code-review-excellence: Effective code review practices and constructive feedback
- e2e-testing-patterns: End-to-end testing with Playwright and Cypress
- auth-implementation-patterns: Authentication/authorization with JWT, OAuth2, RBAC
- debugging-strategies: Systematic debugging techniques and profiling tools
- monorepo-management: Monorepo setup and management with Turborepo, Nx, pnpm
These skills were identified through comprehensive research of:
- Existing 50+ skills across 14 plugins in the project
- Anthropic's official skills repository
- Gap analysis revealing missing coverage in general developer workflows
Changes:
- Added plugins/developer-essentials/ with 8 new SKILL.md files
- Updated .claude-plugin/marketplace.json to register new plugin
- Updated docs/agent-skills.md (47→55 skills, 14→15 plugins)
Each skill follows Anthropic's Agent Skills Specification with proper
YAML frontmatter, progressive disclosure, and clear activation triggers.
🤖 Generated with Claude Code (https://claude.com/claude-code)
Co-authored-by: Claude <noreply@anthropic.com>
