- Restore Payment Intents flow removed by PR, updated for modern best practices
- Use Payment Element instead of legacy Card Element
- Use stripe.confirmPayment() instead of deprecated confirmCardPayment()
- Use automatic_payment_methods instead of hardcoded payment_method_types
- Split Python/JS into separate fenced code blocks for clarity
- Add guidance on when to use Payment Intents vs Checkout Sessions
- Renumber subsequent patterns (Subscription → 4, Customer Portal → 5)
- Remove payment_method_types=['card'] from Quick Start (dynamic payment methods)
- Remove unused appearance variable from Pattern 2 JS example
- Fix actions access pattern: destructure before use for consistency
- Add inline comments clarifying sync/async distinction and amount format
- Add ui_mode='embedded' to Embedded checkout bullet for completeness
- Replace payment_method_types with automatic_payment_methods in test example
Sync marketplace.json versions with plugin.json for all 14 touched
plugins. Fix plugin.json versions for llm-application-dev (2.0.3),
startup-business-analyst (1.0.4), and ui-design (1.0.2) to match
marketplace lineage. Add dotnet-contribution to marketplace.
Rewrites 14 commands across 11 plugins to remove all cross-plugin
subagent_type references (e.g., "unit-testing::test-automator"), which
break when plugins are installed standalone. Each command now uses only
local bundled agents or general-purpose with role context in the prompt.
All rewritten commands follow conductor-style patterns:
- CRITICAL BEHAVIORAL RULES with strong directives
- State files for session tracking and resume support
- Phase checkpoints requiring explicit user approval
- File-based context passing between steps
Also fixes 4 plugin.json files missing version/license fields and adds
plugin.json for dotnet-contribution.
Closes#433
Add .claude-plugin/plugin.json to all 67 remaining plugins and simplify
marketplace.json entries by removing redundant fields (keywords, strict,
commands, agents, skills, repository) that are now auto-discovered.
Bump marketplace version to 1.5.0.
Remove .mcp.json to eliminate external MCP dependency that likely caused plugin load failure.
Add tools: field to all agents, version: field to all skills, matching conductor plugin patterns.
New plugin with 7 presets (review, debug, feature, fullstack, research,
security, migration), 4 specialized agents, 7 slash commands, 6 skills
with reference docs, and Context7 MCP integration for research teams.
* Add extra python skills covering code style, design patterns, resilience, resource management, testing patterns, and type safety ...etc
* fix: correct code examples in Python skills
- Clarify Python version requirements for type statement (3.10+ vs 3.12+)
- Add missing ValidationError import in configuration example
- Add missing httpx import and url parameter in async example
---------
Co-authored-by: Seth Hobson <wshobson@gmail.com>
- 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
* 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>
