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Version bump, claude release skill.
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---
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name: prepare-release
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description: Prepare a new release by updating CHANGELOG.md with changes since the last tag and bumping version numbers in pyproject.toml and ui/package.json
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---
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# Prepare Release
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When preparing a release, follow these steps:
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## 1. Fetch tags and identify the last release
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```bash
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git fetch --tags
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git tag --sort=-creatordate | head -5
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```
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## 2. Get commits since the last release
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```bash
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git log --oneline <last-tag>..HEAD
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```
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## 3. Read current files
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Read these files to understand current state:
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- `CHANGELOG.md` - to understand the format and existing entries
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- `pyproject.toml` - to get current version
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- `ui/package.json` - to get current UI version
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## 4. Update CHANGELOG.md
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- Add a new version section at the top (below the `# Changelog` header)
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- Organize changes into categories:
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- **Breaking Changes** - API changes that require user action
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- **New Features** - New functionality
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- **Internal Improvements** - Refactoring, tests, tooling
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- Use bold headers for each change group
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- Use bullet points for details
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- If there was an "Unreleased" section, rename it to the previous version
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## 5. Bump versions
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Update the version string in:
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- `pyproject.toml` - the `version` field under `[project]`
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- `ui/package.json` - the `"version"` field
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Use semantic versioning:
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- Patch (0.0.x) for bug fixes
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- Minor (0.x.0) for new features
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- Major (x.0.0) for breaking changes
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## 6. Summary
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After completing, summarize what was updated:
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- New version number
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- Key changes added to changelog
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- Files modified

CHANGELOG.md

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# Changelog
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## Unreleased
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## v0.1.4
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### Breaking Changes
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**Renamed `WorkerPool` to `Pool`**
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- `ax.WorkerPool` is now `ax.Pool` for cleaner API
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- Update imports: `from agentexec import Pool`
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**Activity percentage field renamed**
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- `completion_%` renamed to `percentage` for cleaner field naming
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### New Features
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**Pipelines run on workers**
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- Pipelines can now be executed on worker processes
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- Register pipelines with the pool and enqueue them like tasks
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**Tracker for stateful counters**
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- New `Tracker` class for managing stateful counters across workers
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- Useful for tracking progress, metrics, and distributed state
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**Strict Pipeline type flow validation**
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- All step parameters and return types must be `BaseModel` subclasses
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- Type flow between consecutive steps is validated at runtime
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- Tuple returns are unpacked and matched to next step's parameters
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- Final step must return a single `BaseModel` (not a tuple)
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- Empty pipelines raise `RuntimeError` at class definition time
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### Internal Improvements
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**Type checking with `ty`**
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- Added `ty` type checker to development workflow
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- Better Protocol definitions for step handlers
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- Improved type hints throughout pipeline module
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**Better Pipeline flow tests**
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- Comprehensive test coverage for valid and invalid type flows
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- Tests for tuple unpacking, subclass compatibility, count mismatches
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- Tests for primitive type rejection and edge cases
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## v0.1.3
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### Breaking Changes
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pyproject.toml

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[project]
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name = "agentexec"
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version = "0.1.3"
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version = "0.1.4"
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description = "Production-ready orchestration for OpenAI Agents with Redis-backed coordination, activity tracking, and workflow management"
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readme = "README.md"
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requires-python = ">=3.12"

ui/package.json

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{
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"name": "agentexec-ui",
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"version": "0.1.3",
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"version": "0.1.4",
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"description": "React components for agentexec background agent monitoring",
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"type": "module",
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"main": "./dist/index.cjs",

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