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Rebase from the latest origin/main, squash branch commits, and create or update a GitHub pull request. Use when asked to prepare or create a PR.
Install with Codex or Claude Copy this prompt, paste it into Codex, Claude, or another assistant, and let it review the skill page and install it for you.
Based on SOC occupation classification
| name | create-pr |
| description | Rebase from the latest origin/main, squash branch commits, and create or update a GitHub pull request. Use when asked to prepare or create a PR. |
Rebase from the latest origin/main, squash commits, and create a PR on GitHub with an
intelligent title and description.
$create-pr [--draft] [--base <branch>]
Arguments:
--draft: Create as draft PR--base <branch>: Target branch (default: main)# Check current branch
git branch --show-current
# Check if on main/master (should NOT be)
if [[ $(git branch --show-current) == "main" || $(git branch --show-current) == "master" ]]; then
echo "ERROR: Cannot create PR from main/master branch"
exit 1
fi
# Check for uncommitted changes
git status --short
# Ensure gh CLI is available
gh --version
Action: If there are uncommitted changes, stop, and then ask user to commit or stash them first.
# Check if PR already exists for current branch
gh pr view --json number,title,url 2>/dev/null || echo "No existing PR"
Handle Existing PR:
# Fetch latest from origin
git fetch origin main
# Check divergence
git log --oneline HEAD ^origin/main
# Non-interactive rebase onto origin/main
git rebase origin/main
Handle Conflicts: If rebase fails due to conflicts, abort and let user handle rebase manually:
# On rebase failure, abort automatically
git rebase --abort
# Inform user to resolve conflicts manually
echo "Rebase failed due to conflicts. Please resolve manually and retry $create-pr"
exit 1
After successful rebase, squash all commits since origin/main into a single commit:
# Count commits to squash
git rev-list --count origin/main..HEAD
# Soft reset to origin/main (keeps changes staged)
git reset --soft origin/main
# Generate commit message using $gen-commit-msg logic
# See ../gen-commit-msg/SKILL.md for message generation rules
Generate Commit Message (following $gen-commit-msg format):
Analyze staged changes:
git diff --cached --name-only
git diff --cached
Categorize changes (feat/fix/docs/refactor/test/chore/perf)
Determine scope from changed files (workflow/engine/reward/dataset/api/docs/etc.)
Generate message in format:
<type>(<scope>): <subject>
<body>
[Optional sections:]
Key changes:
- change 1
- change 2
Refs: #123, #456
Commit with generated message:
git commit -m "$(cat <<'EOF'
<generated commit message>
EOF
)"
After squashing into a single commit:
# Get all changes since origin/main
git diff origin/main...HEAD --name-only
# Get full diff content
git diff origin/main...HEAD
# Check commit history
git log --oneline origin/main..HEAD
Categorize Changes:
Follow same categorization as $gen-commit-msg:
| Type | When to Use |
|---|---|
feat | New feature or capability |
fix | Bug fix |
docs | Documentation only |
refactor | Code change without feature/fix |
test | Adding or fixing tests |
chore | Build, deps, config changes |
perf | Performance improvement |
Determine Scope:
Infer from changed files:
src/workflow/ → workflowsrc/engine/ → enginesrc/reward/ → rewardsrc/dataset/ → datasetsrc/api/ → apisrc/utils/ → utilssrc/infra/ → infradocs/ → docsexamples/ → examplesPR Title Format:
<type>(<scope>): <brief description>
Rules:
PR Description Format:
MUST strictly follow the GitHub PR template:
## Description
<!-- Clear and concise description of what this PR does -->
## Related Issue
<!-- Link to the issue this PR addresses -->
Fixes #(issue)
## Type of Change
<!-- Mark the relevant option with an 'x' -->
- [ ] Bug fix (non-breaking change that fixes an issue)
- [ ] New feature (non-breaking change that adds functionality)
- [ ] Breaking change (fix or feature that would cause existing functionality to not work as expected)
- [ ] Documentation update
- [ ] Code refactoring (no functional changes)
- [ ] Performance improvement
- [ ] Test coverage improvement
## Checklist
<!-- Mark with 'x' what you've done -->
- [ ] I have read the [Contributing Guide](../CONTRIBUTING.md)
- [ ] I have run formatting tools (pre-commit or manual)
- [ ] I have run relevant unit tests and they pass
- [ ] I have added tests for new functionality
- [ ] I have updated documentation if needed
- [ ] My branch is up to date with main
- [ ] This PR introduces breaking changes (if yes, fill out details below)
- [ ] If this PR changes documentation, I have built and previewed it locally with `jb build docs`
- [ ] No critical issues raised by AI reviewers (`/gemini review`)
**Breaking Change Details (if applicable):**
<!-- Describe what breaks and how users should migrate -->
## Additional Context
<!-- Add any other context, screenshots, logs, or explanations here -->
How to Fill the Template:
[x][x], leave uncompleted as [ ]Show preview to user:
─────────────────────────────────────────────────
Branch: feat/vision-rlvr → main
PR Title:
feat(workflow): add vision support to ImageProcessing
PR Description:
## Description
Add ImageProcessingWorkflow for vision-language RL training. Supports image inputs
alongside text prompts and integrates with existing ImageProcessing pipeline.
## Related Issue
Fixes #789
## Type of Change
- [ ] Bug fix (non-breaking change that fixes an issue)
- [x] New feature (non-breaking change that adds functionality)
- [ ] Breaking change (fix or feature that would cause existing functionality to not work as expected)
- [ ] Documentation update
- [ ] Code refactoring (no functional changes)
- [ ] Performance improvement
- [ ] Test coverage improvement
## Checklist
- [x] I have read the [Contributing Guide](../CONTRIBUTING.md)
- [x] I have run formatting tools (pre-commit or manual)
- [ ] I have run relevant unit tests and they pass
- [x] I have added tests for new functionality
- [x] I have updated documentation if needed
- [x] My branch is up to date with main
- [ ] This PR introduces breaking changes (if yes, fill out details below)
- [x] If this PR changes documentation, I have built and previewed it locally with `jb build docs`
- [ ] No critical issues raised by AI reviewers (`/gemini review`)
**Breaking Change Details (if applicable):**
N/A
## Additional Context
Requires Pillow>=10.0.0 for image processing.
Files changed:
- `src/workflow/image_processing.py`: New ImageProcessingWorkflow class
- `src/api/config.py:45`: Add image processing config fields
- `examples/vision_rlvr.py`: Example training script
- `docs/workflows/vision.md`: Documentation
─────────────────────────────────────────────────
Commands to execute:
1. git push -u origin feat/vision-rlvr
2. gh pr create --title "..." --body "..." [--draft]
─────────────────────────────────────────────────
Confirm with user, then execute:
# Force push branch to remote (required after squash)
git push -f -u origin $(git branch --show-current)
# Create or edit PR using gh CLI with GitHub template format
# If PR exists, use 'gh pr edit' instead of 'gh pr create'
if gh pr view &>/dev/null; then
# Update existing PR
gh pr edit \
--title "feat(workflow): add vision support to ImageProcessing" \
--body "$(cat <<'EOF'
[PR description here]
EOF
)"
else
# Create new PR
gh pr create \
--base main \
--title "feat(workflow): add vision support to ImageProcessing" \
--body "$(cat <<'EOF'
## Description
Add ImageProcessingWorkflow for vision-language RL training. Supports image inputs
alongside text prompts and integrates with existing ImageProcessing pipeline.
## Related Issue
Fixes #789
## Type of Change
- [ ] Bug fix (non-breaking change that fixes an issue)
- [x] New feature (non-breaking change that adds functionality)
- [ ] Breaking change (fix or feature that would cause existing functionality to not work as expected)
- [ ] Documentation update
- [ ] Code refactoring (no functional changes)
- [ ] Performance improvement
- [ ] Test coverage improvement
## Checklist
- [x] I have read the [Contributing Guide](../CONTRIBUTING.md)
- [x] I have run formatting tools (pre-commit or manual)
- [ ] I have run relevant unit tests and they pass
- [x] I have added tests for new functionality
- [x] I have updated documentation if needed
- [x] My branch is up to date with main
- [ ] This PR introduces breaking changes (if yes, fill out details below)
- [x] If this PR changes documentation, I have built and previewed it locally with `jb build docs`
- [ ] No critical issues raised by AI reviewers (`/gemini review`)
**Breaking Change Details (if applicable):**
N/A
## Additional Context
Requires Pillow>=10.0.0 for image processing.
Files changed:
- `src/workflow/image_processing.py`: New ImageProcessingWorkflow class
- `src/api/config.py:45`: Add image processing config fields
- `examples/vision_rlvr.py`: Example training script
- `docs/workflows/vision.md`: Documentation
EOF
)"
fi
Add --draft flag if requested.
Capture PR URL and display to user:
✓ PR created/updated successfully!
https://github.com/example/project/pull/123
Changes: New dataset loader for MATH dataset
PR Title:
feat(dataset): add MATH dataset loader
PR Description:
## Description
Add MathDataset loader for mathematics problem solving with LaTeX rendering and
symbolic math parsing. Includes reward function for automatic answer verification
and full test coverage.
## Related Issue
Fixes #456
## Type of Change
- [ ] Bug fix (non-breaking change that fixes an issue)
- [x] New feature (non-breaking change that adds functionality)
- [ ] Breaking change (fix or feature that would cause existing functionality to not work as expected)
- [ ] Documentation update
- [ ] Code refactoring (no functional changes)
- [ ] Performance improvement
- [ ] Test coverage improvement
## Checklist
- [x] I have read the [Contributing Guide](../CONTRIBUTING.md)
- [x] I have run formatting tools (pre-commit or manual)
- [x] I have run relevant unit tests and they pass
- [x] I have added tests for new functionality
- [x] I have updated documentation if needed
- [x] My branch is up to date with main
- [ ] This PR introduces breaking changes (if yes, fill out details below)
- [x] If this PR changes documentation, I have built and previewed it locally with `jb build docs`
- [ ] No critical issues raised by AI reviewers (`/gemini review`)
**Breaking Change Details (if applicable):**
N/A
## Additional Context
Dataset requires ~500MB download on first use. Added comprehensive test suite
covering all 12,500 problems with >95% reward function accuracy.
Files changed:
- `src/dataset/math.py`: New MathDataset class
- `src/scoring/math_scoring.py`: Symbolic math scoring function
- `examples/math_training.py`: Training script
- `docs/datasets/math.md`: Dataset documentation
- `tests/test_math_dataset.py`: Unit tests
Changes: Fix memory leak in ComputeEngine
PR Title:
fix(engine): resolve memory leak in ComputeEngine rollout
PR Description:
## Description
Fix memory leak during ComputeEngine rollout phase by clearing cached activations
after each batch and moving tensors to CPU before deletion. Reduces memory usage
by ~2GB per rollout iteration.
## Related Issue
Fixes #872
## Type of Change
- [x] Bug fix (non-breaking change that fixes an issue)
- [ ] New feature (non-breaking change that adds functionality)
- [ ] Breaking change (fix or feature that would cause existing functionality to not work as expected)
- [ ] Documentation update
- [ ] Code refactoring (no functional changes)
- [ ] Performance improvement
- [ ] Test coverage improvement
## Checklist
- [x] I have read the [Contributing Guide](../CONTRIBUTING.md)
- [x] I have run formatting tools (pre-commit or manual)
- [x] I have run relevant unit tests and they pass
- [x] I have added tests for new functionality
- [ ] I have updated documentation if needed
- [x] My branch is up to date with main
- [ ] This PR introduces breaking changes (if yes, fill out details below)
- [ ] If this PR changes documentation, I have built and previewed it locally with `jb build docs`
- [ ] No critical issues raised by AI reviewers (`/gemini review`)
**Breaking Change Details (if applicable):**
N/A
## Additional Context
Tested with 100 rollout iterations without OOM. Memory usage stable at 8GB
(previously would grow to 10GB+). Output correctness validated unchanged.
Backported to v0.5.x branch.
Files changed:
- `src/engine/compute.py:234`: Add explicit cache clearing
- `src/engine/compute.py:456`: Move tensor to CPU before deletion
- `tests/test_compute_memory.py`: Add memory leak regression test
Changes: Refactor reward API for better extensibility
PR Title:
refactor(reward): simplify reward function interface
PR Description:
## Description
Simplify reward function API from 4 methods to 2 by consolidating compute and
compute_batch into a single batched interface. Improves type hints and
documentation. All existing reward functions updated.
## Related Issue
Fixes #901
## Type of Change
- [ ] Bug fix (non-breaking change that fixes an issue)
- [ ] New feature (non-breaking change that adds functionality)
- [x] Breaking change (fix or feature that would cause existing functionality to not work as expected)
- [ ] Documentation update
- [ ] Code refactoring (no functional changes)
- [ ] Performance improvement
- [ ] Test coverage improvement
## Checklist
- [x] I have read the [Contributing Guide](../CONTRIBUTING.md)
- [x] I have run formatting tools (pre-commit or manual)
- [x] I have run relevant unit tests and they pass
- [ ] I have added tests for new functionality
- [x] I have updated documentation if needed
- [x] My branch is up to date with main
- [x] This PR introduces breaking changes (if yes, fill out details below)
- [x] If this PR changes documentation, I have built and previewed it locally with `jb build docs`
- [ ] No critical issues raised by AI reviewers (`/gemini review`)
**Breaking Change Details (if applicable):**
Old `compute_batch` method is deprecated and will be removed in v0.7.0.
See migration guide in `docs/migration/reward_api.md` for details.
## Additional Context
All existing tests pass. Performance unchanged at 10k rewards/sec. Backward
compatibility warnings added for deprecated methods.
Files changed:
- `src/api/scoring_api.py:12`: Consolidate compute/compute_batch
- `src/scoring/math_scoring.py`: Update to new API
- `src/scoring/code_scoring.py`: Update to new API
- `src/scoring/geometry_scoring.py`: Update to new API
- `docs/customization/reward.md`: Update documentation
- `docs/migration/reward_api.md`: Migration guide
- `examples/custom_reward.py`: Update example
If rebase fails:
git rebase --abortIf squash/commit fails:
git statusgit diff --cachedIf force push fails:
gh auth statusIf gh pr create or gh pr edit fails:
gh pr viewgh auth statusBefore Starting:
git branch backup/$(git branch --show-current)-$(date +%s)Before Rebase:
Before Squash:
Before Force Push:
Before PR Creation/Update:
Capture a multi-step workflow into a timestamped pipeline memory after trial-and-error sessions. The core output is: (1) the final working commands saved as executable scripts (not bare shell commands), and (2) a structured markdown document separating the clean reproducible pipeline from the detours and pitfalls. Timestamped snapshots live in pipeline_memory/; mature pipelines can be promoted to PIPELINE.md and auto-loaded. Fully environment-agnostic — works for any project, any toolset, any domain. Use when the user finishes a multi-step task, says "保存工作流记忆", "save pipeline memory", "记录一下当前进展", or "/save-pipeline-memory". Takes an optional folder path.
Run Claude Code commands (including /insights, /doctor, custom prompts) via system crontab in non-interactive mode. Use when: (1) setting up daily/weekly automated Claude Code tasks, (2) scheduling reports or analysis via cron, (3) running Claude Code with third-party API backends (DeepSeek, Qwen, etc.) in headless environments, (4) "set up a daily report", "automate this in cron", "schedule insights". Covers: cron PATH setup, third-party API env vars for non-interactive mode, nvm/node auto-discovery, and wechat-reminder integration for notification delivery.
Use when the user wants to *learn* or *understand* a technical concept (an algorithm, a math derivation, an ML architecture, a systems internal) rather than just get a one-shot answer — triggers include "explain X", "teach me X", "help me understand X", or being stuck on a concept while reading a paper or code. Probe the user's level with a few questions FIRST, then teach interactively through a runnable Jupyter notebook with LaTeX derivations and small experiments.
Claudeception is a continuous learning system that extracts reusable knowledge from work sessions. Triggers: (1) /claudeception command to review session learnings, (2) "save this as a skill" or "extract a skill from this", (3) "what did we learn?", (4) After any task involving non-obvious debugging, workarounds, or trial-and-error discovery. Creates new Claude Code skills when valuable, reusable knowledge is identified.
Record a debugging session's findings into a timestamped markdown file under debug_experience/. Captures problem, root cause, solution, and key learnings in a structured, reusable format. Use when: you've just resolved a non-obvious bug, found an undocumented edge case, encountered an issue that took multiple attempts to fix, or when you say things like "保存调试经验", "save debug experience", "记录这次调试", "/save-debug-experience". Takes an optional folder path as argument.
MCP Notion工具使用指南，包含常见问题解决方案和最佳实践。使用当： (1) 访问Notion数据库view URL出现"URL type view not currently supported"错误， (2) 需要获取数据库schema和表结构信息， (3) 查询数据库中的条目内容， (4) 创建页面时MULTI_SELECT字段值不存在导致失败， (5) 需要更新数据库schema添加新选项， (6) 开发需要集成Notion数据的自动化工作流， (7) query_data_sources/query-database-view返回Business Plan要求错误， (8) 需要在无Business Plan的情况下枚举数据库所有条目。