devtu-github▌
mims-harvard/tooluniverse · updated Apr 8, 2026
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Safely push ToolUniverse code to GitHub by enforcing pre-push cleanup, pre-commit hooks, and test validation.
DevTU GitHub Workflow
Safely push ToolUniverse code to GitHub by enforcing pre-push cleanup, pre-commit hooks, and test validation.
Instructions
When the user wants to push code, fix CI, or prepare a commit, follow this workflow:
Phase 1: Pre-Push Cleanup
- Move temp files out of root - session docs and ad-hoc test scripts must NOT be pushed:
# Move session markdown files to temp_docs_and_tests/
for f in $(ls *.md 2>/dev/null | grep -v README.md | grep -v CHANGELOG.md | grep -v LICENSE.md); do
mv "$f" temp_docs_and_tests/
done
# Move root-level test scripts to temp_docs_and_tests/
for f in $(ls test_*.py 2>/dev/null); do
mv "$f" temp_docs_and_tests/
done
- Verify nothing unwanted is staged:
git status --short
Red flags - these should NEVER be staged:
*_SUMMARY.md,*_REPORT.md,SESSION_*.mdin roottest_*.pyin root (these are ad-hoc scripts, not real tests).envor credential filestemp_docs_and_tests/contents
Phase 2: Activate Pre-Commit Hooks
- Ensure pre-commit is installed and active:
pre-commit install
This enables automatic checks on every git commit:
ruff check --fix- Python linting with auto-fixruff format- Code formatting- YAML/TOML validation
- Trailing whitespace removal
- End of file fixes
- Verify hooks are active:
ls -la .git/hooks/pre-commit
Phase 3: Run Tests
- Run the full test suite locally:
python -m pytest tests/ -x --tb=short -q
- If tests fail, diagnose using the error patterns below and fix before proceeding.
Phase 4: Commit and Push
- Stage only specific files (never use
git add .orgit add -A):
git add src/tooluniverse/specific_file.py tests/specific_test.py
- Commit (pre-commit hooks run automatically):
git commit -m "Clear, descriptive message"
- Rebase onto latest main BEFORE pushing (CRITICAL — prevents PR conflicts):
git fetch origin
git stash # stash any uncommitted work
git rebase origin/main
git stash pop # restore uncommitted work
If rebase conflicts arise, resolve them (keep our newer changes), then:
git add <conflicted-file>
git rebase --continue
- Push (force-with-lease after a rebase):
git push --force-with-lease origin <branch-name>
After pushing, verify the PR is conflict-free:
gh pr view <PR-number> --json mergeable,mergeStateStatus
# Must show: "mergeable":"MERGEABLE"
Files That Must NEVER Be Pushed
Temp Session Documents (Root-Level .md)
These are session notes created during development. Move to temp_docs_and_tests/ before committing:
| Pattern | Example |
|---|---|
*_SUMMARY.md |
API_DISCOVERY_SESSION_SUMMARY.md |
*_REPORT.md |
SKILL_TESTING_REPORT.md, TOOLUNIVERSE_BUG_REPORT.md |
SESSION_*.md |
SESSION_2026_02_13.md |
IMPLEMENTATION_*.md |
IMPLEMENTATION_COMPLETE.md |
BUG_ANALYSIS_*.md |
BUG_ANALYSIS_DETAILED.md |
FIX_*.md |
FIX_SUMMARY.md, CORRECT_FIX.md |
AGENT_*.md |
AGENT_DESIGN_UPDATES.md |
Exception: README.md, CHANGELOG.md, LICENSE.md are real docs and MUST stay.
Root-Level Test Scripts
Ad-hoc test scripts like test_*.py in root are NOT part of the test suite (tests/ directory is). Move them to temp_docs_and_tests/:
| File | Purpose |
|---|---|
test_clear_tools.py |
One-off tool cleanup test |
test_finemapping_tools.py |
Ad-hoc tool validation |
test_metabolomics_tools.py |
Ad-hoc tool validation |
test_original_bug.py |
Bug reproduction |
test_pathway_tools.py |
Ad-hoc tool validation |
test_protein_interaction_skill.py |
Skill test |
test_reload_fix.py |
Bug reproduction |
test_round10_tools.py |
Ad-hoc tool validation |
Other Excluded Files
.env- Environment variables with secretstemp_docs_and_tests/- Already in .gitignore.claude/- Claude Code configuration__pycache__/,*.pyc- Python bytecode.DS_Store- macOS metadata
Common Test Failure Patterns
Pattern 1: KeyError: 'role'
Symptom: KeyError: 'role' when accessing message dicts
Fix: Add return_message=True to tu.run() and use .get():
messages = tu.run(calls, use_cache=True, return_message=True)
if msg.get("role") == "tool":
Pattern 2: Mock Not Subscriptable
Symptom: TypeError: 'Mock' object is not subscriptable
Fix: Use real dicts for all_tool_dict and add _get_tool_instance:
mock_tu.all_tool_dict = {"Tool": mock_tool}
mock_tu._get_tool_instance = lambda name, cache=True: mock_tu.all_tool_dict.get(name)
Pattern 3: Linting Errors (F841, E731)
Fix F841 (unused variable): Use _ prefix or _ = func()
Fix E731 (lambda assignment): Replace with def
Pattern 4: Temp Files Tracked by Git
Symptom: git status shows temp files as modified/staged
Fix:
git rm -r --cached temp_docs_and_tests/
git rm --cached API_DISCOVERY_SESSION_SUMMARY.md
git commit -m "Remove temp files from tracking"
Pre-Commit Hook Configuration
The project uses .pre-commit-config.yaml:
repos:
- repo: https://github.com/pre-commit/pre-commit-hooks
hooks: [end-of-file-fixer, trailing-whitespace, check-yaml, check-toml]
- repo: https://github.com/astral-sh/ruff-pre-commit
hooks: [ruff-check --fix, ruff-format]
Scope: Only files matching ^(ToolUniverse/)?src/tooluniverse/
Quick Reference
| Task | Command |
|---|---|
| Activate hooks | pre-commit install |
| Run all tests | pytest tests/ -x --tb=short -q |
| Run specific test | pytest tests/path/test.py::Class::method -xvs |
| Check staged files | git status --short |
| Unstage a file | git restore --staged <file> |
| Remove from tracking | git rm --cached <file> |
| Move temp files | See Phase 1 commands |
| Run hooks manually | pre-commit run --all-files |
Pre-Push Checklist
Before every push, verify:
- Temp markdown files moved from root to
temp_docs_and_tests/ - Root-level
test_*.pyscripts moved totemp_docs_and_tests/ - Pre-commit hooks installed (
pre-commit install) - All tests pass locally (
pytest tests/ -x) - No linting errors
- Only relevant files staged (no
.env, no temp files) - Commit message is clear and descriptive
- Correct branch selected
Git Commit Guidelines
- Never include AI attribution in commits
- Never commit session documentation markdown files
- Use
git add <specific-files>instead ofgit add . - Write clean, professional commit messages
- One logical change per commit
How to use devtu-github on Cursor
AI-first code editor with Composer
Prerequisites
Before installing skills in Cursor, ensure your development environment meets these requirements:
- ›Cursor installed and configured on your development machine
- ›Node.js version 16.0+ with npm package manager (verify with
node --version) - ›Active project directory or workspace where you want to add devtu-github
Execute installation command
Execute the skills CLI command in your project's root directory to begin installation:
The skills CLI fetches devtu-github from GitHub repository mims-harvard/tooluniverse and configures it for Cursor.
Select Cursor when prompted
The CLI will show a list of available agents. Use arrow keys to navigate and space to select Cursor:
Verify installation
Confirm successful installation by checking the skill directory location:
Reload or restart Cursor to activate devtu-github. Access the skill through slash commands (e.g., /devtu-github) or your agent's skill management interface.
Security & Verification Notice
We perform automated surface-level scans (Gen AI Scanner, Socket, Snyk) during installation. These checks detect common vulnerabilities but do not guarantee complete security. Always review skill source code and verify the publisher's reputation before production use.
Skills execute code in your development environment. Always verify the publisher's identity, review recent commits, and test in isolated environments before production deployment.
List & Monetize Your Skill
Submit your Claude Code skill and start earning
Use Cases▌
User Story & Requirements Generation
Create detailed user stories, acceptance criteria, and feature specs
Example
Generate user stories for 'password reset feature' with acceptance criteria, edge cases, and test scenarios
Reduce spec writing time by 50%, ensure comprehensive coverage
Competitive Analysis
Research competitors, compare features, identify gaps
Example
Analyze 5 competitor products, create feature comparison matrix, suggest differentiation opportunities
Complete competitive research in 2 hours instead of 2 days
Roadmap Prioritization
Evaluate features using frameworks (RICE, ICE, Kano) and create prioritized backlogs
Example
Score 20 feature ideas using RICE framework, generate prioritized roadmap with rationale
Make data-driven prioritization decisions faster
Stakeholder Communication
Draft PRDs, status updates, and stakeholder presentations
Example
Create executive summary of Q3 roadmap, monthly progress report, feature launch announcement
Save 3-5 hours/week on communication overhead
Implementation Guide▌
Prerequisites
- ›Claude Desktop or compatible AI client
- ›Access to product documentation and roadmap tools (Jira, Notion, etc.)
- ›Understanding of product management frameworks (RICE, Jobs-to-be-Done, etc.)
- ›Stakeholder contact information and communication channels
Time Estimate
30-60 minutes to see productivity improvements
Installation Steps
- 1.Install product management skill
- 2.Start with user story generation for known feature
- 3.Progress to competitive analysis: research 2-3 competitors
- 4.Use for roadmap prioritization: apply RICE/ICE scoring
- 5.Draft stakeholder communications and refine based on feedback
- 6.Build template library for recurring PM tasks
- 7.Share effective prompts with product team
Common Pitfalls
- ⚠Not validating competitive research—verify facts before sharing
- ⚠Accepting user stories without involving engineering team
- ⚠Over-relying on frameworks without qualitative judgment
- ⚠Not customizing outputs to company culture and communication style
- ⚠Skipping stakeholder validation of generated requirements
Best Practices▌
✓ Do
- +Validate research and competitive analysis with real data
- +Collaborate with engineering when generating technical requirements
- +Customize frameworks and templates to your company context
- +Use skill for first drafts, refine with stakeholder input
- +Document successful prompt patterns for PM tasks
- +Combine AI efficiency with human judgment and intuition
✗ Don't
- −Don't publish competitive analysis without fact-checking
- −Don't finalize user stories without engineering review
- −Don't make prioritization decisions solely on AI scoring
- −Don't skip customer validation of generated requirements
- −Don't ignore company-specific context and culture
💡 Pro Tips
- ★Provide context: company goals, constraints, customer feedback
- ★Ask for alternatives: 'Show 3 ways to prioritize this roadmap'
- ★Request stakeholder-specific formatting: 'Executive summary vs. engineering spec'
- ★Use skill for 70% generation + 30% customization to company needs
When to Use This▌
✓ Use When
Use for user story writing, competitive research, roadmap prioritization, stakeholder communication, and PRD drafting. Best for reducing repetitive documentation and research work.
✗ Avoid When
Avoid for strategic product vision (requires deep customer empathy), pricing decisions (needs market and financial expertise), or when face-to-face customer discovery is more valuable than speed.
Learning Path▌
- 1Basic: user stories, feature specs, status updates
- 2Intermediate: competitive analysis, prioritization frameworks, PRDs
- 3Advanced: product strategy, go-to-market planning, OKR setting
- 4Expert: product vision, market positioning, business model innovation
Discussion
Product Hunt–style comments (not star reviews)- No comments yet — start the thread.
Ratings
4.6★★★★★28 reviews- ★★★★★Anika Ghosh· Dec 28, 2024
devtu-github fits our agent workflows well — practical, well scoped, and easy to wire into existing repos.
- ★★★★★Nikhil Srinivasan· Dec 12, 2024
devtu-github has been reliable in day-to-day use. Documentation quality is above average for community skills.
- ★★★★★Naina Huang· Nov 19, 2024
I recommend devtu-github for anyone iterating fast on agent tooling; clear intent and a small, reviewable surface area.
- ★★★★★Charlotte Gupta· Nov 3, 2024
Solid pick for teams standardizing on skills: devtu-github is focused, and the summary matches what you get after install.
- ★★★★★Charlotte Tandon· Oct 22, 2024
I recommend devtu-github for anyone iterating fast on agent tooling; clear intent and a small, reviewable surface area.
- ★★★★★Li Anderson· Oct 10, 2024
Solid pick for teams standardizing on skills: devtu-github is focused, and the summary matches what you get after install.
- ★★★★★Sakshi Patil· Sep 25, 2024
devtu-github reduced setup friction for our internal harness; good balance of opinion and flexibility.
- ★★★★★Chaitanya Patil· Aug 16, 2024
devtu-github is among the better-maintained entries we tried; worth keeping pinned for repeat workflows.
- ★★★★★Rahul Santra· Jul 27, 2024
Keeps context tight: devtu-github is the kind of skill you can hand to a new teammate without a long onboarding doc.
- ★★★★★Piyush G· Jul 7, 2024
Useful defaults in devtu-github — fewer surprises than typical one-off scripts, and it plays nicely with `npx skills` flows.
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