devtu-github

mims-harvard/tooluniverse · updated Apr 8, 2026

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$npx skills add https://github.com/mims-harvard/tooluniverse --skill devtu-github
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summary

Safely push ToolUniverse code to GitHub by enforcing pre-push cleanup, pre-commit hooks, and test validation.

skill.md

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

  1. 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
  1. Verify nothing unwanted is staged:
git status --short

Red flags - these should NEVER be staged:

  • *_SUMMARY.md, *_REPORT.md, SESSION_*.md in root
  • test_*.py in root (these are ad-hoc scripts, not real tests)
  • .env or credential files
  • temp_docs_and_tests/ contents

Phase 2: Activate Pre-Commit Hooks

  1. 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-fix
  • ruff format - Code formatting
  • YAML/TOML validation
  • Trailing whitespace removal
  • End of file fixes
  1. Verify hooks are active:
ls -la .git/hooks/pre-commit

Phase 3: Run Tests

  1. Run the full test suite locally:
python -m pytest tests/ -x --tb=short -q
  1. If tests fail, diagnose using the error patterns below and fix before proceeding.

Phase 4: Commit and Push

  1. Stage only specific files (never use git add . or git add -A):
git add src/tooluniverse/specific_file.py tests/specific_test.py
  1. Commit (pre-commit hooks run automatically):
git commit -m "Clear, descriptive message"
  1. 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
  1. 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 secrets
  • temp_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_*.py scripts moved to temp_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 of git add .
  • Write clean, professional commit messages
  • One logical change per commit
how to use devtu-github

How to use devtu-github on Cursor

AI-first code editor with Composer

1

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
2

Execute installation command

Execute the skills CLI command in your project's root directory to begin installation:

$npx skills add https://github.com/mims-harvard/tooluniverse --skill devtu-github

The skills CLI fetches devtu-github from GitHub repository mims-harvard/tooluniverse and configures it for Cursor.

3

Select Cursor when prompted

The CLI will show a list of available agents. Use arrow keys to navigate and space to select Cursor:

◆ Which agents do you want to install to?
│ ── Universal (.agents/skills) ── always included ────
│ • Amp
│ • Antigravity
│ • Cline
│ • Codex
│ ●Cursor(selected)
│ • Cursor
│ • Windsurf
4

Verify installation

Confirm successful installation by checking the skill directory location:

.cursor/skills/devtu-github

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

GET_STARTED →

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. 1.Install product management skill
  2. 2.Start with user story generation for known feature
  3. 3.Progress to competitive analysis: research 2-3 competitors
  4. 4.Use for roadmap prioritization: apply RICE/ICE scoring
  5. 5.Draft stakeholder communications and refine based on feedback
  6. 6.Build template library for recurring PM tasks
  7. 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

  1. 1Basic: user stories, feature specs, status updates
  2. 2Intermediate: competitive analysis, prioritization frameworks, PRDs
  3. 3Advanced: product strategy, go-to-market planning, OKR setting
  4. 4Expert: product vision, market positioning, business model innovation

Discussion

Product Hunt–style comments (not star reviews)
  • No comments yet — start the thread.
general reviews

Ratings

4.628 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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