Development workflow
Development lifecycle methodologies: TDD, debugging, code review, simplification, and spike prototyping.From its SKILL.md
npx -y skills add S3YED/appie-kit --skill development-workflowAssembled from the repository path, not quoted from the project. Check it against their README if it does not work.
One thing to look at
- 6 stars6 stars. Stars are a popularity signal and not a quality one, but at this level it is likely that nobody has read this closely except its author, and you would be relying on your own review.
What its file declares
Copied from the file, not written here
The file declares its own license as MIT. That is the author’s claim about this one file, and it is not the same thing as the license GitHub reports for the repository, which is listed with the other numbers below.
SKILL.md
3.6 KB, 749 tokens by cl100k_base, as published. Nobody here has run it
Development Workflow Methodologies
A collection of proven development workflows covering the full lifecycle: from exploration (spikes) through implementation (TDD), verification (code review), cleanup (simplify), and debugging (systematic debugging).
Workflow Sequence
Spike ──→ TDD ──→ Code Review ──→ Simplify ──→ Deploy
│ ↑
└──→ Bug Found? ──→ Systematic Debugging ──┘
Each phase has an independent skill reference with exact commands, iron laws, and anti-pattern tables:
1. Spike — Throwaway Experiments
When to use: Validating feasibility before committing to a real build.
- references/spike.md for the full workflow
2. Test-Driven Development (TDD)
When to use: ANY code change — features, bug fixes, refactoring.
- RED: Write failing test first, watch it fail
- GREEN: Write minimal code to pass
- REFACTOR: Clean up while keeping tests green
- references/test-driven-development.md for the full TDD cycle
3. Pre-Commit Code Review
When to use: Before every commit after 2+ file edits.
- Static security scan (secrets, injections, unsafe patterns)
- Baseline-aware quality gates (tests, linting)
- Independent reviewer subagent (fail-closed JSON verdict)
- Auto-fix loop (max 2 cycles)
- references/github-code-review.md for the full pipeline
4. Simplify Code — Parallel Cleanup
When to use: When the user says "simplify" or "clean up my changes".
- Three parallel reviewers: Reuse, Quality, Efficiency
- Aggregates findings, applies fixes, verifies with tests
- references/simplify-code.md for the full process
5. Systematic Debugging
When to use: ANY technical bug or test failure.
- 4 phases: Root Cause Investigation → Pattern Analysis → Hypothesis Testing → Implementation
- The Rule of Three: stop after 3 failed fixes, question the architecture
- references/systematic-debugging.md for the full methodology
Common Patterns Across All Workflows
The Iron Law
Each methodology has a non-negotiable first principle:
- TDD: "NO PRODUCTION CODE WITHOUT A FAILING TEST FIRST"
- Debugging: "NO FIXES WITHOUT ROOT CAUSE INVESTIGATION FIRST"
- Code Review: "No agent should verify its own work"
Rationalizations vs Reality
All five skills include a table of common excuses and their counters.
Red Flags
Each skill lists patterns that indicate you're skipping the process.
When NOT to Use Each
- Spike: Skip when the answer is already known or the work is production path
- TDD: Skip only for throwaway prototypes, generated code, or config files (ask the user first)
- Code Review: Skip for docs-only or config-only changes
- Simplify: Skip unless the user explicitly asks (it's token-heavy)
- Debugging: Never skip — even simple bugs have root causes
Hermes Tool Integration
All workflows use the same Hermes tool primitives:
terminal("git diff") # Get changes
terminal("pytest ...") # Run tests
terminal("ruff check .") # Lint
terminal("git log --oneline") # Check history
search_files("error_string") # Find errors
read_file("src/problematic.py") # Read code
What ships with it
Read from the repository
Just SKILL.md. No reference files, no scripts.