development-workflow
Development lifecycle methodologies: TDD, debugging, code review, simplification, and spike prototyping.
- License 许可
- MIT
- 所属仓库
- S3YED/appie-kit
- 最近更新
- 2026-08-27
- Stars
- ★ 14
- Forks
- 3
01 前言 Front Matter
- name
- development-workflow
- author
- Hermes Agent
- license
- MIT
- version
- 1.0.0
- metadata
- { "hermes": { "tags": [ "development", "methodology", "tdd", "debugging", "code-review", "spike", "simplification", "workflow" ], "related_skills": [ "plan", "subagent-driven-development", "external-coding-agents" ] } }
- platforms
- [ "linux", "macos", "windows" ]
- description
- Development lifecycle methodologies: TDD, debugging, code review, simplification, and spike prototyping.
03 SKILL.md 正文
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
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