coding-effectively
npx machina-cli add skill ed3dai/ed3d-plugins/coding-effectively --openclawCoding Effectively
Required Sub-Skills
ALWAYS REQUIRED:
howto-functional-vs-imperative- Separate pure logic from side effectsdefense-in-depth- Validate at every layer data passes through
CONDITIONAL: Use these sub-skills when applicable:
howto-code-in-typescript- TypeScript codehowto-develop-with-postgres- PostgreSQL database codeprogramming-in-react- React frontend codewriting-good-tests- Writing or reviewing testsproperty-based-testing- Tests for serialization, validation, normalization, pure functions
Property-Driven Design
When designing features, think about properties upfront. This surfaces design gaps early.
Discovery questions:
| Question | Property Type | Example |
|---|---|---|
| Does it have an inverse operation? | Roundtrip | decode(encode(x)) == x |
| Is applying it twice the same as once? | Idempotence | f(f(x)) == f(x) |
| What quantities are preserved? | Invariants | Length, sum, count unchanged |
| Is order of arguments irrelevant? | Commutativity | f(a, b) == f(b, a) |
| Can operations be regrouped? | Associativity | f(f(a,b), c) == f(a, f(b,c)) |
| Is there a neutral element? | Identity | f(x, 0) == x |
| Is there a reference implementation? | Oracle | new(x) == old(x) |
| Can output be easily verified? | Easy to verify | is_sorted(sort(x)) |
Common design questions these reveal:
- "What about deleted/deactivated entities?"
- "Case-sensitive or not?"
- "Stable sort or not? Tie-breaking rules?"
- "Which algorithm? Configurable?"
Surface these during design, not during debugging.
Core Engineering Principles
Correctness Over Convenience
Model the full error space. No shortcuts.
- Handle all edge cases: race conditions, timing issues, partial failures
- Use the type system to encode correctness constraints
- Prefer compile-time guarantees over runtime checks where possible
- When uncertain, explore and iterate rather than assume
Don't:
- Simplify error handling to save time
- Ignore edge cases because "they probably won't happen"
- Use
anyor equivalent to bypass type checking
Error Handling Philosophy
Two-tier model:
- User-facing errors: Semantic exit codes, rich diagnostics, actionable messages
- Internal errors: Programming errors that may panic or use internal types
Error message format: Lowercase sentence fragments for "failed to {message}".
Good: failed to connect to database: connection refused
Bad: Failed to Connect to Database: Connection Refused
Good: invalid configuration: missing required field 'apiKey'
Bad: Invalid Configuration: Missing Required Field 'apiKey'
Lowercase fragments compose naturally: "operation failed: " + error.message reads correctly.
Pragmatic Incrementalism
- Prefer specific, composable logic over abstract frameworks
- Evolve design incrementally rather than perfect upfront architecture
- Don't build for hypothetical future requirements
- Document design decisions and trade-offs when making non-obvious choices
The rule of three applies to abstraction: Don't abstract until you've seen the pattern three times. Three similar lines of code is better than a premature abstraction.
File Organization
Descriptive File Names Over Catch-All Files
Name files by what they contain, not by generic categories.
Don't create:
utils.ts- Becomes a dumping ground for unrelated functionshelpers.ts- Same problemcommon.ts- What isn't common?misc.ts- Actively unhelpful
Do create:
string-formatting.ts- String manipulation utilitiesdate-arithmetic.ts- Date calculationsapi-error-handling.ts- API error utilitiesuser-validation.ts- User input validation
Why this matters:
- Discoverability: Developers find code by scanning file names
- Cohesion: Related code stays together
- Prevents bloat: Hard to add unrelated code to
string-formatting.ts - Import clarity:
import { formatDate } from './date-arithmetic'is self-documenting
When you're tempted to create utils.ts: Stop. Ask what the functions have in common. Name the file after that commonality.
Module Organization
- Keep module boundaries strict with restricted visibility
- Platform-specific code in separate files:
unix.ts,windows.ts,posix.ts - Use conditional compilation or runtime checks for platform branching
- Test helpers in dedicated modules/files, not mixed with production code
Cross-Platform Principles
Use OS-Native Logic
Don't emulate Unix on Windows or vice versa. Use each platform's native patterns.
Bad: Trying to make Windows paths behave like Unix paths everywhere.
Good: Accept platform differences, handle them explicitly.
// Platform-specific behavior
if (process.platform === 'win32') {
// Windows-native approach
} else {
// POSIX approach
}
Platform-Specific Files
When platform differences are significant, use separate files:
process-spawn.ts // Shared interface and logic
process-spawn-unix.ts // Unix-specific implementation
process-spawn-windows.ts // Windows-specific implementation
Document Platform Differences
When behavior differs by platform, document it in comments:
// On Windows, this returns CRLF line endings.
// On Unix, this returns LF line endings.
// Callers should normalize if consistent output is needed.
function readTextFile(path: string): string { ... }
Test on All Target Platforms
Don't assume Unix behavior works on Windows. Test explicitly:
- CI should run on all supported platforms
- Platform-specific code paths need platform-specific tests
- Document which platforms are supported
Common Mistakes
| Mistake | Reality | Fix |
|---|---|---|
| "Just put it in utils for now" | utils.ts becomes 2000 lines of unrelated code | Name files by purpose from the start |
| "Edge cases are rare" | Edge cases cause production incidents | Handle them. Model the full error space. |
| "We might need this abstraction later" | Premature abstraction is harder to remove than add | Wait for the third use case |
| "It works on my Mac" | It may not work on Windows or Linux | Test on target platforms |
| "The type system is too strict" | Strictness catches bugs at compile time | Fix the type error, don't bypass it |
Red Flags
Stop and refactor when you see:
- A
utils.tsorhelpers.tsfile growing beyond 200 lines - Error handling that swallows errors or uses generic messages
- Platform-specific code mixed with cross-platform code
- Abstractions created for single use cases
- Type assertions (
as any) to bypass the type system - Code that "works on my machine" but isn't tested cross-platform
Source
git clone https://github.com/ed3dai/ed3d-plugins/blob/main/plugins/ed3d-house-style/skills/coding-effectively/SKILL.mdView on GitHub Overview
Coding Effectively guides you to write and refactor code with attention to how logic is organized, where side effects live, and how data moves through systems. It emphasizes context-specific sub-skills (TypeScript, React, PostgreSQL, testing) and a property-driven mindset to surface design gaps early.
How This Skill Works
Begin by separating pure logic from side effects (functional vs imperative). Then enforce defense-in-depth by validating data at every layer and encoding correctness in the type system and tests. The approach favors pragmatic incrementalism, clear file organization, and applying surface design questions to guide decisions.
When to Use It
- Starting a new feature by separating pure logic from side effects
- Refactoring to add layered data validation across services
- Coding in TypeScript projects with strict typing
- Developing PostgreSQL database code with correctness in mind
- Writing or reviewing tests, including property-based testing where relevant
Quick Start
- Step 1: Identify pure logic vs side effects and separate them in your module
- Step 2: Add defensive checks and propagate typed interfaces across layers
- Step 3: Apply relevant sub-skills (howto-code-in-typescript, howto-develop-with-postgres, programming-in-react, writing-good-tests, property-based-testing) and write property-driven tests
Best Practices
- Separate pure logic from side effects early to keep code testable
- Validate and guard data at every boundary (defense-in-depth)
- Encode constraints in the type system and write clear error messages
- Organize files by content rather than generic categories
- Design with properties in mind and test invariants and roundtrips
Example Use Cases
- Decode(encode(x)) == x demonstrates invertibility
- f(f(x)) == f(x) shows idempotence in an operation
- Preserved invariants like length or sum in a data pipeline
- Commutativity: f(a, b) == f(b, a) in a reorder-safe function
- Using an identity element: f(x, 0) == x in a reduce-style operation