csp-agentic-engineeringlisted
Install: claude install-skill maythyai/code-skills-package
# Agentic Engineering
Use this skill for engineering workflows where AI agents perform most implementation work and humans enforce quality and risk controls.
## Operating Principles
1. Define completion criteria before execution.
2. Decompose work into agent-sized units.
3. Route model tiers by task complexity.
4. Measure with evals and regression checks.
## Eval-First Loop
1. Define capability eval and regression eval.
2. Run baseline and capture failure signatures.
3. Execute implementation.
4. Re-run evals and compare deltas.
**Example workflow:**
```
1. Write test that captures desired behavior (eval)
2. Run test → capture baseline failures
3. Implement feature
4. Re-run test → verify improvements
5. Check for regressions in other tests
```
## Task Decomposition
Apply the 15-minute unit rule:
- Each unit should be independently verifiable
- Each unit should have a single dominant risk
- Each unit should expose a clear done condition
**Good decomposition:**
```
Task: Add user authentication
├─ Unit 1: Add password hashing (15 min, security risk)
├─ Unit 2: Create login endpoint (15 min, API contract risk)
├─ Unit 3: Add session management (15 min, state risk)
└─ Unit 4: Protect routes with middleware (15 min, auth logic risk)
```
**Bad decomposition:**
```
Task: Add user authentication (2 hours, multiple risks)
```
## Model Routing
Choose model tier based on task complexity:
- **Haiku**: Classification, boilerplate transforms, narrow edits
- Example: Rename