wshobson/commands — Prompt Excerpts
Excerpt 1: feature-development.md (workflows/)
Technique: Explicit Task-tool invocation with named subagent_type parameters — prompt chaining pattern where each agent receives prior agent's output as injected context.
---
model: claude-opus-4-1
---
Implement a new feature using specialized agents with explicit Task tool invocations:
[Extended thinking: This workflow orchestrates multiple specialized agents to implement a complete feature from design to deployment. Each agent receives context from previous agents to ensure coherent implementation.]
## Traditional Development Steps
1. **Backend Architecture Design**
- Use Task tool with subagent_type="backend-architect"
- Prompt: "Design RESTful API and data model for: $ARGUMENTS. Include endpoint definitions, database schema, and service boundaries."
- Save the API design and schema for next agents
2. **Frontend Implementation**
- Use Task tool with subagent_type="frontend-developer"
- Prompt: "Create UI components for: $ARGUMENTS. Use the API design from backend-architect: [include API endpoints and data models from step 1]"
- Ensure UI matches the backend API contract
3. **Test Coverage**
- Use Task tool with subagent_type="test-automator"
- Prompt: "Write comprehensive tests for: $ARGUMENTS. Cover both backend API endpoints: [from step 1] and frontend components: [from step 2]"
4. **Production Deployment**
- Use Task tool with subagent_type="deployment-engineer"
- Prompt: "Prepare production deployment for: $ARGUMENTS..."
Analysis: This is explicit prompt-chaining by injection: [include API endpoints and data models from step 1] is an instruction to Claude to literally insert prior output as part of the next agent's prompt. The model: claude-opus-4-1 frontmatter pins the orchestrator to Opus.
Technique: Decision matrix + tool selection guide embedded in prompt (structured knowledge encoding)
---
model: claude-sonnet-4-0
---
# Security Scan and Vulnerability Assessment
You are a security expert specializing in application security, vulnerability assessment, and secure coding practices...
### 1. Security Scanning Tool Selection
Choose appropriate security scanning tools based on your technology stack:
**Tool Selection Matrix**
```python
security_tools = {
'python': {
'sast': {
'bandit': {
'strengths': ['Built for Python', 'Fast', 'Good defaults', 'AST-based'],
'command': 'bandit -r . -f json -o bandit-report.json',
},
'semgrep': {
'strengths': ['Multi-language', 'Custom rules', 'Low false positives'],
'command': 'semgrep --config=auto --json --output=semgrep-report.json',
}
},
'dependency_scan': {
'safety': {
'command': 'safety check --json --output safety-report.json',
}
}
}
**Analysis**: Python dict literal embedded as knowledge schema within a markdown prompt — avoids prose repetition by encoding tool options in a structured format Claude can navigate algorithmically. Model pinned to Sonnet (not Opus) — appropriate for a scan task vs architectural reasoning.