research-first-dev ยท diff
git:20260507.8dfdcb4 to git:20260507.9f5be95
2 added, 0 removed. Audit C to A.
---
name: research-first-dev
description: Research-first development methodology that investigates existing solutions, brainstorms alternatives, and evaluates trade-offs before any implementation begins.
allowed-tools: Read, Write, Edit, Bash, Grep, Glob, WebSearch, WebFetch
graph:
domains: [domain:software-engineering]
skillAreas: [skill-area:agentic-loops, skill-area:orchestration-loop]
workflows: [workflow:feature-development]
topics: [topic:developer-experience]
roles: [role:tech-lead, role:backend-engineer]
+ ---
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- Parse the request into specific technical requirements
- Identify the domain and relevant technology stack
- List known constraints (time, resources, compatibility)
- Define success criteria
### 2. Existing Solution Search
- Search GitHub for similar implementations
- Check package registries (npm, PyPI, crates.io, etc.)
- Review documentation for framework-specific solutions
- Identify relevant design patterns
- Check for known anti-patterns to avoid
### 3. Alternative Brainstorming
- Generate at least 3 alternative approaches
- Include a "build" option and at least one "buy/reuse" option
- Consider unconventional approaches
### 4. Trade-Off Evaluation
- Complexity: implementation effort, learning curve
- Time: development timeline, time-to-value
- Risk: failure modes, dependency risks, maintenance burden
- Scalability: growth limits, performance under load
- Score each alternative on all 4 axes
### 5. Recommendation
- Rank alternatives by composite score
- Provide clear recommendation with justification
- Include risk mitigation plan for chosen approach
- Define go/no-go criteria
## Iterative Retrieval
- Start broad, narrow based on findings
- Use confidence scoring to decide when to stop
- Maximum 3 retrieval rounds per topic
- Cache findings for reuse in subsequent phases
## When to Use
- New feature development (always)
- Architecture changes
- Technology selection
- Dependency evaluation
- Performance optimization strategy
## Agents Used
- `planner` (primary consumer)
- `architect` (architecture-specific research)