Babysitter research-first-dev

Research-first development methodology that investigates existing solutions, brainstorms alternatives, and evaluates trade-offs before any implementation begins.

install
source · Clone the upstream repo
git clone https://github.com/a5c-ai/babysitter
Claude Code · Install into ~/.claude/skills/
T=$(mktemp -d) && git clone --depth=1 https://github.com/a5c-ai/babysitter "$T" && mkdir -p ~/.claude/skills && cp -r "$T/library/methodologies/everything-claude-code/skills/research-first-dev" ~/.claude/skills/a5c-ai-babysitter-research-first-dev && rm -rf "$T"
manifest: library/methodologies/everything-claude-code/skills/research-first-dev/SKILL.md
source content

Research-First Development

Overview

Research-first development methodology adapted from the Everything Claude Code project. Mandates investigation of existing solutions and alternatives before writing any code.

Research Process

1. Problem Analysis

  • 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)