Context engineering

Skill a5c-ai/babysitter/library/methodologies/everything-claude-code/skills/context-engineering

Babysitter enforces obedience on agentic workforces and enables them to manage extremely complex tasks and workflows through deterministic, hallucination-free self-orchestration

Install

npx -y skills add a5c-ai/babysitter --skill context-engineering

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What its author says it does

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Dynamic context injection, mode switching (dev/review/research), selective loading, and strategic compaction for token optimization.

SKILL.md

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Load: architecture docs, active code files, test files, recent changes
Skip: historical discussions, completed milestones, research notes
Priority: implementation speed

Review Mode

Load: code diff, coding standards, security rules, test coverage
Skip: architecture docs, planning notes, research
Priority: thoroughness and accuracy

Research Mode

Load: requirements, existing patterns, external research, alternatives
Skip: implementation details, test files, CI configs
Priority: breadth of information

Dynamic Injection

Detect project context automatically (language, framework, tools)
Load relevant skills based on detected context
Inject domain-specific patterns and conventions
Adjust tool allowlists per context mode

Selective Loading

Load only files relevant to the current task
Use glob patterns to scope file reading
Prioritize recently modified files
Skip binary files and generated code

Strategic Compaction

Monitor context token usage
Suggest compression for resolved/completed items
Archive to memory files (activeContext, patterns, progress)
Pre-compaction state preservation
Automated compaction triggers at token thresholds

Cross-Platform Detection

Package manager: npm (package-lock.json), pnpm (pnpm-lock.yaml), yarn (yarn.lock), bun (bun.lockb)
Language: TypeScript (tsconfig.json), Go (go.mod), Python (pyproject.toml), Java (pom.xml)
Test runner: vitest, jest, pytest, go test
CI/CD: GitHub Actions, Dockerfile, docker-compose

When to Use

Session initialization (detect context)
Before each phase (inject relevant context)
Token budget warnings (strategic compaction)
Mode transitions (dev to review to research)

Agents Used

Used by all agents indirectly through context detection
context-engineering agent for explicit compaction analysis