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context-engineering

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

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Repository
a5c-ai/babysitter
Letzte Quellaktivität
1. Juni 2026 um 07:46
Erkannte Sprache von SKILL.md
Englisch
Sterne
1.813
Forks
111

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Lesen Sie SKILL.md und alle von SkillsMP angezeigten Begleitdateien, bevor Sie sich für eine Installation entscheiden.

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SKILL.md
Quellanweisungen · Schreibgeschützte Vorschau
name
context-engineering
description
Dynamic context injection, mode switching (dev/review/research), selective loading, and strategic compaction for token optimization.
allowed-tools
Read, Write, Edit, Bash, Grep, Glob
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"]}
- 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
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