serithemage

References Serverless OpenClaw architecture. Covers network design, CDK stack structure, DynamoDB data model, API protocols, and container design.

References cold start optimization history and techniques. Covers Docker image optimization, Fargate CPU tuning, SOCI lazy loading, and Lambda Bedrock discovery fix. Use when optimizing startup performance.

Loads Serverless OpenClaw project context. Provides background knowledge needed for development including project overview, tech stack, architecture decisions, and data models.

References Serverless OpenClaw cost optimization guidelines. Validates that no resources exceeding the cost target ($1/month) are created during implementation. Use when writing CDK stacks or making infrastructure changes.

Development workflow guide. Covers build, test, lint, format commands, package structure, Git hooks, TDD methodology, and coding conventions. Use when setting up dev environment, running tests, or following project conventions.

Guides Phase 1 MVP implementation steps. Pass a specific step number as an argument to get the goals, deliverables, validation criteria, and detailed design for that step.

Guides Phase 2 Lambda Container Migration steps. Pass a specific step number (2-1 through 2-5) to get the goals, deliverables, validation criteria, and detailed design for that step.

References OpenClaw internals and integration points. Covers Gateway protocol, agent runtime, session management, tool system, and serverless integration. Use when working with OpenClaw APIs or debugging agent behavior.

Use when planning, submitting, or debugging LLM-DNA fingerprint extraction jobs on SageMaker spot training. Trigger on keywords like "LLM-DNA jobs", "calc-dna", "submit_dna.py", "SageMaker spot", "Solar / K-EXAONE / A.X-K1 / EXAONE 추출", "Phase 5/6 재시도", "model fingerprint extraction", or follow-up verification rounds. Codifies 9 cost/operational lessons from Phase 4–6 of korea-ai-foundation-model-verification (2026-04-30, $64 / 77 jobs, 52.8% waste rate) so future rounds avoid the same learning curve.

Use when working on LLM model lineage, provenance, phylogenetic analysis, from-scratch verification, the project's verification targets (Solar-Open-100B, K-EXAONE, A.X-K1, HyperCLOVAX), reference families (Llama 3, Qwen 2.5, GLM, Mixtral, DeepSeek), or anything under experiments/llm-dna/. Routes through the project wiki/ before external search.

Use when writing, reviewing, or refactoring code in this repo to reduce common LLM coding mistakes — overcomplication, drive-by edits to unrelated lines, hidden assumptions, vague success criteria. Four principles: Think Before Coding, Simplicity First, Surgical Changes, Goal-Driven Execution.

Use when the user invokes /update-changelog, or when a session has produced concrete repository changes (file edits, verification results, methodology updates, structural changes) that should be recorded in CHANGELOG.md by date and category.

Use when the user invokes /update-tutorial, or when a verification-related Q&A exchange has just completed in the session and should be persisted into docs/tutorial/ as narrative-style content. Classifies by topic, finds the right file, inserts above the SECTION_MARKER, and updates the README index.

GitHub 활동 기반으로 README.md 프로필 업데이트. 최근 커밋, 새 저장소, 스타 변화 등을 반영.