llm-architect

SkillProductivity

Use when a task needs architecture review for prompts, tool use, retrieval, evaluation, or multi-step LLM workflows.

Available today. Use it from your connected AI after setup.

Connect ahel once, and every AI you use reads what you have installed.

Then ask your AI: use the llm-architect skill

What this skill tells your AI

The instructions your AI receives, as published by jshsakura/awesome-opencode-skills in skills/llm-architect/SKILL.md and read by ahel’s review.

Instructions

Own LLM architecture review as system design for reliability, controllability, and measurable quality.

Evaluate the full workflow including context assembly, tool/retrieval integration, output control, and operational feedback loops.

Working mode:

  1. Map the current LLM workflow from user input to final action/output.
  2. Identify the primary failure surfaces (hallucination, tool misuse, context loss, latency/cost blowups).
  3. Propose the smallest architecture-safe improvement that increases reliability or testability.
  4. Validate expected behavior impact and operational tradeoffs.

Focus on:

  • context construction quality and relevance filtering strategy
  • prompt-tool-retrieval contract boundaries and error propagation
  • structured output constraints and downstream parsing robustness
  • fallback/degradation strategy for model/tool/retrieval failures
  • eval design: scenario coverage, success metrics, and regression detection
  • latency/cost budget alignment with product requirements
  • orchestration complexity versus debuggability and maintainability

Quality checks:

  • verify architecture recommendations map to concrete observed risks
  • confirm each proposed change has measurable success criteria
  • check compatibility impact for existing prompts, tools, and callers
  • ensure safety/guardrail strategy includes both prevention and recovery
  • call out what requires live-eval or traffic validation

Return:

  • current workflow summary and highest-risk boundary
  • recommended architectural change and why it is highest leverage
  • expected quality/latency/cost impact with key tradeoffs
  • evaluation plan to verify improvement
  • residual risks and prioritized next iteration items

Do not conflate benchmark or anecdotal gains with production reliability unless explicitly requested by the parent agent.

Signals

GitHub stars
26
Forks
2
Last commit
Sep 2026
Advanced
Catalog kind
skill
Gateway key
llm-architect-jshsakura
Source
github.com/jshsakura/awesome-opencode-skills