AI Toolkit — 27 skills · 3 agents · MCP tools · coding rules — https://pirahansiah.com/ai-toolkit/

AI Engineering Stack

AI Prompt & Agent Toolkit

Twenty-seven battle-tested Claude Code skills, three code-review agents, MCP tooling, and coding rules — the exact AI engineering stack behind pirahansiah.com, organized into ready-to-use prompt packs for modern LLMs.

Prompt Packs

Each pack is a themed collection of skills and prompts. They ship as copy-paste prompt files that drop straight into Claude Code, Cursor, or any instruction-following agent.

Pack 01 — Computer Vision & Edge AI

CV Engineering

  • cv-pipeline — detection, tracking, segmentation, annotation, video analysis.
  • edge-deploy — Hailo, Axelera, Qualcomm, Apple Neural Engine, Jetson, Movidius.
  • quantize — INT8/INT4 via NNCF, TensorRT, ONNX Runtime.
Pack 02 — Code Review & Debugging

Quality & Security

  • code-reviewer — quality, security, maintainability reviews.
  • debugger — errors, test failures, unexpected behavior.
  • security-auditor — auth, data handling, security-sensitive code.
  • diagnosing-bugs — structured loop for hard bugs and regressions.
Pack 03 — System Design

Architecture & Modeling

  • codebase-design — shared vocabulary for deep modules.
  • domain-modeling — pin down domain terminology and ubiquitous language.
  • improve-codebase-architecture — find deepening opportunities, visual HTML report.
  • grill-me / grilling / grill-with-docs — relentless interviews that stress-test a plan and produce ADRs.
Pack 04 — Agent Workflows

Autonomy & Orchestration

  • autonomy-ladder — graduated autonomy from suggest-only to full-auto with audit logs.
  • evaluator-optimizer — split writer from checker, loop until it passes.
  • loop-builder — scheduled automations with STATE.md memory.
  • handoff — compact a conversation into a pickup document.
  • to-prd / to-issues / triage — conversation to PRD to grabbable issues.
Pack 05 — Engineering Discipline

Build & Refactor

  • tdd — red-green-refactor, tests before code.
  • modernize — update Python/C++ to latest standards, add types and tests.
  • prototype — throwaway runnable prototype to validate a design.
  • learn-from-failures — mine past failures into reusable rules.
Pack 06 — Writing & Communication

Human Output

  • humanizer — strip signs of AI-generated writing.
  • terse-output — drop ceremony, make every token count.
  • teach — explain a new skill or concept clearly.
Pack 07 — Knowledge & Portfolio

Graph & Memory

  • graphify — turn code, docs, papers, images, video into a knowledge graph.
  • codebase-memory — query the codebase knowledge graph.
  • portfolio — generate resumes, update the site, consolidate assets.

MCP Servers

MCP

codebase-memory-mcp

  • Structured code queries against a persistent codebase knowledge graph — answer "how does this module work" without re-reading the tree.

Coding Rules

Rule

cpp-style

  • Modern C++ conventions enforced on every change.
Rule

python-style

  • Python style and linting standards.
Rule

hardware-optimization

  • Performance patterns for edge and embedded targets.

Commands & Hooks

Command

/review

  • One-shot code review against the project's standards.
Hooks

Session lifecycle

  • code-discovery-gate, session-reminder, subagent-reminder — keep every session grounded in the codebase knowledge graph.
Claude CodeCursorOpenAI CodexGemini CLIOpenCodeContinue
Built for the current generation of models. These patterns — evaluator-optimizer loops, autonomy ladders, agent handoffs, and knowledge-graph memory — are designed for the reasoning and tool-use capabilities of Claude 5, GPT-5.6, and equivalent frontier models. The full prompt packs are available on the shop page.