architectural thinking engine
by Timoranjes
Transform your AI agent from a code generator into a senior architect that enforces clean design and SOLID principles.
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THE AGENSI STORE
71 skills found
by Timoranjes
Transform your AI agent from a code generator into a senior architect that enforces clean design and SOLID principles.
Design the right team of specialized AI subagents for your project and get the definition files written properly — precise delegation triggers, focused system prompts, least-privilege tools, and the right model tier for each job. Includes a template, orchestration patterns, and a complete sample team.
Detects and fixes Norwegian-specific AI patterns and "slop" to ensure text sounds natively human.
Create a system of six reusable, field-specific prompt patterns to ensure consistent AI outputs.
Generate professional pytest suites using behavior-driven matrices, AAA patterns, and resilient fixture architecture.
by Timoranjes
Teaches AI coding agents to design safe Prisma schemas that prevent data loss, race conditions, N+1 queries, and the dangerous Prisma migration reset. Covers 12 critical anti-patterns (missing indexes
by Timoranjes
Teaches AI coding agents to systematically reduce code complexity by identifying and refactoring high-cognitive-load patterns: deeply nested conditionals, god functions, excessive state mutations, tan
by Shogun Labs
Battle-tested prompting patterns to eliminate LLM output drift. Sandwich structure, few-shot examples, history limits, retry, and token caps — 6 composable layers for production-grade agent reliability.
A seven-step auditing system that identifies and flags machine-like prose patterns without stripping your original voice.
Remove AI writing patterns without erasing the writer's voice.
by PromptWagon
Reviews document sets, source quality, chunking logic, metadata, retrieval coverage, citation traceability, answer grounding, source gaps, stale content, duplicate content, and failure patterns for RAG knowledge-base chatbots. Helps AI, product, support, governance, and engineering teams diagnose common and costly RAG quality problems before deployment or after incidents.
by Shogun Labs
Battle-tested prompting patterns to eliminate LLM output drift. Sandwich structure, few-shot examples, history limits, retry, and token caps — 6 composable layers for production-grade agent reliability.
by Timoranjes
Teaches AI coding agents to handle API and tool call failures gracefully using production-grade resilience patterns: exponential backoff with jitter, circuit breakers, timeout management, rate-limit h
A deep reference library of production agent patterns — orchestration, context, tool design, failure and recovery, oversight, and evaluation. Every pattern states when it applies, when it's the wrong answer, what it costs, and the failure it prevents. Seven reference files, not a checklist.
by Timoranjes
Comprehensive React Hooks audit and optimization skill for AI coding agents. Audits all 15+ built-in React hooks for correct usage, dependency completeness, cleanup patterns, performance optimization,
A defensive catalog of ~39 agent security attack patterns across every surface — injection, tool abuse, exfiltration, memory poisoning, multi-agent trust, retrieval poisoning — each with a detection signal, a concrete defense, and a severity. Nine reference files plus a threat-model worksheet. For hardening agents you own.
Audits EVM contract bytecode for honeypots, drainers, and malicious owner patterns before you interact.
Replace generic AI-interface patterns with product-specific visual rules and a bounded implementation plan that preserves working behavior.
by Marco F
Turn your AI agent into a Senior Next.js 15 & React 19 Architect │ to automatically enforce strict App Router patterns, secure Server │ Actions with Zod, and eliminate performance bottlenecks.
Check supplied repository paths and ignore patterns for uncovered or already tracked sensitive-looking files.
Analyzes 30-day spending patterns to identify financial leaks and calculate a weekly safe-to-spend number.
by Timoranjes
A systematic debugging framework for AI agents to resolve edit loops, instruction decay, and context drift in production. Helps agents self-diagnose failure patterns and recover autonomously.
Surface missing relationship context, mixed register, and unreviewed Japanese business-language patterns.