katrinalaszlo

Agent experience design, SaaS pricing strategy, and agent-readiness audits. MCP server with notebook search and 5 installable Agent Skills.

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Repositorio: katrinalaszlo/personal-site
Última actividad en el origen: 11 de agosto de 2026 a las 22:57
Idioma detectado de SKILL.md: inglés
Estrellas: 0
Forks: 0

Opciones de instalación

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npx skills add https://github.com/katrinalaszlo/personal-site --skill katrinalaszlo

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SKILL.md

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agent-experience-design

Design products that AI agents can effectively use. Covers Agent Experience (AX) four pillars (Access, Context, Tools, Orchestration), agent-readable site standards (llms.txt, AGENTS.md, AgentReady, Lighthouse agentic browsing, MCP Server Cards), mutual legibility (two-way agent-human communication, three counterintuitive HCI findings), the bifurcated web (visible vs invisible, brand-to-bot, AVIO replacing SEO), and agent self-serve implementation (programmatic signup, sandbox provisioning, capability keys, removing human gates, WebMCP). Use when building agent-facing APIs, MCP servers, agent signup flows, agent-readable documentation, pricing for agent buyers, or any product surface where AI agents are users. Use when reviewing or designing agent UX, agent onboarding, agent auth, or agent billing.

2026-05-18

agent-tools

Specific agent platforms and orchestration tools. Covers OpenClaw personal agents (local-first agent framework, personal agent architecture, tool management, memory persistence, multi-agent coordination) and Hermes orchestration (message-based agent coordination, pub/sub patterns, agent-to-agent communication, workflow orchestration). Use when building personal AI agents, setting up agent orchestration infrastructure, or evaluating agent frameworks and coordination patterns.

2026-05-18

ai-foundations

How neural networks work from tokens to predictions. Covers transformer model architecture (embeddings, attention, Q/K/V projections, multi-head attention, RoPE positional encoding, MLPs, residual connections, output head), training loops (forward pass, backward pass, gradients, loss functions, optimization, learning rate schedules, overfitting, regularization), and data pipelines (tokenization, BPE, batching, packing, evaluation metrics). Use when learning or explaining how LLMs work internally, debugging model behavior, or understanding why a model produces certain outputs.

2026-05-18

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name	katrinalaszlo
description	Agent experience design, SaaS pricing strategy, and agent-readiness audits. MCP server with notebook search and 5 installable Agent Skills.

What I can accomplish

Query notebook content on AI systems, agent experience, pricing, and multi-agent patterns via MCP server
Provide 5 installable Agent Skills covering AI foundations, knowledge systems, system design, agent tools, and agent experience design
Audit sites for agent readiness using aeo-ready scanner
Consult on SaaS pricing strategy, packaging, and conversion optimization

Required inputs

MCP Endpoint: POST https://katrinalaszlo.com/api/mcp with JSON-RPC
Skills Install: npx skills add https://github.com/katrinalaszlo/personal-site
Base URL: https://katrinalaszlo.com
No authentication required for any endpoint

Constraints

All endpoints are read-only and public
MCP server supports query_notebook, list_topics, get_skill tools
No rate limiting on public endpoints

Key documentation

LLM Profile: Compact profile for language models
Full Profile: Extended profile with notebook index and all endpoints
Structured Data: Machine-readable expertise, projects, contact
OpenAPI Spec: API specification for MCP endpoint
Developer Portal: MCP setup, skills install, all endpoints
Notebook: 18 interactive essays on AI systems and agent experience

katrinalaszlo

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What I can accomplish

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What I can accomplish

Required inputs

Constraints

Key documentation