Explorar skills

Use Langtrace for DSPy observability and tracing. Use when you want to set up Langtrace, langtrace-python-sdk, auto-instrument DSPy, trace DSPy calls, LLM observability, app.langtrace.ai, or self-hosted tracing. Also used for langtrace setup, langtrace API key, pip install langtrace-python-sdk, DSPy tracing, auto-instrument DSPy, langtrace self-hosted, langtrace docker, trace LM calls, langtrace v

Run DSPy with local models using Ollama — no API key needed. Use when you want to run DSPy locally, use Ollama, set up a local LLM, run offline, or configure local model parameters. Also used for ollama, local model, run LLM locally, llama local, self-hosted LLM, ollama serve, ollama_chat, local inference, run DSPy offline, no API key needed, ollama pull, ollama list, ollama rm, num_ctx, ollama co

Tier-1 strategy-consultant analysis tailored for edtech / online-learning problems — activation, completion, learning outcomes, monetization. Same five frameworks with edtech-aware MECE defaults, vocabulary, and root-cause priors.

Guide for creating high-quality MCP (Model Context Protocol) servers that enable LLMs to interact with external services through well-designed tools. Use when building MCP servers to integrate external APIs or services, whether in Python (FastMCP) or Node/TypeScript (MCP SDK).

Captura uma captura de tela da Game View do Unity Editor, lendo sua textura de renderização diretamente via API do Unity Editor. A imagem, que corresponde à resolução atual da Game View, é retornada para inspeção visual pelo LLM.

AEO (Answer Engine Optimization / AI Visibility) audit skill. Checks 4 categories: AI bot access (robots.txt, GPTBot, ClaudeBot), structured data (Schema.org/JSON-LD), content structure, and technical factors (HTTPS, sitemap, llms.txt). Scores 0-100 with ROI-ranked recommendations and generates a print-ready HTML/PDF report. Use when a user: - Wants to audit, check, or score a website for AI/AEO/G

Structure a recommendation top-down — Barbara Minto's Pyramid Principle. Outputs a single-sentence top-line answer, three to five supporting arguments, and one layer of evidence under each. Use to convert analysis into executive communication, or to structure a board-meeting talk track.

Translate analysis findings into an actionable insight using three labeled sections (Process, Result, Insight). Use when the user has data but needs a recommendation, when an analysis ends without action, or step 5 of a strategic analysis.

Tier-1 strategy-consultant analysis. Apply five frameworks (MECE, Issue Trees, Hypothesis-Driven, Pareto, So What?) sequentially with strict whiteboard-style visual output. Use for root-cause breakdown, strategic problem framing, or "consultant-style" thinking on a business problem.

LLM observability for DSPy with Langfuse -- auto-trace every LM call, attach scores and evaluations, run annotation queues for human review, and track experiments across prompt versions. Use when you want to set up Langfuse, langfuse.com, openinference-instrumentation-dspy, trace DSPy calls, LLM observability with scores, annotation queues, or experiment tracking. Also used for langfuse setup, pip

Tier-1 strategy-consultant analysis using seven frameworks in sequence — MECE, Issue Trees, 5 Whys, Hypothesis-Driven, Pareto, So What?, and Pyramid Principle. Use when the analysis needs both deeper root-cause drilling AND executive-ready communication structure. Heavier than the 5-framework master; reach for it on high-stakes work.

Tier-1 strategy-consultant analysis tailored for nonprofit / fundraising / donor-retention / program problems. Same five frameworks with nonprofit-aware MECE defaults, vocabulary, and root-cause priors.