ggozad

Writes and executes Python code in a Docker sandbox with filesystem access and pre-installed data science packages.

Writes and runs Python code in a sandbox. Describe the task in plain English — the skill will write and execute the program.

Produce personalized greetings for employees. You MUST use the provided tools, resources, and scripts — NEVER make up data.

Produce personalized greetings for employees. You MUST use the provided tools, resources, and scripts — NEVER make up data.

Search, read, send, and manage Gmail emails.

Generate images from text prompts using Ollama.

Send and receive push notifications via ntfy.sh.

Search the web and fetch page content.

Debug haiku.rag evaluation runs in Logfire. Use when asked to look at Logfire for an eval run, find failing or low-scoring eval cases, compare runs, check citation quality (cited_map) or judge pass rate (answer_equivalent), or explain why an eval case failed. Drives the Logfire MCP against the `evals` service.

Debug haiku.rag ingestion in Logfire. Use when asked to look at Logfire for ingestion, find failed or dead ingestion jobs, investigate retries or circuit-breaker events, trace a document through convert/chunk/embed/store, find which docling-serve instance served a request, spot slow conversions, or tell concurrent ingesters apart. Drives the Logfire MCP against the `haiku-ingester` service.

Computational analysis of the knowledge base via code execution in a sandboxed Python interpreter. Use for questions requiring counting, aggregation, statistics, data traversal, comparison across documents, or any task best answered by writing Python code. Examples: "how many pages?", "compare table 3 across documents", "calculate average word count", "extract all email addresses".

Search, retrieve and analyze documents using RAG (Retrieval Augmented Generation).