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pydantic

@pydantic seed · attribution · source repo

0 followers · 9 skills

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   Pydantic · pydantic

   Pydantic is a Python data validation and serialization library, based on type hints. Use this skill whenever you need to do relatively complex data modeling using Pydantic, e.g. when adding constraints, defining a model hierarchy with subclasses, etc.
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   Logfire UI · pydantic

   Open or return Logfire project pages, live views, trace links, and Explore pages in the Codex browser without querying telemetry first. Use this skill when the user asks to "open in Logfire", "show in the live view", "open Explore", "open the UI", "show in Codex", "use the browser", "give me a link", or asks for a Logfire GUI/browser/live-view presentation of a project, time range, service, span, trace, log, or filter. If "show" or "view" wording is ambiguous, ask whether the user wants a UI view or query analysis.
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   Logfire Evals · pydantic

   Evaluate Python AI/agent code against a dataset of test cases using pydantic_evals, and review results in Logfire's Datasets & Experiments UI. Also covers redirecting an existing Braintrust Eval() suite to Logfire with no code changes. Use this skill whenever the user asks to "set up evals", "add an evaluation", "test my agent against cases", "write a dataset of test cases", "score my LLM output", "add an LLM judge", "check tool-call correctness", "send Braintrust evals to Logfire", "migrate from Braintrust", or mentions pydantic_evals, Braintrust, Datasets & Experiments, or evaluating AI/agent behavior against known inputs. The `pydantic_evals` workflow is Python-only; the Braintrust redirect also supports TypeScript suites, env-vars-only. Both are for scoring DEFINED test cases offline — not for instrumenting live production traffic (use `logfire-instrumentation` for that) and not for infrastructure monitoring (use `logfire-infrastructure`).
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   Logfire Query · pydantic bundle

   Query and analyze Logfire telemetry data — traces, logs, spans, metrics, summaries, and SQL results. Use this skill when the user asks to "query logfire", "search traces", "find logs", "query data", "search spans", "look up errors in logfire", "get metrics from logfire", "analyze telemetry", "summarize errors", "find root cause", or add Logfire querying capabilities to code. Do not use this skill for direct Logfire UI, browser, live-view, Explore-page, or link-opening requests; use logfire-ui instead. If "show" or "view" wording is ambiguous, ask whether the user wants a UI view or query analysis.
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   Logfire Setup · pydantic

   Entry point for Pydantic Logfire — an observability, monitoring, and evals platform. Use this skill when the user asks to "set up Logfire", "add Logfire to my project", "get me set up properly with Logfire", "send as much data as would be useful", mentions Logfire without a specific scope, or their request spans more than one of instrumenting application code / monitoring infrastructure / evaluating AI behavior. If the request is clearly scoped to exactly one of those, fetch that specific skill directly instead of this one — this skill exists to route, not to duplicate their content.
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   Pydantic AI Harness · pydantic bundle

   Extend Pydantic AI agents with batteries-included capabilities from pydantic-ai-harness -- Code Mode (collapse many tool calls into one sandboxed Python execution), a filesystem and shell, sub-agents, planning, context compaction, and more. Use when the user mentions pydantic-ai-harness, CodeMode, Monty, code mode, or tool sandboxing, when they want first-party filesystem/shell/sub-agent/planning/compaction capabilities for a Pydantic AI agent, when they want an agent to run agent-written Python, or when a Pydantic AI agent would benefit from orchestrating multiple tool calls in a single sandboxed script.
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   Logfire Infrastructure · pydantic bundle

   Monitor hosts, Docker containers, Kubernetes clusters, database/queue/cache servers, and cloud-provider metrics with Pydantic Logfire — no application code required. Use this skill whenever the user asks to "monitor my host/server/VM", "monitor my Docker containers", "monitor my Kubernetes cluster", "send infrastructure metrics to Logfire", "watch my database/Postgres/Redis/MongoDB/Kafka", "collect cloud metrics" (AWS/GCP), or mentions the OpenTelemetry Collector in the context of Logfire. This is infrastructure only — for instrumenting APPLICATION CODE (traces, logs, AI/agent spans) use the logfire-instrumentation skill instead.
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   Logfire Instrumentation · pydantic bundle

   Add Pydantic Logfire observability to application code — traces, logs, metrics, and AI/agent spans. Use when the user asks to add or configure Logfire, observability, tracing, logging, or monitoring; maximize useful telemetry; or understand what an app is doing. Supports Python, JavaScript/TypeScript, Rust, and major AI agent frameworks including Pydantic AI, OpenAI Agents SDK, Claude Agent SDK, LangChain, LangGraph, CrewAI, AutoGen, and Google ADK. For infrastructure-only monitoring (hosts, Docker, Kubernetes, databases, or cloud metrics with no app-code changes), use `logfire-infrastructure`. For evaluating AI/agent behavior against test datasets, use `logfire-evals`.
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   Building Pydantic AI Agents · pydantic bundle

   Build AI agents with Pydantic AI — tools, capabilities (including on-demand loading), structured output, streaming, testing, and multi-agent patterns. Use when the user mentions Pydantic AI, imports pydantic_ai, or asks to build an AI agent, add tools/capabilities, defer capability loading, stream output, define agents from YAML, or test agent behavior.
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