{
  "$schema": "https://schemas.agentskills.io/discovery/0.2.0/schema.json",
  "skills": [
    {
      "name": "building-pydantic-ai-agents",
      "type": "archive",
      "description": "Build AI agents with Pydantic AI — tools, capabilities (including on-demand loading), workspaces, 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, attach a workspace, defer capability loading, stream output, define agents from YAML, or test agent behavior.",
      "url": "https://pydantic.dev/.well-known/agent-skills/artifacts/building-pydantic-ai-agents.fb6dbe2c7231c35c0c913c862d0c2b4669ea03a75dc67c42acd4054945a16032.tar.gz",
      "digest": "sha256:fb6dbe2c7231c35c0c913c862d0c2b4669ea03a75dc67c42acd4054945a16032"
    },
    {
      "name": "logfire-coding-agents",
      "type": "archive",
      "description": "Connect Claude Code or Codex itself to Logfire telemetry, or route a coding agent's model requests through Pydantic AI Gateway. Use for coding-session recording, capture policies, Gateway agent configuration, temporary proxy launches, status, or removal. Not for instrumenting an application or routing an application's model client.",
      "url": "https://pydantic.dev/.well-known/agent-skills/artifacts/logfire-coding-agents.c5f84034b3e173af32435bb866255aab8a10f2987b70b71744ce0d216e3f282b.tar.gz",
      "digest": "sha256:c5f84034b3e173af32435bb866255aab8a10f2987b70b71744ce0d216e3f282b"
    },
    {
      "name": "logfire-evals",
      "type": "skill-md",
      "description": "Run offline Python (`pydantic_evals`) or Node.js (`logfire/evals`) evaluations and review them in Logfire. Also redirect existing Braintrust `Eval()` suites. Use for eval setup, test datasets, AI scoring, agent checks, LLM judges, Braintrust migration, or Logfire Datasets & Experiments. Not for live traffic or infrastructure monitoring.",
      "url": "https://pydantic.dev/.well-known/agent-skills/artifacts/logfire-evals.fc3724e110df276e3b992a1f5a5530409d49671cb3d90ce0bb3893780bb2e68d/SKILL.md",
      "digest": "sha256:fc3724e110df276e3b992a1f5a5530409d49671cb3d90ce0bb3893780bb2e68d"
    },
    {
      "name": "logfire-frontend",
      "type": "archive",
      "description": "Set up and troubleshoot Pydantic Logfire frontend observability and session replays in JavaScript/TypeScript browser applications. Use for browser errors, RUM, Web Vitals, replay recording, privacy controls, or reducing browser telemetry volume. Supports browser entrypoints, React/Vite, and the client side of Next.js; use logfire-instrumentation for server-side telemetry.",
      "url": "https://pydantic.dev/.well-known/agent-skills/artifacts/logfire-frontend.2dec9a99f49ea4ec79c476528524cf3ebc60f0e23f3e7f9374ffe59aa6210410.tar.gz",
      "digest": "sha256:2dec9a99f49ea4ec79c476528524cf3ebc60f0e23f3e7f9374ffe59aa6210410"
    },
    {
      "name": "logfire-gateway",
      "type": "skill-md",
      "description": "Configure an application's model calls to use the Pydantic AI Gateway. Use when the user asks to route application inference through Gateway, connect a Gateway key, or add a Gateway provider snippet. This does not configure or instrument coding agents.",
      "url": "https://pydantic.dev/.well-known/agent-skills/artifacts/logfire-gateway.f29f4006216267635924f99528585421648e46b0b5badf196c2606bc89b4999f/SKILL.md",
      "digest": "sha256:f29f4006216267635924f99528585421648e46b0b5badf196c2606bc89b4999f"
    },
    {
      "name": "logfire-instrumentation",
      "type": "archive",
      "description": "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`.",
      "url": "https://pydantic.dev/.well-known/agent-skills/artifacts/logfire-instrumentation.ceaa7469ddca4560402f4b15a343efcb461799b02c44f4680b48de19bd0cd510.tar.gz",
      "digest": "sha256:ceaa7469ddca4560402f4b15a343efcb461799b02c44f4680b48de19bd0cd510"
    },
    {
      "name": "logfire-infrastructure",
      "type": "archive",
      "description": "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.",
      "url": "https://pydantic.dev/.well-known/agent-skills/artifacts/logfire-infrastructure.54e2d642eebb94c7e4fb8a43492d58fca235755c708ea8c0d4f7b476fd2081f5.tar.gz",
      "digest": "sha256:54e2d642eebb94c7e4fb8a43492d58fca235755c708ea8c0d4f7b476fd2081f5"
    },
    {
      "name": "logfire-query",
      "type": "archive",
      "description": "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.",
      "url": "https://pydantic.dev/.well-known/agent-skills/artifacts/logfire-query.13e09b992322f4aece66cb60d73e83c4f4e71e24885963793fc36c9ace2a4c1c.tar.gz",
      "digest": "sha256:13e09b992322f4aece66cb60d73e83c4f4e71e24885963793fc36c9ace2a4c1c"
    },
    {
      "name": "logfire-setup",
      "type": "skill-md",
      "description": "Route broad requests to set up Pydantic Logfire across application instrumentation, infrastructure, evals, frontend observability, Gateway, or coding agents. Use for \"set up Logfire\", \"add Logfire to my project\", \"get me set up properly with Logfire\", \"send as much data as would be useful\", mentions of Logfire without specific scope, or multi-surface requests; use the matching specialist directly for an already scoped request.",
      "url": "https://pydantic.dev/.well-known/agent-skills/artifacts/logfire-setup.65368dd4c7cf277a3a065feecf43131e9d788ff940ea2ba4ad9c168df80ad2c2/SKILL.md",
      "digest": "sha256:65368dd4c7cf277a3a065feecf43131e9d788ff940ea2ba4ad9c168df80ad2c2"
    },
    {
      "name": "logfire-ui",
      "type": "skill-md",
      "description": "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.",
      "url": "https://pydantic.dev/.well-known/agent-skills/artifacts/logfire-ui.c2a10afd95ebd1c1efe87fa551858cb280da9a7d76a8bf28fd7577525d381d06/SKILL.md",
      "digest": "sha256:c2a10afd95ebd1c1efe87fa551858cb280da9a7d76a8bf28fd7577525d381d06"
    },
    {
      "name": "pydantic-ai-harness",
      "type": "archive",
      "description": "Extend Pydantic AI agents with capabilities from pydantic-ai-harness -- the Coder coding agent, file and shell tools in local or sandboxed workspaces (Modal, E2B, Sprites, smolvm), Code Mode, sub-agents and planning, memory and skills, context compaction, guardrails and spend limits, web research and browsers, hosted SaaS integrations, step persistence, and background agents on Render Workflows. Use when the user mentions pydantic-ai-harness or pydantic_ai_harness, imports a harness capability such as Coder, CodeMode, FileSystem, Shell, SubAgents, Memory, or ToolGuardrail, or wants a Pydantic AI agent that edits files, runs commands or agent-written Python, delegates, remembers, manages long context, stays within limits, or runs model and tool operations as chained Render task runs.",
      "url": "https://pydantic.dev/.well-known/agent-skills/artifacts/pydantic-ai-harness.80e35d56ebff0cfe807beaeaf151c876fcdff7ae54bde0dc13628e61ad1ad465.tar.gz",
      "digest": "sha256:80e35d56ebff0cfe807beaeaf151c876fcdff7ae54bde0dc13628e61ad1ad465"
    }
  ]
}