All Agent Skills
41,263 results
- Iphone Duo ReadinessmirzaaghazadehAudit and port an iOS app to iPhone Duo, Apple's first foldable iPhone. Use when asked to support, adapt, prepare, test, or review an app for iPhone Duo, foldable iPhone, the inner/outer display, device poses, or the fold. Entry point that routes to the layout, bars, hinge/scenes, camera, and design skills.
- Iphone Duo Vertical BarsmirzaaghazadehAdapt toolbars, navigation bars and tab bars for the vertical axis on iPhone Duo — item ordering, symbol vs text representations, axis behavior, overflow menus, visibility priority, and when to opt out. Use when toolbar items look wrong, overflow too early, or need to move to the side on the outer display.
- Megfilemegvii-researchUse megfileâs APIs, SmartPath, configuration, and CLI to perform filesystem tasks easy across local FS, S3/OSS-style object storage, SFTP, WebDAV, HTTP, HDFS, and stdio.
- Visual QadylanfeltusUse vision models to self-review screenshots against design intent. Catches spacing issues, alignment problems, color inconsistencies, responsive bugs, and accessibility gaps. Use when reviewing designs, comparing implementations to mockups, or doing pre-ship QA.
- Agent InstallDatadog LabsInstall the Datadog Agent on Kubernetes using the Datadog Operator — required before enabling Single Step Instrumentation (SSI), which automatically instruments applications for APM without code changes. Only use if no Datadog Agent is deployed on the cluster yet.
- Agent InstallDatadog LabsInstall the Datadog Agent on Linux hosts via SSH with Single Step Instrumentation (SSI) enabled — SSI automatically instruments applications for APM without code changes. Only use if no agent is installed yet.
- Agent Observability Auto ExperimentDatadog LabsRun an iterative code-improvement hill-climb against real Datadog LLM-Obs data, locally, with Claude Code as the agent. Establishes a baseline eval, makes one focused change, re-scores with the same harness, keeps the change if it improves the score in the goal's direction (labeling within-noise gains tentative), and repeats.
- Agent Observability Build Eval From AnnotationsDatadog LabsFit a Datadog LLM-Obs evaluator to human labels. Takes an annotation queue, works out where in the trace the labelled property actually lives, drafts an LLM-judge that predicts the human label, scores that judge against the already-labelled rows with a metric agreed with the user, then hill-climbs it — inspect the errors, make one focused change, re-score, keep it only if it beats the best — for…
- Agent Observability Eval BootstrapDatadog LabsBootstrap evaluators from production traces — by default propose online LLM-judge evaluators and, after you confirm, create them in Datadog as disabled drafts (never auto-enabled); on request emit Python SDK code or a framework-agnostic JSON spec instead.
- Agent Observability Eval PipelineDatadog LabsEnd-to-end Agent Observability pipeline for an instrumented ml_app — classify production traces, root-cause failures, bootstrap evaluators, then (optionally) sample + publish a dataset, generate + run an experiment, and analyze results. Six narrated phases with a standardized banner and a "continue" checkpoint between each.
- Agent Observability Experiment AnalyzerDatadog LabsAnalyze LLM experiment results. Handles single or comparative experiments, exploratory or Q&A modes. Use when user says "analyze experiment", "compare experiments", "analyze against baseline", or provides one or two experiment IDs for analysis.
- Agent Observability Experiment BootstrapDatadog LabsBootstrap a reproducible LLM Observability experiment through the Python ddtrace SDK or the Node dd-trace SDK. Use for experiment, dataset, evaluator, benchmark, regression, or LLM-as-a-judge scaffolding. The legacy Python invocation remains supported.
- Agent Observability Online ExperimentDatadog LabsLoad this skill when the user wants to run an online experiment (live-traffic A/B test) on an LLM application instrumented with Agent Observability: compare two versions of a prompt, model, or behavior using a Datadog feature flag, score metrics from evaluations, and cost and token metrics.
- Agent Observability Replay TraceDatadog LabsUse when a developer wants to iterate on ONE specific Agent Observability / LLM Obs trace whose output they didn't like — re-running that trace against their LOCAL code, seeing a concise diff of the old vs new output, and looping (change code → replay → diff) until satisfied. Invoked as /agent-observability-replay-trace <trace-id> [changes to test].
- Agent Observability Session ClassifyDatadog LabsClassify whether user intent was satisfied in a Datadog Agent Observability trace or session. Three modes: (1) session_id — classify a single CMD+I assistant session with RUM; (2) trace_id — classify a single Agent Observability trace without RUM; (3) ml_app — sample and classify multiple sessions or traces from a given LLM app. Output is compact by default (verdict + one-sentence reason).
- Agent Observability Trace RcaDatadog LabsRoot cause analysis on production LLM traces. Diagnoses why an LLM application is failing — works from eval judge verdicts, runtime errors, or structural anomalies depending on what signals are present. Walks the span tree from symptom to root cause.
- Agent SkillsDatadog LabsDatadog skills for AI agents. Essential monitoring, logging, tracing and observability.
- Algorithmic Tradingomer-metinUse when building trading systems, backtesting strategies, implementing execution algorithms, or analyzing market microstructure - covers strategy development, risk management, and production deploymentUse when ", " mentioned.
- API DesignmargeloDesign and review predictable public APIs for TypeScript, JavaScript, React, and React Native libraries. Use when shaping exported functions, classes, hooks, options objects, event and listener APIs, error behavior, naming, cross-platform abstractions, or JS-only packages. Pair with build-nitro-modules when the library is backed by Nitro.
- Build Nitro ModulesmargeloBuilds and designs React Native Nitro Modules with Nitrogen, HybridObject TypeScript specs, Nitro View components, generated native implementations, zero-copy and native-state APIs, Swift/Kotlin/C++ bindings, example apps, and testing.
- Card Game Designomer-metinWorld-class expertise in TCG/CCG design, resource systems, and metagame balanceUse when "card game design, TCG design, CCG design, trading card game, collectible card game, mana curve, deck building, card templating, keyword mechanic, set design, draft format, limited format, card rarity, color pie, faction design, card balance, magic the gathering style, hearthstone style, deckbuilder, card…
- Crypto Trading Botsomer-metinComprehensive expertise in automated crypto trading systems, including DEX sniping bots, arbitrage strategies, MEV protection, Telegram trading bots, and anti-rug protection. Use when "trading bot, sniping bot, arbitrage bot, Telegram trading, DEX bot, MEV bot, copy trading, auto trading, token sniper, " mentioned.
- Datadog AppDatadog LabsGuides developers building Datadog Apps with TypeScript, React, the @datadog/apps scaffolder, and @datadog/vite-plugin. Use when a user wants to scaffold, run, debug, upgrade, build, upload, publish, upload without publishing (draft upload), add an upload-no-publish script, set up CI/CD, use OAuth or API/application key auth, trigger/poll Workflow Automation, choose DDSQL or Action Catalog for…
- datadog-labs/agent-skillsDatadog LabsCollectionPublic repository for Datadog Agent Skills