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Found 6,717 Skills
Layer agentic capabilities onto a full-stack Eve app — agents, teams, memory, events, chat, and coordination. Use when designing an app where agents are primary actors, not afterthoughts.
Build agent-friendly CLIs for Eve-compatible apps. Wrap REST APIs with domain commands, auto-auth, structured errors, and --json output. Agents use CLIs instead of curl/fetch.
Web UI testing and browser automation. Use Vercel agent-browser for general apps, or the repo-pinned Playwright wrapper inside Eve Horizon. Use when tasks require opening pages, interacting with forms, validating UI flows, taking screenshots, extracting page data, or running repeatable browser-based checks locally or in CI.
Design agent-native applications on Eve Horizon. Apply parity, granularity, composability, and emergent capability principles to make apps that agents can build, operate, and extend naturally.
Distill repeated work into Eve skillpacks by creating or updating skills with concise instructions and references. Use when a workflow repeats or knowledge should be shared across agents.
Choose and combine Eve storage primitives to give agents persistent memory — short-term workspace, medium-term attachments and threads, long-term org docs and filesystem. Use when designing how agents remember, retrieve, and share knowledge.
Author agentic verification plans for Eve-compatible apps. Use when building structured test suites that verify app correctness AND Eve platform conformance — CLI parity, manifest conventions, SSO auth, managed migrations, fixture-driven ingestion, and agent efficiency.
Analyse agent execution to find wasted tool calls, wrong turns, and blind alleys. Optimise agents to reach their goal in the fewest turns, tokens, and least time. Recommend harness/model changes — never apply without user approval.
Run and interpret one safe, bounded Kitaru replay comparison against an accepted cohort and exact evaluators. Use when a user wants to replay a cohort, test or compare a model, prompt, system prompt, parameter, agent version, or tool policy, supervise an experiment run, determine whether one candidate helped, or ask for one bounded change worth testing.
Guide users from their own agent code or recorded traces through Kitaru setup, session import or recording, human review, an accepted behavior, a versioned cohort, and evaluator selection, then hand one bounded change to the replay-experiment skill. Use when a user wants to connect or inspect an existing agent, import real traces, investigate a known bad or surprising session, discover recurring failure modes, learn the evidence-led review flow, resume an investigation, create a cohort from reviewed evidence, or author an evaluator for an accepted behavior. When a first-time user has no agent or evidence and wants a fast demonstration with the public returns-agent template, use the `kitaru-guided-tour` skill instead.
Give first-time users a short, value-first Kitaru tour with the public returns-agent template. Use when someone has no agent or traces of their own, arrives from Kitaru onboarding, asks for a demo, tutorial, quickstart, or guided example, needs the public template cloned or prepared, wants the coding agent to prepare trace annotations before they judge sessions, or wants to experience Kitaru's value before learning the full investigation method. Prepare a three-session frontend review, let the human provide verdicts, turn one accepted finding into a deterministic evaluator, and finish with one approved bounded replay experiment. Route real agents, open-ended discovery, and production evidence to kitaru-investigation instead.
Build a project-local Kitaru adapter for an unsupported Python or TypeScript agent framework. Use when a user wants to record or replay framework-native agent runs in Kitaru, needs a custom adapter, has no supported Kitaru integration for their framework, or needs to assess whether public framework hooks and the installed Kitaru SDK can support an adapter.