A TypeScript-first agent app kit. Write instructions in Markdown and tools in TypeScript, and get an agent you can run, inspect, approve and replay.

Documentation · Quickstart · Issues

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npm create plico@latest my-agent -- --provider anthropic
cd my-agent && npm install
npx plico run --dry .      # no API key needed

Add a key to .env, run npm run dev, and chat with your agent in Studio.

Studio ships inside @plico-ai/cli. Every row above is one event from the run's log.

How it works

What a project looks like

my-agent/
├── agent.md            instructions, in Markdown
├── plico.config.ts     model, provider, settings
├── skills/             Markdown the agent loads when it needs it
├── tools/              TypeScript tools, with approvals
├── evals/              scripted cases that run in CI with no model
├── artifacts/          files the agent produces
└── memory/

Everything is a file you can read, review in a pull request, and commit next to your app code.

Instructions are plain Markdown:

# Internal Ops Agent

You help the internal ops team triage requests.

- Use `create_ticket` to open a ticket.
- Use `close_ticket` only when the person asks. A person approves each call.

Tools are typed TypeScript. The handler's input is inferred from inputSchema:

import { defineTool } from "@plico-ai/sdk";

export default defineTool({
  name: "close_ticket",
  description: "Close a support ticket. This cannot be undone.",
  inputSchema: {
    type: "object",
    properties: { ticketId: { type: "string" } },
    required: ["ticketId"],
    additionalProperties: false,
  },
  capabilities: ["ticket:write"],
  approval: { required: true, reason: "Closing a ticket cannot be undone." },
  handler: async ({ ticketId }) => ({ ticketId, status: "closed" }),
});

When the model calls close_ticket, the run pauses and Studio asks a person to approve it.

Declare an output schema in agent.md frontmatter or plico.config.ts to require a validated structured result. The final run.completed event and run result include structuredOutput; output stays text. See run schemas.

Why Plico

• File-first. The project is a directory tree. No hidden state, no code generation, no build step.
• One event log. Every run is a durable, replayable trace. Studio, evals, streaming and the HTTP API all read from it.
• Human approval. Mark a tool as needing approval and the run waits until someone decides.
• Studio included. Chat, inspect run events, review approvals, and diff the artifacts your agent writes.
• Evals without a model. Scripted cases replay in CI, so a change to a prompt or tool is checked in seconds.
• Any provider. Anthropic, OpenAI, Google, or any OpenAI-compatible endpoint (Ollama, OpenRouter, LiteLLM).
• Embeds in your backend. createPlico mounts the API in Express, Hono or Next.js, tags runs with your own metadata, and leaves authentication to your app.
• OpenTelemetry tracing. Export spans to the collector you already run.

Packages

Package	Purpose
create-plico	npm create plico: scaffold a project
@plico-ai/cli	The plico command: validate, run, serve, eval, readiness
@plico-ai/sdk	defineTool and defineConfig for your project
@plico-ai/server	The HTTP API and createPlico for embedding
@plico-ai/runtime	The run loop and event store
@plico-ai/core	Project loading and validation
@plico-ai/contracts	Wire types

Status

Plico is a developer preview (0.1). The HTTP API under /v1 takes additive changes only; the TypeScript exports can change in any 0.x minor release. It needs Node 22.18 or later. Follow the milestones for what is planned.

Learn more

• Quickstart: scaffold, run, and approve a tool call
• Project layout, Tools, Providers
• Approvals, Evals, Events, Upgrading, and how Plico compares
• Embed in a backend and the HTTP API
• Example: a refund agent and examples/internal-ops-agent, complete projects
• Build with an AI coding agent: llms.txt, a scaffolded AGENTS.md and a Claude skill

Contributing

See CONTRIBUTING.md to set up the repository and run the checks.

License

Apache-2.0. See LICENSE and NOTICE.