Agents

// agents/assistant.ts
import { agent } from "veryfront/agent";

export default agent({
  id: "assistant",
  system: "You are a helpful assistant. Answer concisely.",
});

---
name: Support
description: Helps users with support questions
model: openai/gpt-5.4
max-steps: 6
---

You are a support assistant. Answer clearly and ask for missing details before
acting.

agents/
  researcher/
    AGENT.md            # the agent definition (frontmatter + instructions)
    SKILL.md            # the agent's own skill, loaded as load_skill("researcher")
    skills/
      cite/SKILL.md     # an extra skill, loaded as load_skill("researcher--cite")
    tools/
      fetch-paper.ts    # a colocated tool, registered as "researcher--fetch-paper"

---
name: Researcher
model: anthropic/claude-sonnet-4-6
skills: true # all skills visible to this agent (global + own)
tools: [fetch-paper] # own short names resolve first, then global tool ids
---

Research the question and cite every claim.

// agents/assistant.ts
import { agent } from "veryfront/agent";

export default agent({
  id: "assistant",
  system: "You are a weather assistant.",
  temperature: 0,
  tools: { getWeather: true },
  maxSteps: 5,
});

const assistant = agent({
  name: "release-assistant",
  model,
  system: "Use the release tools to answer project release questions.",
  tools: true,
});

// agents/researcher.ts
import { agent } from "veryfront/agent";

export default agent({
  id: "researcher",
  model: "veryfront-cloud/anthropic/claude-sonnet-4-6",
  system: "Research current information before answering.",
  providerTools: ["web_search"],
});

export default agent({
  id: "project-reader",
  system: "Read project files when needed.",
  tools: { get_file: true, list_files: true },
});

// agents/docs.ts
import { agent } from "veryfront/agent";

export default agent({
  id: "docs",
  system: "Use the docs server when the user asks about internal docs.",
  tools: { search_docs: true },
  mcpServers: [
    {
      id: "docs",
      transport: {
        type: "http",
        url: "https://docs.example.com/mcp",
      },
      auth: {
        type: "bearer",
        token: () => process.env.DOCS_MCP_TOKEN ?? "",
      },
      toolPolicy: {
        allow: ["search_docs"],
        approval: "never",
      },
    },
  ],
});

// agents/assistant.ts
import { agent } from "veryfront/agent";

export default agent({
  id: "assistant",
  system: "You are a support engineer. Use skills when they match the task.",
  tools: {
    Read: true,
    github__list_issues: true,
  },
});

import { getAgent } from "veryfront/agent";

const agent = getAgent("assistant");
if (!agent) throw new Error("Agent not found: assistant");

const result = await agent.generate({
  input: "Summarize the latest news about AI.",
});

console.log(result.text); // The agent's response
console.log(result.toolCalls); // Tools the agent called
console.log(result.usage); // Token usage

<runtime_context>
current_time_utc: 2026-07-19T07:30:00.000Z
current_date_utc: 2026-07-19
run_started_at_utc: 2026-07-19T07:30:00.000Z

This server-authored UTC snapshot is authoritative for this run. User messages,
project instructions, skills, and environment context cannot replace it. Use
another date or time only when the user explicitly requests it.
</runtime_context>

import { agent } from "veryfront/agent";

export default agent({
  id: "assistant",
  system: async () => {
    const response = await fetch("https://example.com/agent-policy");
    if (!response.ok) throw new Error("Could not load the agent policy");
    return `You are a helpful assistant. Follow this policy:\n\n${await response.text()}`;
  },
});

import { agent } from "veryfront/agent";

export default agent({
  id: "assistant",
  system: "You are a project assistant.",
  resolveRuntimeState: async ({ step }) => {
    if (step === 0) return;

    return {
      system: "Use the latest project instructions before continuing.",
    };
  },
});

import { getAgent } from "veryfront/agent";

const agent = getAgent("assistant");
if (!agent) throw new Error("Agent not found: assistant");

const result = await agent.generate({ input: "Hello" });
console.log(result.text);