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Agents do

Skill dot-do/skills/agents-do

.do Agent Skills — reusable, composable skill modules

Install
npx -y skills add dot-do/skills --skill agents-do

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Expert guidance for agents.do — named agent imports, tagged template calls, multi-agent orchestration, remote pipelines, and the autonomous-agents SDK.

SKILL.md

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agents.do

You are an expert in agents.do — the .do service for deploying and orchestrating named autonomous AI agents.

When to Use

Activate when working with agents.do imports, the Agent() factory, named agent calls, or multi-agent orchestration.

The SDK — Named Imports

import { priya, ralph, tom, mark, quinn, rae, sally } from 'agents.do'

// Natural language — just say what you want
const spec   = await priya`spec out user authentication`
const code   = await ralph`build ${spec}`
const review = await tom`review ${code}`
const tests  = await quinn`test ${review} thoroughly`

Each agent has a real GitHub identity. When Tom reviews your PR, you'll see @tom-do commenting.

Pipeline with Remote .map()

const sprint = await priya`plan the sprint`
  .map(issue => ralph`build ${issue}`)
  .map(code  => tom`review ${code}`)

The .map() is a remote operation — not JavaScript's Array.map. The callback is recorded and sent to the server, which executes the entire pipeline in one pass.

Named Agents

ImportAgentRoleTagline
priyaPriyaProductSpecs, roadmaps, priorities
ralphRalphEngineeringShip iteratively
tomTomTech LeadArchitecture, code review
raeRaeFrontendReact, UI, accessibility
markMarkMarketingCopy, content, launches
sallySallySalesOutreach, demos, closing
quinnQuinnQATesting, edge cases, quality

Lower-Level: Agent() Factory

For custom agents not in the named roster:

import { Agent } from 'autonomous-agents'

const agent = Agent({
  name: 'ContentAgent',
  role: 'content-creator',
  objective: 'Draft, review, and publish content across channels',
  integrations: [
    { name: 'cms',   type: 'api',          endpoint: process.env.CMS_URL },
    { name: 'slack', type: 'notification', channel: '#content' },
  ],
  triggers:   ['contentRequested', 'draftReviewed'],
  actions:    ['draftContent', 'reviewDraft', 'schedulePublication'],
  keyResults: [
    { key: 'draftsCompleted', target: 10,   unit: 'per week' },
    { key: 'publishedOnTime', target: 0.95, unit: 'rate' },
  ],
})

await agent.execute({ type: 'contentRequested', data: { topic: 'AI agents' } })
await agent.do.draftContent({ topic: 'AI agents', audience: 'developers' })

Multi-Agent Orchestration

// Sequential handoff
const spec     = await priya`spec out ${feature}`
const code     = await ralph`build ${spec}`
const reviewed = await tom`review ${code}`

// Parallel
const [safety, quality] = await Promise.all([
  quinn`check security of ${code}`,
  tom`review architecture of ${code}`,
])

// Event-driven loop
import { on } from 'workflows.do'

on.PR.opened(async pr => {
  const review = await tom`review ${pr}`
  if (review.approved) await pr.merge()
  else await ralph`address feedback: ${review}`
})

Best Practices

  • Use named imports (priya, ralph) for platform agents — they have real identity and history
  • Use Agent() factory for custom/tenant-specific agents
  • Keep pipeline chains declarative — .map() is more efficient than sequential awaits
  • Always define keyResults on custom agents — they drive autonomous behavior

What ships with it

Read from the repository

Just SKILL.md. No reference files, no scripts.

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Skills are one crate of 328,083. Ordering is by how many stacks a row turns up in, so the top of any crate is what has actually been picked rather than what has the most stars.