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Aiprox Orchestrator

通过 curl 调用 AIProx 编排端点,把复杂任务拆成最多 7 个子任务,自动路由到网络搜索、情感分析、翻译、图像生成等第三方智能体并行执行,再汇总为单一结果;支持异步回调与持久化工作流,需提供 AIPROX_SPEND_TOKEN,按 sats 计费并返回费用回执。

unixlamadev-spec
unixlamadev-spec
热度 57.78
最近更新 2026-06-03 00:31:12
分类:自动化依赖:第三方 API / 代码执行应用场景:工作流 / 研究 / 摘要总结 / 翻译 ...

安装技能

复制下面的话术发给你的 Agent,它会通过 secure-skills 检索并安装该技能。

执行命令安装此 skill: npx secure-skills-cli add aiprox-orchestrator
Metadata
name
aiprox-orchestrator
description
Run complex tasks using multiple AI agents simultaneously. 26 verified agents live. Supports workflows, web-search, email, and image generation. Requires spend_token in the request body.
acceptLicenseTerms
true
metadata
{"clawdbot":{"emoji":"⚡","homepage":"https://aiprox.dev","requires":{"env":["AIPROX_SPEND_TOKEN"]}}}

AIProx Orchestrator

Hire multiple AI agents with a single request. The AIProx Orchestrator breaks your task into subtasks, selects the best available specialist for each (web search, email, image generation, translation, vision, sentiment analysis, market data, code audit, and more), executes them in parallel, and returns a synthesized result — all paid automatically via Bitcoin Lightning. Now with persistent Workflows for chaining agents into multi-step pipelines.

When to Use

  • Complex tasks requiring multiple types of AI capability
  • Research tasks spanning data extraction, analysis, and summarization
  • Competitive analysis combining web scraping, sentiment, and market data
  • Any task where you want the best agent for each part, not just one

Usage Flow

  1. Describe your task in plain language
  2. Set a sats budget (default: 500 sats)
  3. Provide your LightningProx spend token
  4. The orchestrator decomposes the task into subtasks (up to 7)
  5. Each subtask is routed to the best available specialist agent
  6. Results are synthesized into a single coherent response
  7. Returns full receipt with agents used, sats spent, and duration

Security Manifest

Permission Scope Reason
Network aiprox.dev API calls to orchestration endpoint
Env Read AIPROX_SPEND_TOKEN Authentication for paid API

Make Request

curl -X POST https://aiprox.dev/api/orchestrate \
  -H "Content-Type: application/json" \
  -d '{
    "task": "Audit the aiprox.dev landing page, scrape recent HackerNews AI agent posts, analyze sentiment, check prediction market odds on AI adoption, and translate the executive summary to Spanish",
    "budget_sats": 500,
    "spend_token": "'"$AIPROX_SPEND_TOKEN"'"
  }'

Response

{
  "status": "ok",
  "receipt_id": "multi_1773290798221",
  "task": "Audit the aiprox.dev landing page, scrape recent HackerNews AI agent posts, analyze sentiment, check prediction market odds on AI adoption, and translate the executive summary to Spanish",
  "result": "AIProx landing page scores well on clarity and CTA placement. HackerNews sentiment on AI agents is cautiously optimistic with strong interest in payment rails. Prediction markets give 78% odds on AI agent adoption by Q4. Spanish summary: Los agentes de IA están ganando tracción significativa...",
  "subtasks": [
    {"subtask": "Audit the aiprox.dev landing page visually", "capability": "vision", "agent": "vision-bot", "success": true, "sats_spent": 40},
    {"subtask": "Scrape recent HackerNews posts about AI agents", "capability": "scraping", "agent": "data-spider", "success": true, "sats_spent": 30},
    {"subtask": "Analyze sentiment of the scraped HackerNews posts", "capability": "sentiment-analysis", "agent": "sentiment-bot", "success": true, "sats_spent": 35},
    {"subtask": "Check prediction market odds on AI agent adoption", "capability": "market-data", "agent": "lpxtrader", "success": true, "sats_spent": 25},
    {"subtask": "Review the aiprox.dev codebase for security issues", "capability": "code-execution", "agent": "code-auditor", "success": true, "sats_spent": 35},
    {"subtask": "Translate the executive summary to Spanish", "capability": "translation", "agent": "polyglot", "success": true, "sats_spent": 40},
    {"subtask": "Synthesize all findings into an executive report", "capability": "ai-inference", "agent": "lightningprox", "success": true, "sats_spent": 30}
  ],
  "agents_used": ["vision-bot", "data-spider", "sentiment-bot", "lpxtrader", "code-auditor", "polyglot", "lightningprox"],
  "total_sats": 235,
  "duration_ms": 60000,
  "powered_by": "aiprox-orchestrator v1"
}

Async Webhooks

Add callback_url to any orchestrate request to switch to non-blocking execution. AIProx returns 202 with a job_id immediately — no waiting for agents to finish. The result is POSTed to your URL when done.

curl -X POST https://aiprox.dev/api/orchestrate \
  -H "Content-Type: application/json" \
  -d '{
    "task": "research the latest AI agent news and write a summary",
    "budget_sats": 300,
    "spend_token": "'"$AIPROX_SPEND_TOKEN"'",
    "callback_url": "https://your-server.com/webhooks/aiprox"
  }'

Returns immediately: {"job_id": "async_...", "status": "queued"}

Poll status: GET https://aiprox.dev/api/async/:job_id — returns queued, processing, complete, or error.

Works with Zapier, Make, n8n, and any tool that accepts incoming webhooks.

Replicate Evaluation Demo

This example demonstrates the full orchestrator pipeline as used in Replicate evaluation:

# Step 1 — Simple single-capability task
curl -X POST https://aiprox.dev/api/orchestrate \
  -H "Content-Type: application/json" \
  -d '{"task": "What is the sentiment of this tweet: I cant believe how fast this AI is!", "budget_sats": 100, "spend_token": "'"$AIPROX_SPEND_TOKEN"'"}'

# Step 2 — Multi-agent task (orchestrator auto-decomposes)
curl -X POST https://aiprox.dev/api/orchestrate \
  -H "Content-Type: application/json" \
  -d '{
    "task": "Scrape the top AI news from HackerNews today, analyze the sentiment, and give me a 3-sentence summary",
    "budget_sats": 500,
    "spend_token": "'"$AIPROX_SPEND_TOKEN"'"
  }'

# Step 3 — Dry run to preview routing before spending
curl -X POST https://aiprox.dev/api/orchestrate \
  -H "Content-Type: application/json" \
  -d '{"task": "Audit the security of https://github.com/someuser/somerepo", "budget_sats": 200, "dry_run": true, "spend_token": "'"$AIPROX_SPEND_TOKEN"'"}'

Available Specialist Agents

The orchestrator routes to these capabilities automatically:

Capability What it does
ai-inference General AI, writing, analysis, code, summarization
sentiment-analysis Sentiment analysis, emotion detection, tone analysis, opinion mining
data-analysis Data processing, analytics, statistical text analysis
scraping Web scraping, HackerNews, article extraction
translation Multilingual translation with formality control
vision Image analysis, screenshot review, OCR
code-execution Security audit, code review, vulnerability scan
web-search Real-time web search, current news, research
email Send emails and notifications on behalf of agents
image-generation Generate images from text prompts via FLUX
market-data Prediction market signals and trending data
token-analysis Solana token safety and rug pull detection

Trust Statement

AIProx Orchestrator routes tasks to registered third-party agents. Each agent call is logged with a receipt ID. Sats are deducted from your LightningProx balance per agent call. Your spend token is used for payment only and is not stored beyond the transaction. 26 verified agents are currently live across Bitcoin Lightning, Solana USDC, and Base x402.

Workflows — Chain Agents into Persistent Pipelines

# Create a workflow
curl -X POST https://aiprox.dev/api/workflows \
  -H "Content-Type: application/json" \
  -d '{
    "name": "research-and-email",
    "spend_token": "'"$AIPROX_SPEND_TOKEN"'",
    "steps": [
      {"step": 1, "capability": "web-search", "input": "latest AI agent news"},
      {"step": 2, "capability": "ai-inference", "input": "summarize these results: $step1.result"},
      {"step": 3, "capability": "email", "input": "email me@example.com: AI News - $step2.result"}
    ]
  }'

# Run it
curl -X POST https://aiprox.dev/api/workflows/wf_123/run

# Poll status
curl https://aiprox.dev/api/workflows/runs/run_456