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unixlamadev-spec

Aiprox Workflows

by unixlamadev-spec · GitHub ↗ · v1.0.1 · MIT-0
cross-platform ✓ Security Clean
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Install in OpenClaw
/install aiprox-workflows
Description
Create and run multi-agent AI workflows on AIProx. Chain agents into scheduled pipelines. Pay per execution in sats.
README (SKILL.md)

\r \r

AIProx Workflows\r

\r AIProx Workflows is a multi-agent pipeline engine. Chain AI agents into named workflows, schedule them to run on a cron, and get results delivered by email or webhook. Pay per execution in sats — no subscriptions, no monthly fees.\r \r

When to Use\r

\r

  • Building automated pipelines that chain multiple AI agents\r
  • Scheduling recurring tasks (daily news digest, competitive intel, market signals)\r
  • Running one-off multi-step pipelines on demand\r
  • Any workflow where one agent's output feeds into the next\r \r

MCP Tools\r

\r

create_workflow\r

\r Create a named pipeline with ordered agent steps.\r \r

Create a workflow "daily-crypto-brief" that searches Bitcoin news, analyzes sentiment, and emails a summary @daily\r
```\r
\r
Step chaining: use `$step1.result`, `$step2.result`, etc. to pass outputs forward.\r
\r
**Available capabilities:**\r
\r
| Capability | What it does |\r
|---|---|\r
| `web-search` | Real-time web search via search-bot |\r
| `sentiment-analysis` | Sentiment and tone analysis via sentiment-bot |\r
| `scraping` | Web scraping and article extraction via data-spider |\r
| `data-analysis` | Data processing and text analysis via doc-miner |\r
| `translation` | Multilingual translation via polyglot |\r
| `vision` | Image/screenshot analysis via vision-bot |\r
| `code-execution` | Code audit and security review via code-auditor |\r
| `email` | Send email notifications via email-bot |\r
| `market-data` | Prediction market signals via market-oracle |\r
| `token-analysis` | Solana token safety and rug detection via isitarug |\r
\r
### `run_workflow`\r
\r
Trigger any workflow by its ID.\r
\r
```\r
Run workflow wf_abc123\r
```\r
\r
### `list_workflows`\r
\r
Show all workflows for the current spend token.\r
\r
```\r
List my workflows\r
```\r
\r
### `get_run_history`\r
\r
Show past execution results, sats spent, and step-by-step output.\r
\r
```\r
Show run history for wf_abc123\r
```\r
\r
### `delete_workflow`\r
\r
Delete a workflow (cancels scheduled runs).\r
\r
### `run_template`\r
\r
Run a pre-built template by name in one shot.\r
\r
```\r
Run the polymarket-signals template and email me at [email protected]\r
```\r
\r
## Pre-Built Templates\r
\r
| Template name | Pipeline | Cost |\r
|---|---|---|\r
| `news-digest` | search-bot → sentiment-bot → email-bot | ~150 sats/run |\r
| `token-scanner` | data-spider → isitarug → email-bot | ~120 sats/run |\r
| `competitive-intel` | search-bot → doc-miner → sentiment-bot → email-bot | ~200 sats/run |\r
| `multilingual-content` | data-spider → doc-miner → polyglot | ~180 sats/run |\r
| `site-audit` | vision-bot → code-auditor → doc-miner | ~220 sats/run |\r
| `polymarket-signals` | market-oracle → sentiment-bot → email-bot | ~160 sats/run |\r
\r
## Authentication\r
\r
Set `AIPROX_SPEND_TOKEN` in your MCP server config. Get a spend token at [lightningprox.com](https://lightningprox.com).\r
\r
```json\r
{\r
  "mcpServers": {\r
    "aiprox-workflows": {\r
      "command": "npx",\r
      "args": ["aiprox-workflows-mcp"],\r
      "env": {\r
        "AIPROX_SPEND_TOKEN": "lnpx_your_token_here"\r
      }\r
    }\r
  }\r
}\r
```\r
\r
## Scheduling\r
\r
| Shorthand | When |\r
|---|---|\r
| `@hourly` | Every hour |\r
| `@daily` | Every day at midnight |\r
| `@weekly` | Every Sunday |\r
| `0 9 * * 1-5` | 9am Monday–Friday |\r
\r
## Pricing\r
\r
50–220 sats per workflow execution depending on agents used. No monthly plan. Deducted from your Lightning spend token balance.\r
\r
## Behavior Guidelines\r
\r
**When a user asks to automate something:**\r
1. Identify which capabilities are needed (search → analyze → notify is the common pattern)\r
2. Suggest a template if one matches, otherwise offer to create a custom workflow\r
3. Confirm the schedule and email/webhook if they want recurring runs\r
4. After creating, offer to run it immediately\r
\r
**Cost transparency:**\r
- Mention estimated sats cost before creating/running\r
- Report `sats_spent` after each run\r
\r
**Check templates first:**\r
If the task matches a template, use `run_template` — it's faster and pre-configured.\r
\r
## Links\r
\r
- Dashboard: [aiprox.dev/workflows](https://aiprox.dev/workflows)\r
- Templates: [aiprox.dev/templates](https://aiprox.dev/templates)\r
- Registry: [aiprox.dev/registry.html](https://aiprox.dev/registry.html)\r
- npm SDK: `npm install aiprox-workflows`\r
- MCP server: `npx aiprox-workflows-mcp`\r
Usage Guidance
This skill is coherent with its stated purpose, but before installing consider: (1) Treat AIPROX_SPEND_TOKEN as a sensitive spend-only credential; ask whether the token can be scoped/limited and whether revocation is easy. (2) Confirm whether the agent will run workflows autonomously by default and what user consent/confirmation is required before each paid run — if you want to avoid unexpected charges, disable autonomous invocation or require explicit approval. (3) Verify the external domains mentioned (aiprox.dev, lightningprox.com) and the npm package (aiprox-workflows) before installing any adapter. (4) Start by creating/running a single test workflow and monitor run_history and sats_spent; set strict budget caps if the service supports them. (5) If you need stronger guarantees, ask the provider how emails/webhooks are sent/stored and whether sensitive data processed in workflows is retained or accessible to third parties.
Capability Analysis
Type: OpenClaw Skill Name: aiprox-workflows Version: 1.0.1 The aiprox-workflows skill bundle provides a legitimate interface for managing multi-agent AI pipelines via the AIProx service. It includes tools for creating, running, and monitoring workflows that utilize capabilities like web searching, scraping, and sentiment analysis, with payments handled via a Lightning Network spend token (AIPROX_SPEND_TOKEN). The SKILL.md instructions are well-structured behavioral guidelines that focus on cost transparency and user assistance, with no evidence of malicious intent, data exfiltration, or harmful prompt injection.
Capability Assessment
Purpose & Capability
The name/description (multi-agent workflow engine with per-run payments) matches the manifest and SKILL.md: it requires a spend token and documents workflow creation, running, scheduling, templates, and agent capabilities. The listed capabilities (search, scraping, sentiment, email, market data, token-analysis, code-audit, etc.) are consistent with a pipeline/orchestration product that delegates work to specialized agents.
Instruction Scope
SKILL.md contains explicit instructions for creating/running/listing/deleting workflows, scheduling, and cost reporting. It instructs the operator to place AIPROX_SPEND_TOKEN in the MCP server config and to use npx/aiprox-workflows-mcp for the MCP adapter. It does not instruct the agent to read unrelated files or arbitrary environment variables, nor to exfiltrate data to unexpected endpoints beyond email/webhook outputs described in the doc.
Install Mechanism
This is an instruction-only skill (no install spec or code shipped). The docs reference an npm package and an MCP adapter command (npx aiprox-workflows-mcp / npm install aiprox-workflows) but provide no automated installer in the manifest — this is consistent but means installing the adapter is a manual step the user must perform from external registries.
Credentials
Only AIPROX_SPEND_TOKEN is required, which is proportionate to a billed workflow service. This token is a financial credential (spend token) and should be treated as highly sensitive; the skill doesn't request unrelated tokens or system credentials.
Persistence & Privilege
always:false (not force-installed). The platform-default ability for the agent to invoke the skill autonomously remains enabled — combined with a spend token this creates a real financial risk (the agent could trigger paid runs). The manifest does not request other privileged system access or modify other skills' config.
How to Use
  1. Make sure OpenClaw is installed (local or Docker)
  2. Run the install command in chat: /install aiprox-workflows
  3. After installation, invoke the skill by name or use /aiprox-workflows
  4. Provide required inputs per the skill's parameter spec and get structured output
Version History
v1.0.1
Version 1.0.1 of aiprox-workflows - No file changes detected in this release. - Documentation, features, and usage remain unchanged from the previous version.
v1.0.0
Initial release: Multi-agent AI workflow pipelines for AIProx. - Create, schedule, and manage multi-step workflows that chain AI agents (e.g., search, analytics, email). - Includes commands for workflow creation, running, listing, history, deletion, and template use. - Supports pre-built templates for common use cases (news digest, token scan, competitive intelligence, more). - Pay per execution in sats; no subscriptions, transparent pricing shown for each action. - Requires AIPROX_SPEND_TOKEN for authentication; provides setup instructions. - Documentation includes scheduling, behavior guidelines, and links to dashboard and SDK.
Metadata
Slug aiprox-workflows
Version 1.0.1
License MIT-0
All-time Installs 2
Active Installs 2
Total Versions 2
Frequently Asked Questions

What is Aiprox Workflows?

Create and run multi-agent AI workflows on AIProx. Chain agents into scheduled pipelines. Pay per execution in sats. It is an AI Agent Skill for Claude Code / OpenClaw, with 248 downloads so far.

How do I install Aiprox Workflows?

Run "/install aiprox-workflows" in the OpenClaw or Claude Code chat to install it in one step — no extra setup required.

Is Aiprox Workflows free?

Yes, Aiprox Workflows is completely free, licensed under MIT-0. You can download, install and use it at no cost.

Which platforms does Aiprox Workflows support?

Aiprox Workflows is cross-platform and runs anywhere OpenClaw / Claude Code is available (cross-platform).

Who created Aiprox Workflows?

It is built and maintained by unixlamadev-spec (@unixlamadev-spec); the current version is v1.0.1.

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