signal-pipeline

Route and validate discovery signals into the trading workflow.

Updated Aug 23, 2026
One-click install
npx skills add https://github.com/wrensignal/wrenOS --skill signal-pipeline
Or copy as Structured Prompt for Agent
Please help me install this Agent Skill.
Skill: signal-pipeline
Source: https://github.com/wrensignal/wrenOS/tree/main/packs/core-skills-pack/signal-pipeline
Command: npx skills add https://github.com/wrensignal/wrenOS --skill signal-pipeline

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

The signal-pipeline unifies the flow of research outputs into the trading workflow by handling inbox routing, schema validation, delivery tracking, and retention, ensuring signals reach the appropriate trading components without manual handoffs or data loss.

Core Features & Use Cases

  • Inbox Routing: moves output files from research skills into the trading agent's inbox in multi-agent setups.
  • Schema Validation: enforces required fields and data formats to maintain a clean, auditable signal stream.
  • Delivery Tracking: provides end-to-end visibility from production to consumption, enabling reliable backtests and decisions.
  • Data Retention & Snapshots: manages archival policies and optional state snapshots for reproducibility.
  • Health & Auditability: monitors pipeline health and generates artifacts for monitoring dashboards.

Quick Start

Configure your workspace and start the signal-pipeline to route discovery outputs to the trading inbox.

Frequently Asked Questions about signal-pipeline

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I automate routing research signals to a trading workflow?

To automate research signal routing, you configure a pipeline that moves discovery outputs from research skills into the trading inbox. The signal-pipeline handles this by validating schemas, tracking delivery, and managing retention without manual handoffs.

What is schema validation for trading signals and why do I need it?

Schema validation for trading signals enforces required fields and data formats to maintain a clean, auditable signal stream. It ensures that discovery signals meet strict data contracts before reaching trading components, preventing malformed data from disrupting downstream execution.

How do I track delivery and monitor health for data pipelines in a multi-agent setup?

Tracking delivery in a multi-agent setup requires end-to-end visibility from signal production to consumption. The pipeline provides delivery tracking and health monitoring artifacts, ensuring deterministic file delivery and generating outputs for monitoring dashboards.

Does the signal-pipeline work with multi-agent setups for inbox management?

Yes, the pipeline operates across both single-agent and multi-agent setups. It handles inbox management by routing output files directly into the trading agent's inbox, satisfying deterministic file delivery and configurable retention policies.

How do I configure data retention and state snapshots for reproducible backtests?

Configuring data retention and snapshots involves setting archival policies within your pipeline configuration. The signal-pipeline manages these policies to preserve historical signals and optional state snapshots, enabling reliable backtests and reproducibility.

What is the best way to ensure auditability for research signal routing?

Ensuring auditability for signal routing requires enforcing schema checks and generating health artifacts. The pipeline provides delivery tracking and monitors pipeline health, creating an auditable trail from research production to trading consumption.