Mosaic-agent
Official@mosaic-agent
Offers specialized financial data ingestion, market signal processing, and technical engineering support for quantitative trading and software development environments.
Agent Skills by Mosaic-agent
Showing 15 vetted skills indexed across 1 GitHub repositories.
Mosaic-agentcommit
Draft conventional-commit messages for staged Git changes.
Mosaic-agentdata-engineering-importer
Automate historical data ingestion and ClickHouse schema maintenance for market data pipelines.
Mosaic-agentdsp-multi-asset-importer
Backfill and validate historical DSP Multi Asset holdings into market_data.mf_holdings.
Mosaic-agentmacro-strategy
Translate live market data and Mosaic signals into macro theses and regime classifications.
Mosaic-agentdaily-signal-composite
Aggregate six signal sources into a 0–100 composite score per ETF.
Mosaic-agentetf-news
Fetch ETF headlines and categorize them by category and sentiment.
Mosaic-agentgoldbees-pipeline
Generate ML-driven trading signals with Kelly-weighted positions and risk governance.
Mosaic-agentmacro-scanner
Scan Google News RSS and Yahoo Finance headlines for macro themes and ETF impacts.
Mosaic-agentrisk-governor
Compute volatility-targeted position weights from GARCH volatility and regime signals.
Mosaic-agentcaveman-help
Display a read-only caveman reference card of modes, skills, and activation triggers.
Mosaic-agentcaveman-review
Generate one-line code-review comments with line references from PR diffs.
Mosaic-agentcavecrew
Decide when to delegate tasks to caveman-style subagents for software engineering.
Mosaic-agentcaveman-stats
Report real token usage and estimated savings from Claude Code session logs.
Mosaic-agentcaveman
Compress model responses into caveman-style prose while preserving technical content.
Mosaic-agentcaveman-commit
Generate Conventional Commits messages with subjects up to 50 characters.
Frequently Asked Questions About Mosaic-agent
FAQPage SchemaWhat specific financial tasks can be performed using these capabilities?▼
You can ingest historical market data, validate multi-asset holdings, aggregate signal sources into ETF composite scores, and compute volatility-targeted position weights. These functions enable the generation of macro-strategy theses and the execution of risk-governed trading signals based on GARCH volatility models.
Which technical personas benefit from these engineering support functions?▼
Quantitative developers and financial engineers benefit from these functions. The suite provides specialized support for managing Git commit standards, performing automated code reviews on pull requests, and tracking token usage metrics to optimize development session costs.
What are the prerequisites for deploying these data and engineering functions?▼
Deployment requires an existing environment configured for market data ingestion, specifically supporting ClickHouse database schemas. Additionally, users must have access to Git repositories for commit generation and PR diff analysis, alongside connectivity to financial news RSS feeds for macro-theme scanning.