home / skills / openclaw / skills / quiver

quiver skill

/skills/stuhorsman/quiver

This skill retrieves Quiver Quantitative data on congress trades, lobbying, contracts, and insiders to help track political market signals.

npx playbooks add skill openclaw/skills --skill quiver

Review the files below or copy the command above to add this skill to your agents.

Files (3)
SKILL.md
1.6 KB
---
name: quiver
description: Query alternative financial data from Quiver Quantitative (Congress trading, Lobbying, Government Contracts, Insider transactions). Use this to track politician stock trades or unconventional market signals.
---

# Quiver Quantitative Skill

Access alternative data sets from Quiver Quantitative to track non-traditional market signals.

## Prerequisites

- **API Token:** You need a Quiver Quantitative API token.
- **Environment:** Set `QUIVER_API_KEY` in your environment or `TOOLS.md`.

## Usage

This skill uses a Python script to fetch data and return it as JSON.

### Congress Trading
Track stock trades by US Senators and Representatives.

```bash
# Recent trades by all members
skills/quiver/scripts/query_quiver.py congress

# Specific Ticker
skills/quiver/scripts/query_quiver.py congress --ticker NVDA

# Specific Politician
skills/quiver/scripts/query_quiver.py congress --politician "Nancy Pelosi"
```

### Corporate Lobbying
Track lobbying spend by companies.

```bash
skills/quiver/scripts/query_quiver.py lobbying AAPL
```

### Government Contracts
Track government contracts awarded to companies.

```bash
skills/quiver/scripts/query_quiver.py contracts LMT
```

### Insider Trading
Track corporate insider transactions.

```bash
skills/quiver/scripts/query_quiver.py insiders TSLA
```

## Output

All commands output a JSON array of records. You can pipe this to `jq` to filter or format it.

```bash
# Get Pelosi's recent NVDA trades
skills/quiver/scripts/query_quiver.py congress --politician "Nancy Pelosi" | jq '.[] | select(.Ticker == "NVDA")'
```

Overview

This skill queries alternative financial datasets from Quiver Quantitative to surface unconventional market signals like Congress trading, corporate lobbying, government contracts, and insider transactions. It returns structured JSON that you can filter, analyze, or pipe into other tools. Use it to monitor politician stock activity, corporate influence, and non-traditional drivers of market moves.

How this skill works

The skill calls Quiver Quantitative endpoints using your QUIVER_API_KEY and returns JSON arrays of records for each data category. It supports targeted queries by ticker, politician, or company and outputs raw records ready for further filtering or ingestion. Commands are executed via a lightweight Python script that accepts subcommands like congress, lobbying, contracts, and insiders.

When to use it

  • Investigating unusual stock moves potentially tied to political activity.
  • Monitoring lobbying spend trends for a specific company or sector.
  • Checking awarded government contracts that may affect revenue forecasts.
  • Tracking insider transactions to detect management buy/sell signals.
  • Feeding alternative datasets into quant models or research pipelines.

Best practices

  • Store your QUIVER_API_KEY securely in environment variables and rotate it periodically.
  • Filter results locally (jq or Python) before feeding into downstream models to reduce noise.
  • Combine datasets (e.g., congress trades + contracts) to corroborate signals.
  • Rate-limit and cache responses if running automated or frequent queries.
  • Validate returned JSON fields against expected keys before downstream processing.

Example use cases

  • Fetch recent Congress trades and filter for a target ticker to check for politically linked activity.
  • Pull lobbying spend history for AAPL to assess regulatory influence over time.
  • Retrieve government contract awards for a defense contractor ahead of earnings or bid decisions.
  • Aggregate insider transaction records to compute net insider buys/sells by company.

FAQ

What do I need to run this skill?

You need a Quiver Quantitative API token set in QUIVER_API_KEY and Python available to run the script.

What format does the skill return?

All queries return a JSON array of records that you can pipe to jq or parse in code.