Delegate independent tasks to specialized agents working concurrently with isolated context.
Get Benzinga News
get-bz-news
Fetch Benzinga news with significant daily returns from Neo4j
SKILL.md
Full skill instructions
Get Benzinga News
Fetch news where |daily_adj| >= threshold. Default threshold is 1.5σ of trailing adjusted volatility.
Arguments
$ARGUMENTS = TICKER START_DATE END_DATE [THRESHOLD]
- THRESHOLD optional:
1.5s(default),2s, or fixed like3(percent)
Example: AAPL 2024-01-01T00:00:00 2024-04-01T00:00:00
Steps
Step 1: Calculate Volatility
MATCH (d:Date)-[r:HAS_PRICE]->(c:Company {ticker: $ticker})
WHERE d.date >= date($start) - duration('P365D') AND d.date < date($start)
MATCH (d)-[m:HAS_PRICE]->(idx:MarketIndex {ticker: 'SPY'})
WHERE r.daily_return IS NOT NULL AND m.daily_return IS NOT NULL
RETURN stdev(r.daily_return - m.daily_return) AS adj_vol, count(*) AS days
Fail if < 60 days: Return INSUFFICIENT_HISTORY: {days} days (need 60+)
Step 2: Compute Threshold
Parse THRESHOLD argument:
1.5s→threshold = 1.5 × adj_vol(default)2s→threshold = 2.0 × adj_vol3→threshold = 3.0(fixed percent, ignore volatility)
Step 3: Fetch News
Use threshold and adj_vol as literal parameters (no subquery):
MATCH (n:News)-[inf:INFLUENCES]->(c:Company {ticker: $ticker})
WHERE n.created >= $start AND n.created < $end
AND inf.daily_stock IS NOT NULL AND inf.daily_macro IS NOT NULL
AND abs(inf.daily_stock - inf.daily_macro) >= $threshold
RETURN n.id AS news_id,
n.created AS date,
n.title AS title,
n.teaser AS teaser,
n.body AS body,
n.market_session AS market_session,
inf.daily_stock AS daily_stock,
(inf.daily_stock - inf.daily_macro) AS daily_adj,
(inf.daily_stock - inf.daily_sector) AS sector_adj,
(inf.daily_stock - inf.daily_industry) AS industry_adj,
abs(inf.daily_stock - inf.daily_macro) / $adj_vol AS z_score
ORDER BY n.created ASC
Output
Return JSON with:
query: parameters used (ticker, dates, threshold_pct, adj_vol)results: array of news items with z_score
If no results: NO_NEWS_FOUND
More Other skills
brand-guidelines
Applies Anthropic's official brand colors and typography to any sort of artifact that may benefit from having Anthropic's look-and-feel. Use it when brand colors or style guidelines, visual formatting, or company design standards apply.
theme-factory
Toolkit for styling artifacts with a theme. These artifacts can be slides, docs, reportings, HTML landing pages, etc. There are 10 pre-set themes with colors/fonts that you can apply to any artifact that has been creating, or can generate a new theme on-the-fly.
internal-comms
A set of resources to help me write all kinds of internal communications, using the formats that my company likes to use. Claude should use this skill whenever asked to write some sort of internal communications (status reports, leadership updates, 3P updates, company newsletters, FAQs, incident reports, project updates, etc.).
Fundamental design principles for writing maintainable, testable Python code.
responsive-design
Modern responsive layouts using container queries, fluid typography, CSS Grid, and mobile-first strategies.
Generate Playwright tests from scenarios using interactive browser exploration and validation.
Automated website exploration and test case generation using Playwright.
Modern React state management with Redux Toolkit, Zustand, Jotai, and React Query for every state category.
gdpr-data-handling
GDPR-compliant data handling with consent management, data subject rights, and privacy controls.
Python error handling patterns including input validation, exception hierarchies, and partial failure handling. Use when implementing validation logic, designing exception strategies, handling batch processing failures, or building robust APIs.
refactor-plan
Detailed multi-file refactor planning with safety checks and rollback guidance.
