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Cypher query patterns for Company/entity data. Reference doc auto-loaded by neo4j-entity agent.
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SOC 職業分類に基づく
| name | entity-queries |
| description | Cypher query patterns for Company/entity data. Reference doc auto-loaded by neo4j-entity agent. |
| user-invocable | false |
Queries for Company, Sector, Industry, MarketIndex, and related market data (prices, dividends, splits).
MATCH (c:Company {ticker: $ticker})
RETURN c
MATCH (c:Company {ticker: $ticker})-[:BELONGS_TO]->(ind:Industry)-[:BELONGS_TO]->(sec:Sector)-[:BELONGS_TO]->(idx:MarketIndex)
RETURN c.ticker, c.name, ind.name AS industry, sec.name AS sector, idx.name AS market_index
MATCH (c:Company)-[:BELONGS_TO]->(ind:Industry)-[:BELONGS_TO]->(sec:Sector {name: $sector_name})
RETURN c.ticker, c.name, ind.name AS industry
ORDER BY c.ticker
MATCH (c:Company {ticker: $ticker})-[r:RELATED_TO]-(other:Company)
RETURN other.ticker, other.name, r.relationship_type
MATCH (m:MarketIndex)
RETURN m.ticker, m.name, m.etf
MATCH (n:News)-[r:INFLUENCES]->(m:MarketIndex {ticker: 'SPY'})
WHERE r.daily_macro IS NOT NULL AND abs(r.daily_macro) > 1.0
RETURN n.title, r.daily_macro, n.created
ORDER BY abs(r.daily_macro) DESC
LIMIT 20
MATCH (d:Date)-[p:HAS_PRICE]->(m:MarketIndex {ticker: 'SPY'})
WHERE d.date >= $start_date AND d.date <= $end_date
RETURN d.date, p.open, p.high, p.low, p.close, p.volume, p.daily_return
ORDER BY d.date
MATCH (d:Date)-[p:HAS_PRICE]->(c:Company {ticker: $ticker})
WHERE d.date >= $start_date AND d.date <= $end_date
RETURN d.date, p.open, p.high, p.low, p.close, p.volume, p.daily_return
ORDER BY d.date
MATCH (d:Date)-[p:HAS_PRICE]->(s:Sector {name: $sector_name})
WHERE d.date >= $start_date AND d.date <= $end_date
RETURN d.date, p.open, p.high, p.low, p.close, p.volume, p.daily_return
ORDER BY d.date
MATCH (d:Date)-[p:HAS_PRICE]->(c:Company {ticker: $ticker})
RETURN d.date, p.close, p.volume
ORDER BY d.date DESC
LIMIT 1
MATCH (c:Company {ticker: $ticker})-[:DECLARED_DIVIDEND]->(d:Dividend)
RETURN d.declaration_date, d.ex_dividend_date, d.pay_date,
d.cash_amount, d.dividend_type, d.frequency
ORDER BY d.declaration_date DESC
MATCH (c:Company {ticker: $ticker})-[:DECLARED_DIVIDEND]->(d:Dividend)
WHERE d.declaration_date >= $start_date AND d.declaration_date <= $end_date
RETURN d.declaration_date, d.cash_amount, d.dividend_type, d.frequency
ORDER BY d.declaration_date
MATCH (dt:Date)-[:HAS_DIVIDEND]->(d:Dividend)<-[:DECLARED_DIVIDEND]-(c:Company {ticker: $ticker})
WHERE dt.date >= $start_date AND dt.date <= $end_date
RETURN dt.date, d.cash_amount, d.dividend_type
ORDER BY dt.date
MATCH (c:Company {ticker: $ticker})-[:DECLARED_SPLIT]->(s:Split)
RETURN s.execution_date, s.split_from, s.split_to
ORDER BY s.execution_date DESC
MATCH (c:Company {ticker: $ticker})-[:DECLARED_SPLIT]->(s:Split)
WHERE s.execution_date >= $start_date AND s.execution_date <= $end_date
RETURN s.execution_date, s.split_from, s.split_to
MATCH (d:Date)
WHERE d.date >= $start_date AND d.date <= $end_date
AND d.is_trading_day = '1'
RETURN d.date, d.market_open_current_day, d.market_close_current_day
ORDER BY d.date
MATCH (d:Date {date: $date})-[:NEXT]->(next:Date)
WHERE next.is_trading_day = '1'
RETURN next.date AS next_trading_day
MATCH (c:Company) WHERE c.sector IS NOT NULL
RETURN c.ticker, c.name, c.sector, c.industry, c.mkt_cap
ORDER BY c.sector, c.ticker LIMIT 20
MATCH (c:Company)-[:DECLARED_SPLIT]->(s:Split)
RETURN c.ticker, s.split_from, s.split_to, s.execution_date
ORDER BY s.execution_date DESC
MATCH (c:Company)
WHERE c.sector IS NULL OR c.industry IS NULL OR c.mkt_cap IS NULL OR c.employees IS NULL
RETURN c.ticker, c.name,
CASE WHEN c.sector IS NULL THEN 'Missing' ELSE c.sector END as sector,
CASE WHEN c.industry IS NULL THEN 'Missing' ELSE c.industry END as industry,
CASE WHEN c.mkt_cap IS NULL THEN 'Missing' ELSE c.mkt_cap END as mkt_cap,
CASE WHEN c.employees IS NULL THEN 'Missing' ELSE c.employees END as employees
LIMIT 20
MATCH (c:Company)
WHERE c.mkt_cap IS NOT NULL
AND toFloat(replace(c.mkt_cap, ',', '')) > 10000000000
RETURN c.ticker, c.name, c.mkt_cap, c.sector
ORDER BY toFloat(replace(c.mkt_cap, ',', '')) DESC LIMIT 20
MATCH (c:Company)-[:DECLARED_DIVIDEND]->(d:Dividend)
WHERE LOWER(d.frequency) = 'quarterly'
WITH c, COUNT(d) as dividend_count
WHERE dividend_count > 2
RETURN c.ticker, c.name, dividend_count
ORDER BY dividend_count DESC LIMIT 20
MATCH (c:Company)-[:DECLARED_DIVIDEND]->(d:Dividend)
WHERE datetime(d.declaration_date) > datetime() - duration('P180D')
AND d.cash_amount IS NOT NULL
RETURN c.ticker, d.cash_amount, d.ex_dividend_date, d.pay_date, d.dividend_type
ORDER BY toFloat(d.cash_amount) DESC LIMIT 20
MATCH (d:Date)-[:HAS_SPLIT]->(s:Split)<-[:DECLARED_SPLIT]-(c:Company)
RETURN c.ticker, d.date, s.split_from, s.split_to, s.execution_date
ORDER BY d.date DESC
MATCH (c:Company) WHERE c.sector = 'Technology'
RETURN c.ticker, c.name, c.industry, c.mkt_cap
ORDER BY toFloat(replace(c.mkt_cap, ',', '')) DESC LIMIT 50
MATCH (c:Company)-[:DECLARED_DIVIDEND]->(d:Dividend)
WHERE datetime(d.declaration_date) > datetime() - duration('P90D')
RETURN c.ticker, d.cash_amount, d.ex_dividend_date, d.pay_date
ORDER BY d.declaration_date DESC LIMIT 20
MATCH (m:MarketIndex)
OPTIONAL MATCH (m)<-[:BELONGS_TO]-(s:Sector)
OPTIONAL MATCH (m)<-[:BELONGS_TO]-(i:Industry)
OPTIONAL MATCH (m)<-[:BELONGS_TO]-(c:Company)
RETURN m.ticker, m.name,
COUNT(DISTINCT s) as sector_count,
COUNT(DISTINCT i) as industry_count,
COUNT(DISTINCT c) as company_count
ORDER BY m.ticker
MATCH (c:Company)-[:DECLARED_SPLIT]->(s:Split)
WHERE datetime(s.execution_date) > datetime() - duration('P365D')
RETURN c.ticker, s.split_from, s.split_to, s.execution_date
ORDER BY s.execution_date DESC LIMIT 10
Queries for PIT (Point-in-Time) mode. All use Date.market_close_current_day normalized to strict ISO8601 as available_at. Pass pit in the params dict alongside other Cypher parameters.
Normalization: market_close_current_day format is "YYYY-MM-DD HH:MM:SS±HHMM". Convert to ISO8601:
replace(d.market_close_current_day, ' ', 'T') → "YYYY-MM-DDTHH:MM:SS±HHMM"
left(s, size(s)-2) + ':' + right(s, 2) → "YYYY-MM-DDTHH:MM:SS±HH:MM"
MATCH (d:Date)-[p:HAS_PRICE]->(c:Company {ticker: $ticker})
WHERE d.market_close_current_day IS NOT NULL
WITH d, p, replace(d.market_close_current_day, ' ', 'T') AS raw
WITH d, p, left(raw, size(raw)-2) + ':' + right(raw, 2) AS norm_close
WHERE norm_close <= $pit
WITH norm_close, d, p ORDER BY d.date DESC
WITH collect({
available_at: norm_close,
available_at_source: 'time_series_timestamp',
date: d.date,
open: p.open,
high: p.high,
low: p.low,
close: p.close,
volume: p.volume
}) AS items
RETURN items AS data, [] AS gaps
MATCH (d:Date)-[p:HAS_PRICE]->(c:Company {ticker: $ticker})
WHERE d.market_close_current_day IS NOT NULL
AND d.date >= $start_date
WITH d, p, replace(d.market_close_current_day, ' ', 'T') AS raw
WITH d, p, left(raw, size(raw)-2) + ':' + right(raw, 2) AS norm_close
WHERE norm_close <= $pit
WITH norm_close, d, p ORDER BY d.date
WITH collect({
available_at: norm_close,
available_at_source: 'time_series_timestamp',
date: d.date,
open: p.open,
high: p.high,
low: p.low,
close: p.close,
volume: p.volume
}) AS items
RETURN items AS data, [] AS gaps
MATCH (d:Date)-[p:HAS_PRICE]->(c:Company {ticker: $ticker})
WHERE d.market_close_current_day IS NOT NULL
WITH d, p, replace(d.market_close_current_day, ' ', 'T') AS raw
WITH d, p, left(raw, size(raw)-2) + ':' + right(raw, 2) AS norm_close
WHERE norm_close <= $pit
WITH norm_close, d, p ORDER BY d.date DESC LIMIT 1
WITH collect({
available_at: norm_close,
available_at_source: 'time_series_timestamp',
date: d.date,
open: p.open,
high: p.high,
low: p.low,
close: p.close,
volume: p.volume
}) AS items
RETURN items AS data, [] AS gaps
MATCH (d:Date)-[:HAS_DIVIDEND]->(div:Dividend)<-[:DECLARED_DIVIDEND]-(c:Company {ticker: $ticker})
WHERE d.market_close_current_day IS NOT NULL
WITH d, div, replace(d.market_close_current_day, ' ', 'T') AS raw
WITH d, div, left(raw, size(raw)-2) + ':' + right(raw, 2) AS norm_close
WHERE norm_close <= $pit
WITH norm_close, d, div ORDER BY d.date DESC
WITH collect({
available_at: norm_close,
available_at_source: 'time_series_timestamp',
date: d.date,
declaration_date: div.declaration_date,
cash_amount: div.cash_amount,
dividend_type: div.dividend_type,
frequency: div.frequency
}) AS items
RETURN items AS data, [] AS gaps
MATCH (d:Date)-[:HAS_SPLIT]->(sp:Split)<-[:DECLARED_SPLIT]-(c:Company {ticker: $ticker})
WHERE d.market_close_current_day IS NOT NULL
WITH d, sp, replace(d.market_close_current_day, ' ', 'T') AS raw
WITH d, sp, left(raw, size(raw)-2) + ':' + right(raw, 2) AS norm_close
WHERE norm_close <= $pit
WITH norm_close, d, sp ORDER BY d.date DESC
WITH collect({
available_at: norm_close,
available_at_source: 'time_series_timestamp',
date: d.date,
execution_date: sp.execution_date,
split_from: sp.split_from,
split_to: sp.split_to
}) AS items
RETURN items AS data, [] AS gaps
available_at from Date.market_close_current_day (normalize space→T, insert colon in offset)WHERE d.market_close_current_day IS NOT NULL (gaps 21 holiday + 44 orphan dividends)norm_close <= $pit (boundary-inclusive; items at PIT are valid)daily_return from HAS_PRICE in PIT envelope — use raw OHLCV onlyavailable_at_source: 'time_series_timestamp'collect({...}) to produce data[] arrayRETURN items AS data, [] AS gapspit in the params dict alongside other Cypher parameterspit — open mode pass-through{"data":[],"gaps":[]} passes the gateCompany.ticker has no index but count is small (~796); exact match scans are acceptable.HAS_PRICE relationship contains OHLCV data as properties.daily_return on HAS_PRICE is a percentage (5.06 means 5.06%).Company.mkt_cap is stored as numeric string with commas (e.g., "81,035,171,840").| Date | Gap | Affected | Mitigation |
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Version 1.1 | 2026-01-11 | Added self-improvement protocol
Predict stock direction post 8-K earnings & refine using 10-Q/10-K outcomes
Predict stock direction after an 8-K earnings release from a prebuilt earnings context bundle
Post-event causal attribution — explains why a stock moved after 8-K earnings, compares against prediction, writes reusable lessons for future predictions. Production invocation via SDK embed (main session), not fork.
Core Neo4j schema reference with all labels, relationships, data types, and indexes. Use when exploring database structure, checking field types, or understanding the financial knowledge graph schema.
V1105_LONGDESC_START_MARKER. This skill tests v2.1.105's skill-description cap raise from 250 to 1536 characters. If this description appears truncated in the skill listing system-reminder at around character 250, the cap was not raised; if it appears truncated at around 1536, the cap was raised correctly per changelog. The test sentinel markers are placed at specific character offsets: V1105_OFFSET_100 is at char 100 approximately, V1105_OFFSET_300 is at char 300 approximately (old cap would truncate this), V1105_OFFSET_700 is at char 700 approximately, V1105_OFFSET_1000 is at char 1000, V1105_OFFSET_1200 is at char 1200, V1105_OFFSET_1400 is at char 1400, and V1105_END_MARKER is the last visible sentinel. This description also contains deliberately redundant filler to reach the target length without substantive content since the purpose is only to verify truncation behavior rather than to provide meaningful guidance. filler filler filler filler filler filler filler filler filler filler filler filler filler
Child skill for v2.1.107 nesting retest — writes marker and returns