PM schema overview edits

Author: dev-dist

src/content/data-streams/reference/report-schema-overview.mdx

@@ -50,36 +50,36 @@ Below is a summary of all available Data Streams report schemas, their main use
 
 ## Cryptocurrency Report Schema
 
-[Chainlink Cryptocurrency Reports](./report-schema-v3) provide market data for digital assets, supporting high-frequency, onchain use cases. Each report includes a consensus price (`price`), as well as simulated bid (`bid`) and ask (`ask`) prices that estimate the impact of buying or selling at a specified liquidity depth. These values help protocols and applications understand current market conditions and potential slippage for larger trades.
+[Chainlink Cryptocurrency Reports](./report-schema-v3) provide market data for digital assets, supporting high-frequency, onchain use cases. Each report includes a consensus mid price (`price`), as well as simulated bid (`bid`) and ask (`ask`) prices that estimate the impact of buying or selling at a specified liquidity depth. These values help protocols and applications understand current market conditions and potential slippage for larger trades.
 
 For a deeper explanation of how liquidity-weighted bid and ask prices work, see [Liquidity-Weighted Bid-Ask Prices (LWBA)](../concepts/liquidity-weighted-prices).
 
 ## DEX State Price Report Schema
 
 [Chainlink DEX State Price Reports](./report-schema-v3-dex) are designed for assets that derive most or all of their liquidity from decentralized exchanges (DEXs). Unlike standard crypto price streams, these reports use onchain market data to reflect the unique conditions of AMM pools and DEX-dominant tokens. In this report, the `price`, `bid`, and `ask` fields are all equal, representing the execution price a trader would receive based on the current state of onchain liquidity pools, rather than order-book mechanics. This approach enables accurate, real-time pricing, even for long-tail or newly launched tokens in low-volume environments.
 
-[The DEX State Price methodology](/data-streams/concepts/dex-state-price-streams#high-level-outline-of-the-dex-state-price-methodology) aggregates data from multiple DEX pools, applies volume and TVL-based weighting, using filters to reduce manipulation and smooth volatility. Users should be aware of the specific risks inherent to DeFi, such as smart contract vulnerabilities, bridge dependencies, and external price manipulation. It is important to review [risk mitigation guidance](/data-streams/concepts/dex-state-price-streams#risk-mitigation) and adjust protocol parameters accordingly when integrating DEX State Price Reports.
+[The DEX State Price methodology](/data-streams/concepts/dex-state-price-streams#high-level-outline-of-the-dex-state-price-methodology) aggregates data from multiple DEX pools, applies volume and TVL-based weighting, and uses filters to reduce manipulation and smooth volatility. Users should be aware of the specific risks inherent to DeFi, such as smart contract vulnerabilities, bridge dependencies, and external price manipulation. It is important to review [risk mitigation guidance](/data-streams/concepts/dex-state-price-streams#risk-mitigation) and adjust protocol parameters accordingly when integrating DEX State Price Reports.
 
 For more details on the methodology and risk considerations, see [DEX State Price Streams](../concepts/dex-state-price-streams).
 
 ## Real World Asset (RWA) Report Schema
 
-[Chainlink RWA Data Streams](./report-schema-v8) provide fresh, reliable, and accurate financial market data for tokenized real-world assets, enabling DeFi users to gain onchain exposure to physical assets. Each report includes a staleness measure (`lastUpdateTimestamp`), consensus median price (`midPrice`) and market status (`marketStatus`).
+[Chainlink RWA Data Streams](./report-schema-v8) provide fresh, reliable, and accurate financial market data for real-world assets, enabling DeFi users to gain onchain exposure to physical assets. Each report includes a staleness measure (`lastUpdateTimestamp`), consensus median price (`midPrice`) and market status (`marketStatus`).
 
-RWA assets trade on traditional exchanges during [market hours](../market-hours). These market hours depend per asset class and can be subject to unexpected halts, pauses and other behaviors affecting traditional markets. For this reason, this class of Data Streams contains a market hours flag and a staleness measure to equip our users to handle these events correctly. It is critical that users implement correct safeguards on their side to pause markets, add more conservative risk caps, or do whatever else is appropriate for their application.
+RWA assets trade on traditional exchanges during [market hours](../market-hours). These market hours vary by asset class and can be subject to unexpected halts, pauses and other behaviors affecting traditional markets. For this reason, this class of Data Streams contains a market hours flag and a staleness measure to equip our users to handle these events correctly. It is critical that users implement correct safeguards on their end to pause markets, add more conservative risk caps, or do whatever else is appropriate for their application.
 
 ## Net Asset Value (NAV) Report Schema
 
-[Chainlink NAV Data Streams](./report-schema-v9) provide real-time, tamper-proof access to the Net Asset Value (`navPerShare`) of tokenized assets, funds, or portfolios, delivered over the low latency, high frequency Chainlink Data Streams infrastructure. Each report includes NAV per share (`navPerShare`), NAV date (`navDate`), assets under management (`aum`), ripcord status (`ripcord`).
+[Chainlink NAV Data Streams](./report-schema-v9) provide real-time, tamper-proof access to the Net Asset Value (`navPerShare`) of tokenized assets, funds, or portfolios, delivered over the low latency, high frequency Chainlink Data Streams infrastructure. Each report includes NAV per share (`navPerShare`), NAV date (`navDate`), assets under management (`aum`), and ripcord status (`ripcord`). The ripcord is set to true (`1`) by the asset issuer when the consumer should ignore the value being sent (for cases such as maintenance, upstream data source outages, etc). The feed data will remain stale until the ripcord returns false (`0`).
 
 NAV is a fundamental financial metric that represents the value of an investment vehicle such as a mutual fund or ETF and is calculated as the total assets minus the total liabilities.
 
 Data Streams ensures that any NAV update, whenever it occurs, is captured and made available immediately and at low latency, allowing for seamless integration with onchain applications alongside other real-time data streams. Although the NAV value may not change frequently, Data Streams provides the most recent NAV as soon as it is published by the source.
 
 ## Backed xStock Report Schema
 
-[Chainlink Backed xStock Data Streams](./report-schema-v10) provide fresh, reliable, and accurate financial market data for Tokenized Equities such as [xStock](https://xstocks.com/us) assets, enabling DeFi users to gain onchain exposure to tokenized stocks. These Streams are a unique product provided by Chainlink Labs for partners such as xStocks. They combine data from our US equity Data Streams with data from the tokenization service, which enables users to correctly handle corporate actions affecting the underlying equities. Each report includes the staleness measure (`lastUpdateTimestamp`), last traded price (`price`), market status (`marketStatus`), current multiplier (`currentMultiplier`, the number of underlying shares each xStock is redeemable for), new multiplier (`newMultiplier`, the future number of shares after a scheduled corporate action), activation date/time of the corporate action (`activationDateTime`) and the tokenized price if available on primary or secondary markets (`tokenizedPrice`).
+[Chainlink Backed xStock Data Streams](./report-schema-v10) provide fresh, reliable, and accurate financial market data for Tokenized Equities such as [xStock](https://xstocks.com/us) assets, enabling DeFi users to gain onchain exposure to tokenized stocks. These Streams are a unique product provided by Chainlink Labs for partners such as xStocks. They combine data from our US equity Data Streams with data from the tokenization service, which enables users to correctly handle corporate actions affecting the underlying equities. Each report includes the staleness measure (`lastUpdateTimestamp`), consensus mid price (`price`), market status (`marketStatus`), current multiplier (`currentMultiplier`, the number of underlying shares each xStock is redeemable for), new multiplier (`newMultiplier`, the future number of shares after a scheduled corporate action), activation date/time of the corporate action (`activationDateTime`) and the tokenized price if available on primary or secondary markets (`tokenizedPrice`).
 
-The underlying US equities trade on traditional exchanges during [market hours](../market-hours). These market hours depend per asset class and can be subject to unexpected halts, pauses and other behaviors affecting traditional markets. For this reason, this class of Data Streams contains a market hours flag and a staleness measure to equip our users to handle these events correctly. It is critical that users implement correct safeguards on their side to pause markets, add more conservative risk caps, or implement other measures appropriate for their application.
+The underlying US equities trade on traditional exchanges during [market hours](../market-hours). These market hours depend per asset class and can be subject to unexpected halts, pauses and other behaviors affecting traditional markets. For this reason, this class of Data Streams contains a market hours flag and a staleness measure to equip our users to handle these events correctly. It is critical that users implement correct safeguards on their end to pause markets, add more conservative risk caps, or implement other measures appropriate for their application.
 
 [The schema](./report-schema-v10) is designed specifically for tokenized equities such as xStocks and contains data from the Chainlink US equities streams, combined with data provided by the tokenizer to properly handle corporate actions. With this enhanced data users are able to handle expected and unexpected market events such as pauses, halts and market off hours. The tokenization provider layers in data around the `currentMultiplier`, the `newMultiplier` and the `activationDateTime` of the new multiplier to handle corporate actions.