> For the complete documentation index, see [llms.txt](https://takes.gitbook.io/takes-docs/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://takes.gitbook.io/takes-docs/technical-design/indexing-and-data.md). # Data and history Token balances and claims come from chain events. Account values, fills, and funding come from Hyperliquid. These sources do not always update at the same time. Takes records events once and saves progress so collection can resume after interruption. Value snapshots wait for token history to catch up before combining it with current account data. ## What you see A confirmed transaction can appear on-chain before the page updates. Missing chart points mean unavailable data, not zero value. Portfolio value uses recorded NAV. Trading volume sums fill values. Mint and redemption volumes count at settlement. Historical totals depend on the data collected, and today's totals are incomplete. Takes does not display since-launch performance until the token data includes a verified launch price. ## Recovery limits Takes can rebuild derived balances from stored events. Rebuilding cannot recover history that was never collected or restore trading losses. Use contract state for current claim eligibility. For a delayed page, see [Troubleshooting](/takes-docs/reference/troubleshooting.md#troubleshooting). ## Weight models and history Token creation events record the immutable weight model. Creation emits the required notional model in the same transaction. Event replay rejects missing or unsupported models. Each new rebalance records its model alongside the planned targets. Observed asset leverage divides absolute notional by matched backing equity × derived capital weight. For notional weights, that capital weight is `(weight / asset leverage) / sum(weight / asset leverage)`. NAV and in-flight request adjustments retain their existing accounting. Historical records are not reinterpreted as a different strategy. --- # Agent Instructions This documentation is published with GitBook. GitBook is the documentation platform designed so that both humans and AI agents can read, navigate, and reason over technical content effectively. Learn more at gitbook.com. ## Querying This Documentation If you need additional information that is not directly available in this page, you can query the documentation by asking a question. Perform an HTTP GET request on the following URL with the `ask` and `goal` query parameters: ``` GET https://takes.gitbook.io/takes-docs/technical-design/indexing-and-data.md?ask=&goal= ``` `ask` is the immediate question: it should be specific, self-contained, and written in natural language. `goal` is what the user is ultimately trying to achieve, the reason they need the answer. Sharing it helps GitBook give you a better, more relevant answer. A goal is most helpful when it describes the outcome the user wants rather than restating the question. For example, with `ask=how do I create an API token`, a goal like `automate deployments from our CI pipeline` lets GitBook tailor the answer to that use case. The response will contain a direct answer to the question and relevant excerpts and sources from the documentation. Use this mechanism when the answer is not explicitly present in the current page, you need clarification or additional context, or you want to retrieve related documentation sections.