# ChartsPod > A free browser-based crypto charting and market-research terminal. ChartsPod combines live charts, order flow, derivatives, options, screening, backtesting, alerts, journaling and AI-assisted workflows while keeping the market, venue and timeframe attached to the analysis. Core crypto charting and public market research can be opened without an account. An account is used for account-bound functions such as cross-device synchronization, shared rooms and authenticated tools. The in-terminal AI assistant uses a provider key supplied by the user; ChartsPod does not resell model inference. ## What ChartsPod includes - **Charts**: 20 chart types and 200 technical studies, including candles, Heikin Ashi, Renko, Kagi, line break, point and figure, footprint, volume profile and market profile. - **Order flow**: trade tape, depth of market, volume footprint, bid/ask volume, delta, cumulative volume delta, imbalance, absorption and liquidity heatmaps where the selected venue exposes the required public data. - **Derivatives**: funding, open interest, liquidations, positioning and futures-basis context across supported venues. - **Options**: chain, open interest by strike and expiry, implied volatility, skew, max pain, modelled gamma, vanna, charm, zero-gamma analysis and strategy payoff tools for supported public venue feeds. - **Research**: screeners, 33 built-in strategies, backtesting, Formula Lab, live tables, alerts, calendar, journal, watchlists and multi-chart workspaces. - **AI and MCP**: an in-terminal assistant with tool evidence and a public MCP endpoint that compatible clients can call at https://chartspod.com/api/mcp. ## Limits and accurate use - ChartsPod is not a broker, exchange, custodian or order-routing service. It does not place trades or hold customer funds. - Content and calculated outputs are research and decision-support material, not financial advice, guaranteed signals or promises of future performance. - Coverage varies by exchange, instrument and public API. Missing history stays missing rather than being represented as zero. - Options exposures are modelled from public open interest and volatility inputs; they are not published dealer positions. - Historical trade-at-price and order-book depth are limited by the venue feed and the data loaded or retained by the application. ## Start here - [ChartsPod home](https://chartspod.com/): Product overview, capabilities and access information. - [Open the terminal](https://chartspod.com/terminal): Launch the charting and market-research workspace. - [Documentation](https://chartspod.com/docs): Setup, charting, research and workflow documentation. - [Connect an AI with MCP](https://chartspod.com/mcp): Connect a compatible assistant to ChartsPod market-data and chart tools. - [Indicator reference](https://chartspod.com/indicators): Indicator calculations, settings and practical limitations. - [Markets](https://chartspod.com/markets): Market-specific research guides and direct links to the corresponding live contracts. - [ChartsPod News](https://chartspod.com/news): Original market research, comparisons, guides and the credited news wire. - [News RSS feed](https://chartspod.com/news/feed.xml): Machine-readable feed for ChartsPod research. - [Options workspace](https://chartspod.com/options): Public crypto options analytics and modelled exposure tools. - [Chart widgets](https://chartspod.com/widgets): Embeddable chart tools and implementation guidance. ## Research standards and policies - [About ChartsPod](https://chartspod.com/about): What ChartsPod is, how it is built and who it serves. - [Methodology](https://chartspod.com/methodology): Calculation, testing and evidence standards. - [Data sources](https://chartspod.com/data-sources): Venue coverage, provenance and known data limits. - [Editorial policy](https://chartspod.com/editorial-policy): Authorship, corrections, sourcing and editorial independence. - [Risk disclosure](https://chartspod.com/risk-disclosure): Market, model, execution and data risks. - [Privacy policy](https://chartspod.com/privacy): How personal and technical data is handled. - [Terms of service](https://chartspod.com/terms): Rules governing access and use. - [Payments and refunds](https://chartspod.com/payments): Payment, cancellation and refund terms when paid access is offered. - [Cookie policy](https://chartspod.com/cookie-policy): Cookies and browser storage used by ChartsPod. - [Contact and support](https://chartspod.com/contact): How to contact the ChartsPod team. ## Featured market guides - [Bitcoin (BTC) market guide](https://chartspod.com/markets/btc-usdt): Bitcoin (BTC) is a benchmark market whose liquidity, relative strength and volatility regime influence how the wider crypto complex is priced. The live link opens BTCUSDT. - [Ethereum (ETH) market guide](https://chartspod.com/markets/eth-usdt): Ethereum (ETH) is a benchmark market whose liquidity, relative strength and volatility regime influence how the wider crypto complex is priced. The live link opens ETHUSDT. - [BNB (BNB) market guide](https://chartspod.com/markets/bnb-usdt): BNB (BNB) is a smart-contract network market whose trend should be compared with ecosystem activity, peer strength and broad risk appetite. The live link opens BNBUSDT. - [XRP (XRP) market guide](https://chartspod.com/markets/xrp-usdt): XRP (XRP) is a payments-oriented market that should be read through liquidity, network use, relative strength and event risk. The live link opens XRPUSDT. - [Solana (SOL) market guide](https://chartspod.com/markets/sol-usdt): Solana (SOL) is a smart-contract network market whose trend should be compared with ecosystem activity, peer strength and broad risk appetite. The live link opens SOLUSDT. - [TRON (TRX) market guide](https://chartspod.com/markets/trx-usdt): TRON (TRX) is a payments-oriented market that should be read through liquidity, network use, relative strength and event risk. The live link opens TRXUSDT. - [Dogecoin (DOGE) market guide](https://chartspod.com/markets/doge-usdt): Dogecoin (DOGE) is an attention-led market where participation, liquidity concentration and social reflexivity can outweigh conventional valuation inputs. The live link opens DOGEUSDT. - [Cardano (ADA) market guide](https://chartspod.com/markets/ada-usdt): Cardano (ADA) is a smart-contract network market whose trend should be compared with ecosystem activity, peer strength and broad risk appetite. The live link opens ADAUSDT. - [Hyperliquid (HYPE) market guide](https://chartspod.com/markets/hype-usdt): Hyperliquid (HYPE) is a decentralised-finance market where protocol activity, token economics and the condition of on-chain liquidity can change the chart narrative. The live link opens HYPEUSDT. - [Zcash (ZEC) market guide](https://chartspod.com/markets/zec-usdt): Zcash (ZEC) is a privacy-focused market where venue access, liquidity fragmentation and regulatory headlines are part of the technical context. The live link opens ZECUSDT. - [Chainlink (LINK) market guide](https://chartspod.com/markets/link-usdt): Chainlink (LINK) is a crypto-infrastructure market whose adoption narrative must be tested against price structure, volume and durable demand. The live link opens LINKUSDT. - [Monero (XMR) market guide](https://chartspod.com/markets/xmr-usdt): Monero (XMR) is a privacy-focused market where venue access, liquidity fragmentation and regulatory headlines are part of the technical context. The live link opens XMRUSDT. - [Stellar (XLM) market guide](https://chartspod.com/markets/xlm-usdt): Stellar (XLM) is a payments-oriented market that should be read through liquidity, network use, relative strength and event risk. The live link opens XLMUSDT. - [Bitcoin Cash (BCH) market guide](https://chartspod.com/markets/bch-usdt): Bitcoin Cash (BCH) is a payments-oriented market that should be read through liquidity, network use, relative strength and event risk. The live link opens BCHUSDT. - [Litecoin (LTC) market guide](https://chartspod.com/markets/ltc-usdt): Litecoin (LTC) is a payments-oriented market that should be read through liquidity, network use, relative strength and event risk. The live link opens LTCUSDT. - [Hedera (HBAR) market guide](https://chartspod.com/markets/hbar-usdt): Hedera (HBAR) is a smart-contract network market whose trend should be compared with ecosystem activity, peer strength and broad risk appetite. The live link opens HBARUSDT. - [Avalanche (AVAX) market guide](https://chartspod.com/markets/avax-usdt): Avalanche (AVAX) is a smart-contract network market whose trend should be compared with ecosystem activity, peer strength and broad risk appetite. The live link opens AVAXUSDT. - [Shiba Inu (SHIB) market guide](https://chartspod.com/markets/shib-usdt): Shiba Inu (SHIB) is an attention-led market where participation, liquidity concentration and social reflexivity can outweigh conventional valuation inputs. The live link opens 1000SHIBUSDT. - [Sui (SUI) market guide](https://chartspod.com/markets/sui-usdt): Sui (SUI) is a smart-contract network market whose trend should be compared with ecosystem activity, peer strength and broad risk appetite. The live link opens SUIUSDT. - [Uniswap (UNI) market guide](https://chartspod.com/markets/uni-usdt): Uniswap (UNI) is a decentralised-finance market where protocol activity, token economics and the condition of on-chain liquidity can change the chart narrative. The live link opens UNIUSDT. ## Recent ChartsPod research - [200-Day Moving-Average Filter Backtest in Crypto: Fees, Slippage and Break-Even Costs](https://chartspod.com/news/200-day-moving-average-filter-backtest-in-crypto-fees-slippage-and-break-even-costs): A 200-day moving-average filter keeps a strategy long only above the line. On crypto it often cuts drawdowns, at the cost of whipsaws near the average. - [25-Delta Options Skew in Crypto: How to Read the Data With Price Context](https://chartspod.com/news/25-delta-options-skew-in-crypto-how-to-read-the-data-with-price-context): 25-delta skew compares the implied volatility of puts and calls equally far out of the money. It shows which side traders pay more to own. - [A DEX Pool With No Recent Swaps: Is the Displayed Price Still Useful?](https://chartspod.com/news/a-dex-pool-with-no-recent-swaps-is-the-displayed-price-still-useful): A pool's displayed price is the price of its last swap. If nobody has swapped for hours, that number may be far from where you could trade. - [A Large Crypto Trade Is Not Always a Whale Bet: Read the Tape](https://chartspod.com/news/a-large-crypto-trade-is-not-always-a-whale-bet-read-the-tape): A large print can be a hedge, an arbitrage leg, a liquidation or a market maker rebalancing. Calling it a whale bet requires more than size. - [A Liquidity Lock Does Not Prove a Token Is Safe: Other Checks](https://chartspod.com/news/a-liquidity-lock-does-not-prove-a-token-is-safe-other-checks): A liquidity lock stops one specific action: withdrawing locked LP tokens before a date. Many other risks remain. - [A Low-Liquidity Token Exit Plan: Size the Position Before the Swap](https://chartspod.com/news/a-low-liquidity-token-exit-plan-size-the-position-before-the-swap): On a thin token, the hard part is not buying. It is selling later without crushing the price. Size the position for the exit before you enter. - [A Profitable Crypto Backtest With 20 Trades: Is the Sample Useful?](https://chartspod.com/news/a-profitable-crypto-backtest-with-20-trades-is-the-sample-useful): Twenty profitable trades can come from luck as easily as from an edge. Before trusting a result, measure how uncertain it is. - [A Token With Many Pools: Which Chart Represents Your Actual Swap?](https://chartspod.com/news/a-token-with-many-pools-which-chart-represents-your-actual-swap): Your swap may not go through the pool you were watching. Aggregators split orders across pools, so the chart that matters is the route's, not the headline's. - [Accumulation Distribution Line in Crypto: Why the Value Changes Before Candle Close](https://chartspod.com/news/accumulation-distribution-line-in-crypto-why-the-value-changes-before-candle-close): The Accumulation/Distribution line adds volume weighted by where the close sits in the bar's range. The live bar's contribution can swing from fully positive to fully negative. - [ADX in Crypto: Warm-Up Bars and Short-History Errors](https://chartspod.com/news/adx-in-crypto-warm-up-bars-and-short-history-errors): ADX applies Wilder smoothing twice — first to directional movement, then to DX. It needs more history than most indicators to settle. - [ADX in Crypto: Why the Value Changes Before Candle Close](https://chartspod.com/news/adx-in-crypto-why-the-value-changes-before-candle-close): ADX measures trend strength from directional movement smoothed over many bars. It changes intrabar, but slowly; the bigger risk is reading its direction too early. - [ADX Trend Filter Backtest in Crypto: Fees, Slippage and Break-Even Costs](https://chartspod.com/news/adx-trend-filter-backtest-in-crypto-fees-slippage-and-break-even-costs): An ADX filter lets a strategy trade only when trend strength is above a threshold. It removes some chop and delays entries. - [Aggr.trade Audio Thresholds: Match Alerts to Trade Size and Market](https://chartspod.com/news/aggr-trade-audio-thresholds-match-alerts-to-trade-size-and-market): Audio lets you watch other screens while the tape talks. It only helps if each sound means something specific for the market you trade. - [Aggr.trade Bitcoin Settings: Reduce Noise Without Hiding Relevant Trades](https://chartspod.com/news/aggr-trade-bitcoin-settings-reduce-noise-without-hiding-relevant-trades): A BTC tape with every fill is unreadable; a tape filtered too hard hides the trades that matter. Set thresholds by venue and market, then check what you are no longer seeing. - [Aggr.trade Liquidation Prints: Check Venue Coverage and Event Timing](https://chartspod.com/news/aggr-trade-liquidation-prints-check-venue-coverage-and-event-timing): Liquidation prints on a live tape are only as complete as the exchange feeds behind them. Check venue coverage and timing before reading a cascade. - [Aggr.trade Trade Aggregation: Why Several Prints Become One Row](https://chartspod.com/news/aggr-trade-trade-aggregation-why-several-prints-become-one-row): One market order often fills against many resting orders. Aggregation reunites those fills so the tape shows the order, not the fragments. - [Aggr.trade vs ChartsPod for Cross-Exchange Price Comparison: Feature Coverage](https://chartspod.com/news/aggr-trade-vs-chartspod-for-cross-exchange-price-comparison-feature-coverage): Aggr.trade sums trades across exchanges or shows them separately. For cross-exchange comparison, how you configure panes decides what you learn. - [Aggr.trade vs ChartsPod for Custom Indicator Research: Feature Coverage](https://chartspod.com/news/aggr-trade-vs-chartspod-for-custom-indicator-research-feature-coverage): Aggr.trade is open source and highly configurable for live trade data. Custom indicator scripting details weren't confirmed in the material reviewed. - [Aggr.trade vs ChartsPod for CVD Data Quality: Feature Coverage](https://chartspod.com/news/aggr-trade-vs-chartspod-for-cvd-data-quality-feature-coverage): Aggr builds its view from live trades streamed from many exchanges. That makes its delta trade-based, but aggregated across venues you choose. - [Aggr.trade vs ChartsPod for Footprint Row Resolution: Feature Coverage](https://chartspod.com/news/aggr-trade-vs-chartspod-for-footprint-row-resolution-feature-coverage): Aggr.trade focuses on live aggregated trades, sound cues and charts. Footprint row settings weren't described in its README or changelog as reviewed. - [Aggr.trade vs ChartsPod for Intraday Historical Data: Feature Coverage](https://chartspod.com/news/aggr-trade-vs-chartspod-for-intraday-historical-data-feature-coverage): Aggr.trade is live-first. Its README says history requires running aggr-server yourself. - [Aggr.trade vs ChartsPod for Large-Trade Analysis: Feature Coverage](https://chartspod.com/news/aggr-trade-vs-chartspod-for-large-trade-analysis-feature-coverage): Aggr.trade is designed for watching trades live across exchanges, with size thresholds and audio cues. Large prints are its strength. - [Aggr.trade vs ChartsPod for Market-Wide Screening: Feature Coverage](https://chartspod.com/news/aggr-trade-vs-chartspod-for-market-wide-screening-feature-coverage): Aggr.trade watches live trades across exchanges for the markets you add. It isn't a market-wide screener. - [Aggr.trade vs ChartsPod for Multi-Chart Workspaces: Feature Coverage](https://chartspod.com/news/aggr-trade-vs-chartspod-for-multi-chart-workspaces-feature-coverage): Aggr.trade lets you arrange panes of live trades, charts and stats in workspaces. Its focus is real-time flow across many exchanges. - [Aggr.trade vs ChartsPod for Order-Book History: Feature Coverage](https://chartspod.com/news/aggr-trade-vs-chartspod-for-order-book-history-feature-coverage): Aggr.trade is built around live trades, not order-book depth. Its README and changelog reviewed describe trades, liquidations and alerts rather than a book history. - [Aggr.trade vs ChartsPod for Spot and Perpetual Data: Feature Coverage](https://chartspod.com/news/aggr-trade-vs-chartspod-for-spot-and-perpetual-data-feature-coverage): Aggr.trade can show spot and perpetual trades side by side from many venues. ChartsPod pairs those markets with derivatives and order-book context. - [Aggr.trade vs TensorCharts: Trade Tape vs Order-Book Context](https://chartspod.com/news/aggr-trade-vs-tensorcharts-trade-tape-vs-order-book-context): A trade tape shows what was executed. An order-book view shows what was waiting. Aggr.trade and TensorCharts emphasise different halves of the same story. - [Aggregated vs Single-Exchange Open Interest in Crypto: How to Read the Data With Price Context](https://chartspod.com/news/aggregated-vs-single-exchange-open-interest-in-crypto-how-to-read-the-data-with-price-context): Aggregated open interest shows the whole market's positioning; single-exchange OI shows one venue's. They can move in opposite directions. - [Aggregated vs Single-Exchange Open Interest in Crypto: Units and Time Windows That Change the Result](https://chartspod.com/news/aggregated-vs-single-exchange-open-interest-in-crypto-units-and-time-windows-that-change-the-result): Aggregated OI sums several exchanges; single-venue OI shows one. Coverage and timing differences can make the aggregate move when no single venue does. - [AI Analysts Disagree on Crypto: Compare Inputs Before Conclusions](https://chartspod.com/news/ai-analysts-disagree-on-crypto-compare-inputs-before-conclusions): Two AI analysts reach opposite conclusions about the same coin. Before choosing one, compare what each looked at. - [AI Chart Screenshots vs Market Data: Verify Exact Prices With Tools](https://chartspod.com/news/ai-chart-screenshots-vs-market-data-verify-exact-prices-with-tools): AI models reading a chart screenshot estimate prices from pixels. For exact levels, use data tools that fetch the numbers. - [AI Crypto Analysis With Live Data: What Evidence Should Be Included?](https://chartspod.com/news/ai-crypto-analysis-with-live-data-what-evidence-should-be-included): An AI market analysis is only as good as the evidence it shows. Ask for the data, not just the conclusion. - [AI Crypto Backtest Research: A Prompt That Requests Evidence and Invalidation](https://chartspod.com/news/ai-crypto-backtest-research-a-prompt-that-requests-evidence-and-invalidation): An AI backtest prompt should specify everything that makes backtests unrealistic, so the agent can't quietly assume the optimistic version. - [AI Crypto Backtest Research: How to Check Timestamps Before Trusting the Answer](https://chartspod.com/news/ai-crypto-backtest-research-how-to-check-timestamps-before-trusting-the-answer): A backtest summary from an AI is only checkable if it states the test period, data source and when the test ran. Otherwise it can't be reproduced. - [AI Crypto Backtest Research: Trace the Conclusion Back to the Tool Results](https://chartspod.com/news/ai-crypto-backtest-research-trace-the-conclusion-back-to-the-tool-results): An AI backtest summary reports returns, win rates and drawdowns. Each figure should be traceable to a trade list and settings in the tool output. - [AI Crypto Backtest Research: What the Assistant Should Say When Data Is Missing](https://chartspod.com/news/ai-crypto-backtest-research-what-the-assistant-should-say-when-data-is-missing): Backtests need complete price data, cost settings and enough trades. When any is missing, an AI should say the result is limited rather than report a clean number. - [AI Crypto Backtests: Check Fills, Fees and the Number of Trials](https://chartspod.com/news/ai-crypto-backtests-check-fills-fees-and-the-number-of-trials): An AI can run a backtest in seconds. Whether the result means anything depends on fills, fees and how many variations it tried. - [AI Crypto Breakout Research: A Prompt That Requests Evidence and Invalidation](https://chartspod.com/news/ai-crypto-breakout-research-a-prompt-that-requests-evidence-and-invalidation): Breakouts tempt fast decisions. A prompt that asks the AI for evidence on both sides and a clear invalidation slows the decision down to a useful speed. - [AI Crypto Breakout Research: How to Check Timestamps Before Trusting the Answer](https://chartspod.com/news/ai-crypto-breakout-research-how-to-check-timestamps-before-trusting-the-answer): An AI breakout analysis is only as current as the bar it read. Breakout claims fail most often because the 'breakout bar' hadn't closed. - [AI Crypto Breakout Research: Trace the Conclusion Back to the Tool Results](https://chartspod.com/news/ai-crypto-breakout-research-trace-the-conclusion-back-to-the-tool-results): A breakout conclusion rests on a level, a closed bar and flow data. Tracing each claim to a tool result shows whether the conclusion is supported. - [AI Crypto Breakout Research: What the Assistant Should Say When Data Is Missing](https://chartspod.com/news/ai-crypto-breakout-research-what-the-assistant-should-say-when-data-is-missing): A breakout call needs the level, the closed breakout bar and the flow behind it. When any is missing, the assistant should say so instead of filling in. - [AI Crypto Calendar Research: A Prompt That Requests Evidence and Invalidation](https://chartspod.com/news/ai-crypto-calendar-research-a-prompt-that-requests-evidence-and-invalidation): Scheduled events move crypto. An AI calendar prompt should turn the calendar into scenarios, not predictions. - [AI Crypto Calendar Research: How to Check Timestamps Before Trusting the Answer](https://chartspod.com/news/ai-crypto-calendar-research-how-to-check-timestamps-before-trusting-the-answer): Calendar answers depend on event times, timezones and whether an event already happened. A missing timezone alone can shift an event by hours. - [AI Crypto Calendar Research: Trace the Conclusion Back to the Tool Results](https://chartspod.com/news/ai-crypto-calendar-research-trace-the-conclusion-back-to-the-tool-results): Calendar answers list events with times and values. Each should trace to a source with its timezone and status. - [AI Crypto Calendar Research: What the Assistant Should Say When Data Is Missing](https://chartspod.com/news/ai-crypto-calendar-research-what-the-assistant-should-say-when-data-is-missing): Calendar data has gaps: unconfirmed times, missing forecasts, events not covered by the source. The assistant should mark them clearly. - [AI Crypto Chart Screenshot Analysis: A Prompt That Requests Evidence and Invalidation](https://chartspod.com/news/ai-crypto-chart-screenshot-analysis-a-prompt-that-requests-evidence-and-invalidation): Pasting a chart screenshot into an AI is quick, but the model reads pixels, not data. The prompt must make it say what it can and can't read. - [AI Crypto Chart Screenshot Analysis: How to Check Timestamps Before Trusting the Answer](https://chartspod.com/news/ai-crypto-chart-screenshot-analysis-how-to-check-timestamps-before-trusting-the-answer): A screenshot freezes one moment, but often hides when that moment was. An AI reading it can't know unless the time is visible. - [AI Crypto Chart Screenshot Analysis: Trace the Conclusion Back to the Tool Results](https://chartspod.com/news/ai-crypto-chart-screenshot-analysis-trace-the-conclusion-back-to-the-tool-results): An AI reading a screenshot has no tool data — only pixels. Its claims should trace to what's visible in the image, or to data it fetched separately. - [AI Crypto Chart Screenshot Analysis: What the Assistant Should Say When Data Is Missing](https://chartspod.com/news/ai-crypto-chart-screenshot-analysis-what-the-assistant-should-say-when-data-is-missing): A screenshot hides most of the data behind the chart. The assistant should say what it can't read rather than guess. - [AI Crypto Data Reconciliation: A Prompt That Requests Evidence and Invalidation](https://chartspod.com/news/ai-crypto-data-reconciliation-a-prompt-that-requests-evidence-and-invalidation): Two sources disagree on volume, OI or price. An AI can do the comparison quickly — if the prompt makes it list definitions before declaring a winner. - [AI Crypto Data Reconciliation: How to Check Timestamps Before Trusting the Answer](https://chartspod.com/news/ai-crypto-data-reconciliation-how-to-check-timestamps-before-trusting-the-answer): When two sources disagree, the first thing to check is whether they were read at the same time and over the same window. - [AI Crypto Data Reconciliation: Trace the Conclusion Back to the Tool Results](https://chartspod.com/news/ai-crypto-data-reconciliation-trace-the-conclusion-back-to-the-tool-results): A reconciliation answer explains why two sources differ. Its explanation should trace to definitions and values in the tool output, not general knowledge. - [AI Crypto Data Reconciliation: What the Assistant Should Say When Data Is Missing](https://chartspod.com/news/ai-crypto-data-reconciliation-what-the-assistant-should-say-when-data-is-missing): Reconciling two data sources often fails because one can't be fetched or lacks a field. The assistant should report what it couldn't compare. - [AI Crypto Formula Research: A Prompt That Requests Evidence and Invalidation](https://chartspod.com/news/ai-crypto-formula-research-a-prompt-that-requests-evidence-and-invalidation): Asking an AI to write an indicator formula is easy. Getting one you can trust means asking for the definition, an edge-case list and a hand-checkable example. - [AI Crypto Formula Research: How to Check Timestamps Before Trusting the Answer](https://chartspod.com/news/ai-crypto-formula-research-how-to-check-timestamps-before-trusting-the-answer): A formula answer can be correct and still disagree with your chart, because its worked example used data from a different time or venue. - [AI Crypto Formula Research: What the Assistant Should Say When Data Is Missing](https://chartspod.com/news/ai-crypto-formula-research-what-the-assistant-should-say-when-data-is-missing): Formula answers depend on definitions, defaults and data. When the AI isn't sure of a definition or can't test it, it should say so. - [AI Crypto Funding Analysis: A Prompt That Requests Evidence and Invalidation](https://chartspod.com/news/ai-crypto-funding-analysis-a-prompt-that-requests-evidence-and-invalidation): Funding numbers are easy to misquote: wrong interval, wrong venue, predicted instead of settled. A precise prompt prevents most errors. - [AI Crypto Funding Analysis: How to Check Timestamps Before Trusting the Answer](https://chartspod.com/news/ai-crypto-funding-analysis-how-to-check-timestamps-before-trusting-the-answer): Funding values come in two kinds: settled rates with a funding time, and predicted rates that change until settlement. An AI answer must say which. - [AI Crypto Funding Analysis: Trace the Conclusion Back to the Tool Results](https://chartspod.com/news/ai-crypto-funding-analysis-trace-the-conclusion-back-to-the-tool-results): Funding conclusions involve rates, intervals and venues. Each number in the answer should appear in a tool result with its time and type. - [AI Crypto Funding Analysis: What the Assistant Should Say When Data Is Missing](https://chartspod.com/news/ai-crypto-funding-analysis-what-the-assistant-should-say-when-data-is-missing): Funding data can be missing for a venue, a period or a symbol with a different interval. Each gap affects comparisons differently. ## Complete machine-readable indexes - [Complete ChartsPod LLM index](https://chartspod.com/llms-full.txt): every published market guide and ChartsPod article. - [XML sitemap](https://chartspod.com/sitemap.xml): canonical indexable URLs and article modification dates. ## Terms for quoting and linking Quoting short passages and linking to ChartsPod is welcome. Preserve the stated venue, instrument, timeframe, methodology and limitations. Do not describe ChartsPod as a broker, signal service or hosted AI provider, and do not present research content as financial advice.