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DepthFeed

by com.depthfeed

bars

Read-only

OHLCV price bars for US equities and ETFs, Binance spot pairs, and perpetual futures. One minute is the finest resolution; 5Min, 15Min, 1Hour and 1Day are rolled up from it and say so with derived. Spell a crypto pair the way the venue does (BTCUSDT, not BTC) and a perpetual with a .P suffix (BTCUSDT.P) — spot and perp are different instruments at different prices. BTCU, ETHU and WLDU are each both a US ETF and a Binance pair, and resolve to the equity — pass venue=binance to reach the pair instead. Optional venue selects the market explicitly: us-equities, binance (spot) or binance-futures (perpetuals). Bounded by the same plan history window as every other read (403 HISTORY_LIMIT_EXCEEDED past it); the plan also sets how many symbols one request may carry.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
symbolsYesComma-separated symbols, e.g. "AAPL,BTCUSDT,BTCUSDT.P". 3 per request on Explorer, 8 Quant, 16 Research, 32 Desk.
end_timeNoEnd of time as ms-epoch or ISO-8601. History is clamped to your plan's window.
timeframeNo1Min (default), 5Min, 15Min, 1Hour or 1Day.
start_timeNoStart of time as ms-epoch or ISO-8601. History is clamped to your plan's window.

Schema Changelog

Changes observed during successful MCP inspections. Dates show when Glama detected each change.

  1. Added

TDQS

A4.3/5.0
Behavior5/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

Annotations already declare readOnlyHint and openWorldHint, but the description adds critical behavioral context: plan history window bounding, 403 HISTORY_LIMIT_EXCEEDED error, per-request symbol limits, resolution roll-up and 'derived' flag, and spot/perp venue resolution. This goes well beyond the annotations.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is long but information-dense, covering asset classes, resolution rules, symbol ambiguity, venue selection, and plan limits. It opens with purpose and each sentence adds essential detail without repetition or filler.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness4/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

The description covers purpose, asset scope, resolution, symbol naming, venue disambiguation, history limits, and symbol count. It does not explicitly describe the output format, but OHLCV bars imply the return structure, and the 'derived' flag hints at response contents. The missing venue parameter in the schema is a notable gap, but overall the tool is well-specified.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema descriptions cover all 4 parameters, so baseline is 3. The description adds useful symbol formatting examples and resolution semantics, but it also references an optional 'venue' parameter that is absent from the input schema. This discrepancy could mislead the agent into passing an invalid parameter, reducing the value of the additional meaning.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The first sentence clearly states the tool returns OHLCV price bars for US equities/ETFs, Binance spot, and perpetual futures. This specific verb-resource pairing distinguishes it from sibling tools like kalshi_get_candles and polymarket_get_market, which serve other markets.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines4/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description gives clear context on when to use the tool via its asset scope and provides explicit symbol-naming conventions and venue disambiguation. However, it does not directly name alternative tools or state exclusions such as 'use this for equities/Binance, not for Kalshi/Polymarket'.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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TDQS

A4.1/5.0
Disambiguation5/5

Each tool targets a distinct venue and data type: Polymarket/Kalshi/Limitless-specific search, orderbook, and snapshot tools are clearly separated by prefix, while bars, backtest_paths, screener, and whoami serve unique purposes. No two tools could plausibly be confused in agent selection.

Naming Consistency4/5

Most tools follow a clear `<venue>_<action>_<object>` pattern (e.g., kalshi_get_orderbook, limitless_get_snapshots, polymarket_search_markets). A few like backtest_paths, bars, screener, and whoami break the pattern, but they are descriptive and consistent with their domain. Overall predictable and legible.

Tool Count5/5

15 tools is well-scoped for a multi-venue market data API. Each tool adds meaningful functionality—search, snapshots, candles, orderbooks, screener, session info—without redundancy. The count aligns well with the apparent coverage of prediction markets, crypto, and equities.

Completeness5/5

The surface covers read operations for all major venues: search, market detail, orderbook, historical snapshots, and OHLCV bars. It also includes backtesting, cross-venue screener, and session introspection. No obvious dead ends or missing critical operations for a data-centric server.

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