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f1ow

by com.f1ow

Open Interest

derivatives_open_interest
Read-only

Current market-wide (cross-exchange aggregate) open interest (USD) for one coin's perpetuals, with its 24h and 7d change, the 24h price change, AND the underlying 4h-bucket series. Read OI against price: price up on rising OI is new money opening positions, price up on falling OI is short covering — opposite trades off the same price move. The series makes that read available bucket by bucket instead of once per day (pair it with market_candles at 4h for the price leg), and carries the window's own low/high so the current level can be judged against where it has actually been. Falls back to a single-venue figure if the aggregate source is offline. Set 'points' to trim the series (omit for the full ~10-day window; 0 to suppress it).

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
pointsNoHow many of the newest 4h buckets to emit. Omit for the full window (60 points ~ 10 days); 0 suppresses the series and returns the summary only.
symbolYesCoin symbol, e.g. "BTC".

TDQS

A4.4/5.0
Behavior5/5

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

Annotations only provide readOnlyHint=true; the description adds substantial behavioral detail: cross-exchange aggregation, a single-venue fallback when the aggregate source is offline, series low/high context, and the ability to suppress the series. This is exactly the kind of beyond-annotation transparency the dimension asks for.

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 most important result summary is front-loaded, followed by interpretation, fallback, and parameter guidance. It is longer than average, but each sentence carries operational value; the only slight excess is the interpretive trading guidance, which is still relevant to selecting and using the tool.

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

Completeness5/5

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

With no output schema, the description compensates by enumerating the main returned components: current OI, changes, price change, 4h series, series low/high, and fallback behavior. It also explains the points parameter's effect on output shape, so an agent has enough to call the tool correctly.

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 description coverage is 100%, so the schema already documents symbol and points thoroughly. The description reinforces the points behavior (trim, omit, or suppress) and ties symbol to 'one coin', but does not add materially new parameter semantics beyond that baseline.

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?

States a specific deliverable: current market-wide cross-exchange aggregate open interest in USD for one coin's perpetuals, plus 24h/7d changes, 24h price change, and a 4h series. This clearly distinguishes it from siblings like funding_current or market_candles, and it even references market_candles as a companion for the price leg.

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?

Gives clear analytical context: read OI against price, use the 4h series bucket-by-bucket, and pair with market_candles at 4h for the price leg. It does not explicitly list when not to use this tool versus other derivatives-related siblings, so it misses the top bar.

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

A4/5.0
Disambiguation4/5

Tools are grouped by clear prefixes and mostly target distinct resources; market_quotes vs research_token_view, market_top_movers vs market_trending, and funding_current vs market_quotes have some field or purpose overlap, but descriptions draw enough scope boundaries for an agent to choose correctly in most cases. No two tools are truly interchangeable.

Naming Consistency5/5

All 30 tool names use lowercase snake_case with a consistent domain-prefix convention such as market_, flow_, research_, sentiment_, and catalysts_, making the surface predictable. Even helpers like utc_time and risk_position_size fit the same noun-oriented pattern without style mixing.

Tool Count2/5

At 30 tools this set crosses the 'too many' threshold, and several tools reproduce data already available through broader ones such as research_token_view and market_quotes. The breadth is defensible for a crypto-research platform, but the surface feels heavy and could be consolidated.

Completeness5/5

The tool set covers the read-only crypto research workflow thoroughly: market data, candles, derivatives, funding, OI, order book, whale flows, ETF flows, on-chain metrics, news, sentiment, prediction odds, technicals, regime/positioning scans, and position sizing. It also includes health and UTC helpers that close practical workflow gaps, with no obvious dead ends.

Resources