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market-data

get_open_interest

Open interest with per-row quality flags (verified archive + flagged bridge). tf=1h (default, full history) or tf=5m (archive-native 5-minute rows from 2020-09; ranged pulls, ~100k rows max per call).

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
tfNo
endNo
startNo
symbolYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed1 schema field changed
    • addedInput schema / properties / tf
      Added value: +{
      +  "enum": [
      +    "1h",
      +    "5m"
      +  ],
      +  "type": "string"
      +}
  2. First observed

TDQS

A3.8/5.0
Behavior4/5

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

There are no annotations, so the description carries the full behavioral disclosure burden. It provides useful details beyond the schema: per-row quality flags, verified archive versus flagged bridge data, the timeframe-dependent data vintage, and the ~100k row cap per call. It doesn't describe output structure, but the core behavioral constraints are surfaced.

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

Conciseness5/5

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

The description is a single dense sentence that front-loads the core resource and quality information, then packs the important timeframe, history, and row-limit details into a compact remainder. Every clause adds value and there is no 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?

For a read-oriented data retrieval tool with 4 parameters and no output schema, the description covers the main usage distinctions and constraints. It could be more complete by stating the expected start/end formats and explicitly saying the response contains rows keyed by symbol and timestamp, but overall the essential calling guidance is present.

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 coverage is 0%, so the description must compensate. It meaningfully explains tf semantics and the row/range limits of 5m pulls. However, start and end are only weakly implied by 'ranged pulls', and symbol is not elaborated beyond its schema type, leaving some burden on the agent.

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

Purpose4/5

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

The description clearly states the tool exposes open interest data and distinguishes two timeframe modes (1h vs 5m), which positions it as a specific data resource. It doesn't explicitly differentiate from sibling tools like get_bars or get_funding, but 'open interest' is self-identifying enough within the suite.

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

Usage Guidelines3/5

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

The description gives practical usage context: tf=1h is the default with full history, while tf=5m is archive-native and intended for ranged pulls with a maximum row cap. However, it never states when to prefer this tool over alternatives or provides explicit exclusions, leaving the when-to-use decision mostly implied.

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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