Open interest for ANY USDT perp: Bybit OI in base + USD with 1h/24h change, plus OKX OI. (get_positioning covers SOL+BTC only.) Costs $0.01 USDC per call (x402, Solana mainnet).
| Name | Required | Description | Default |
|---|---|---|---|
| symbol | Yes | USDT perp symbol e.g. SOLUSDT |
Changes observed during successful MCP inspections. Dates show when Glama detected each change.
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the full behavioral burden and does well by disclosing the per-call cost, the x402 payment mechanism, and the Solana mainnet requirement. It also specifies the data sources and change periods, though it could mention error behavior or whether data is live/cached.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is two sentences, front-loaded with the core functionality and data returned, then adds the sibling distinction and cost. There is no filler; every clause contributes selection-relevant information.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a one-parameter tool with no output schema, the description gives a solid list of what is returned (Bybit base/USD values, change windows, OKX OI) and the payment requirement. It does not spell out the exact response JSON structure or error cases, but the included details are enough for an agent to call it and interpret the result
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The schema covers the symbol parameter well with a description and example (SOLUSDT). The description adds the word 'ANY' to emphasize broad acceptance but provides no additional format, case, or constraint details beyond the schema, so it meets but does not exceed the baseline.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool returns open interest for any USDT perpetual, with specific data points (Bybit OI in base and USD, 1h/24h change, plus OKX OI). It also distinguishes itself from a sibling by noting get_positioning covers only SOL and BTC, making selection unambiguous.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
It explicitly states the tool's coverage ('ANY USDT perp') and contrasts it with an alternative ('get_positioning covers SOL+BTC only'), which directly guides an agent on when to choose this tool. The cost note also provides practical usage context for when paid calls are acceptable.
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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Many tools are tightly scoped and cross-referenced, but the set contains overlapping families: liquidation tools (alert/scan/history/stats/leaders/recent/heatmap) and redundant snapshots like get_market_snapshot vs get_trade_context, get_last_liquidation vs get_recent_liquidations, and get_cascade_forecast_free vs get_cascade_forecast. Agents will need to read descriptions carefully to avoid misselection.
All tool names follow a consistent get_<domain>_<detail> snake_case pattern, which makes the API predictable. The only real deviations are the bare 'pricing' tool and the 'free' suffix on taster variants.
At 52 tools, this far exceeds the 3-15 well-scoped range and crosses the 50-tool extreme threshold. The count is inflated by numerous paid/free taster pairs and many overlapping liquidation variants.
The surface covers prices, funding, open interest, orderbooks, liquidations, wallet/token data, Solana network health, DeFi TVL, and stablecoin flows—broad coverage for a crypto data feed. Gaps like historical OHLC/price candles, a machine-readable symbol list, and pagination endpoints are workable around but would round it out.