Large prints from the live trade tape for any USDT perp: trades over a USD threshold, buy/sell totals, net flow, dominant side. Costs $0.02 USDC per call (x402, Solana mainnet).
| Name | Required | Description | Default |
|---|---|---|---|
| limit | No | max trades returned, 1-50, default 20 | |
| symbol | Yes | USDT perp symbol e.g. SOLUSDT | |
| min_usd | No | min print USD, default 100k |
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?
Since no annotations are provided, the description carries the full disclosure burden. It transparently discloses the paid nature of the call, including exact cost and payment rail ($0.02 USDC via x402 on Solana mainnet), and explains the data source and output categories. It does not fully describe return shape or time window, but the core behavioral context is present.
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 with no filler. The first sentence front-loads the core functionality and outputs; the second adds essential cost/payment 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 read-only tool with one required parameter, the description plus schema covers inputs, output categories, data source, and cost. The lack of an output schema is mildly mitigated by the listed output fields, though exact response structure and pagination are not specified.
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 already documents all three parameters with 100% coverage, including symbol, limit, and min_usd. The description's mention of a USD threshold reinforces min_usd but does not add materially new parameter semantics beyond the schema.
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 identifies a specific resource: large prints from the live trade tape for any USDT perp. It also enumerates the tool's outputs (buy/sell totals, net flow, dominant side), making it easy to distinguish from sibling market-data tools.
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?
No explicit when-to-use guidance or alternative tool comparisons are provided. The agent must infer the tool's purpose from the name and description alone, with no exclusions, prerequisites, or selection conditions.
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.