Bid/ask resting-liquidity imbalance within ±N bps of mid for any USDT perp: USD each side, ratio, skew read. Costs $0.01 USDC per call (x402, Solana mainnet).
| Name | Required | Description | Default |
|---|---|---|---|
| bps | No | window ±bps around mid, 5-500, default 50 | |
| 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?
No annotations are provided, so the description carries the behavioral disclosure burden. It explicitly discloses the $0.01 USDC cost, the x402/Solana mainnet execution path, the read-only nature of the call, and the output fields. It does not mention rate limits or error behavior, but the most important behavioral traits are covered.
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?
Two concise sentences deliver the metric, scope, output fields, cost, and execution network with no filler. The core concept is front-loaded, making it easy for an agent to scan and act on.
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 simple two-parameter read with no output schema, the description provides the essential invocation context: input universe, window semantics, output fields, and cost/network. It stops short of specifying exact return shape or sign conventions, but nothing critical for deciding whether to call the tool is missing.
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?
Schema description coverage is 100%, so both bps and symbol are already documented with types, ranges, defaults, and examples. The description reinforces that the symbol must be a USDT perp and that bps is the window size, but it adds no meaningful parameter information 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 states the exact metric (bid/ask resting-liquidity imbalance within ±N bps of mid), the applicable universe (any USDT perp), and the returned outputs (USD each side, ratio, skew). This clearly differentiates it from sibling tools like get_orderbook_walls, which focus on walls rather than imbalance.
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?
The description implies when to use the tool—when an orderbook imbalance within a bps window is needed for a USDT perpetual—but it does not explicitly compare to alternatives or state when not to use it. The cost warning is useful operational context but does not serve as a routing guideline.
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.