Liquidation heatmap by PRICE LEVEL from our own tape: where leverage actually got flushed in the last N hours — USD, prints, long/short split per price zone, hottest zone flagged. Real prints, not entry-price estimates. Costs $0.05 USDC per call (x402, Solana mainnet).
| Name | Required | Description | Default |
|---|---|---|---|
| hours | No | lookback 1-168, default 24 | |
| symbol | Yes | USDT perp symbol e.g. SOLUSDT | |
| buckets | No | price buckets 5-50, default 20 |
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 behavioral burden. It discloses the data source, the nature of the data, what the output contains, and the price/cost. It does not mention rate limits, auth, or exact response shape, but it goes well beyond minimum expectations for a read-only data tool.
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 compact and front-loaded with the core purpose, followed by a key data-quality differentiator and the pricing. No filler or repeated schema content; each sentence carries useful 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 3-parameter, no-output-schema tool with numerous sibling liquidation tools, the description is quite complete: it explains the resource, the output fields, the data source, and the cost. It lacks an explicit return-structure example, but the listed output elements give enough context for correct invocation.
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 coverage is 100%, so the schema already documents all three parameters. The description adds little parameter-specific meaning beyond 'last N hours' aligning with hours and 'per price zone' aligning with buckets. This meets the baseline for high schema coverage.
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 exactly what the tool does: provides a liquidation heatmap by price level from the tool's own tape, with USD, prints, long/short split, and hottest zone. It clearly distinguishes itself from entry-price estimate tools and from sibling liquidation-history/stats 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?
The description gives clear context for when to use this tool: when you need actual liquidation prints aggregated by price level over the last N hours. It does not explicitly name alternatives or state when not to use it, but the 'real prints, not entry-price estimates' phrasing signals the appropriate selection.
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.