TVL for any DeFi protocol (with 1d/7d change) or top-15 chains ranking. DefiLlama-backed. Costs $0.005 USDC per call (x402, Solana mainnet).
| Name | Required | Description | Default |
|---|---|---|---|
| target | No | protocol slug/name e.g. jito, marinade — omit for top chains |
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 burden and does disclose important operational traits: DeFiLlama-backed data, $0.005 USDC cost per call, x402 on Solana mainnet, and 1d/7d change fields. It does not describe the exact response shape, but the purpose statement implies the returned content well.
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: the core purpose appears first, followed by the data source and cost. Every sentence earns its place with no fluff.
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 tool with one optional parameter and no output schema, the description covers purpose, alternatives mode, example behavior, and the cost/payment rail. The main gap is lack of a concrete response shape, but the tool is simple enough that this is a minor omission.
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% and the target parameter is already described with examples and the omit-for-top-chains behavior. The description adds little beyond the schema, but for a single optional parameter the schema fully carries the meaning.
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 what the tool does: fetch TVL for a DeFi protocol or top-15 chains ranking, backed by DefiLlama. It names a specific resource and behavior, and there is no obvious sibling tool with the same purpose.
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 usage context: provide a protocol slug/name or omit for top chains. It does not explicitly name alternatives or exclusions, but the sibling list contains no direct TVL duplicate, so the guidance is sufficient.
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.