check_token_risk_batchSame as check_token_risk but for up to 25 mints in one call — N mints charged as N calls, same per-call economics as check_token_risk, no bulk discount. All-or-nothing: if the batch can't be fully covered by remaining quota/credit, the whole batch is rejected rather than partially processed.
| Name | Required | Description | Default |
|---|---|---|---|
| mints | Yes | 1-25 Solana token mint addresses |
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 a good job: it discloses batching limits, per-call billing equivalence, no discount, and all-or-nothing rejection. It still relies on referencing check_token_risk for the actual risk-check behavior and does not describe the return format, but the critical behavioral traits are disclosed.
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 sentences contain all necessary information, with the core batching purpose front-loaded. The billing and quota behavior are compactly stated with no filler.
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 covers invocation scope, limits, billing, and failure behavior. It is slightly incomplete only in that it defers the actual risk-check semantics to check_token_risk rather than describing them, but this is acceptable for a thin batch wrapper.
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 provides 100% coverage of the sole parameter with a clear description ('1-25 Solana token mint addresses'). The description adds billing and batching semantics but no new syntactic or format details beyond what the schema provides, so the baseline 3 applies.
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 tool is the same as check_token_risk but for up to 25 mints in one call, which clearly identifies the verb (check risk), the resource (Solana tokens), and the batch scope. It differentiates from the sibling check_token_risk by batching and from get_token_risk_history by being a risk check rather than history.
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 says the tool should be used instead of check_token_risk when you have up to 25 mints in one call, and it explains the economics (N mints charged as N calls, no bulk discount) and the all-or-nothing quota behavior. These are concrete conditions for choosing this tool over the single-mint sibling.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Add one secure layer between your agents and this server.
Each tool targets a clearly distinct operation: live single-mint risk check, batched multi-mint risk check, and historical risk data retrieval. The single vs. batch distinction is explicit in the names and descriptions, so there is no meaningful overlap or selection ambiguity.
All tools follow a consistent snake_case verb_noun pattern (check_token_risk, check_token_risk_batch, get_token_risk_history). The 'batch' suffix clearly modifies the object, and the switch from 'check' to 'get' appropriately distinguishes live assessment from historical data.
Three tools is lean but well-scoped for a focused token-risk API: a single check, a batch check, and a history lookup. Each tool fills a distinct role with no redundant or filler endpoints.
The core workflow—assess one token, assess many tokens, retrieve history—is fully covered. Minor gaps exist, such as no way to query remaining quota/credit before a batch call and no token metadata/lookup endpoint, but agents can work around these.