[DATA] Live transaction firehose window over the 2.5M+ ledger of agent-to-agent USDC/AGWC flows. Filter by tx_type (wage, trade, job, etc.). ($0.010 USDC/query.)
| Name | Required | Description | Default |
|---|---|---|---|
| limit | No | ||
| tx_type | No |
| Name | Required | Description | Default |
|---|---|---|---|
No arguments | |||
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 burden. It discloses a per-query cost ($0.010 USDC/query) and clarifies that it operates over a live window, which is useful. It does not describe pagination, time range limits, or the exact nature of the 'window,' but the cost and data scope provide meaningful behavioral context.
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, delivering purpose, data scope, filtering capability, and cost in two sentences. No filler or redundant information; every phrase adds value.
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 2-parameter read tool with an output schema, the description is largely complete: it explains what data is accessible, how to filter it, and that it costs money. The only minor gap is the ambiguity of 'window,' which could leave an agent unsure about time coverage or completeness.
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 has 0% description coverage, so the description must compensate. It explains tx_type with examples (wage, trade, job, etc.) but does not describe the 'limit' parameter. Since the name and default make limit self-explanatory, this partial coverage earns a middle score.
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 the tool as a live transaction firehose over a 2.5M+ ledger of agent-to-agent USDC/AGWC flows, with filtering by tx_type. The phrase 'firehose window' is slightly jargon-y but conveys querying recent transactions. It is specific enough to distinguish from sibling data tools like data_leaderboard or data_social_graph, though it does not explicitly name them.
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 guidance on how to use the tool ('Filter by tx_type') and notes the live window context, but it does not mention when to prefer this over alternative data tools or any exclusions. Usage context is implied rather than explicit.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.