A capped teaser of the on-chain agent-to-agent payment graph.
Returns connected agents (nodes) and the value flowing between them (edges), capped to a small connected sample (≤200 nodes). This is a truncated preview, not the full network. Use it to see who pays whom in the agent economy; the full graph — every node and edge with amounts — is the paid endpoint below.
| 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?
No annotations are provided, but the description discloses that the tool returns a truncated preview (capped to 200 nodes), which is a key behavioral trait. It does not discuss safety, authorization, or rate limits, but for a read-only teaser, the disclosed information is adequate.
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 three sentences long, with each sentence serving a distinct purpose: defining the tool, describing the output, and providing usage guidance. No redundant information, perfectly concise.
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?
Given no parameters, no output schema, and simple sibling tools, the description is fairly complete. It explains the output and usage, but could have added a note about being read-only or safe. Still, it provides enough for agent selection.
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?
There are no parameters (schema coverage 100%), so the description does not need to add parameter info. However, it compensates by explaining the return values (nodes, edges, capped). The baseline for 0 parameters is 4, and the description meets that.
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 it returns a capped subset of the agent-to-agent payment graph (nodes and edges) with a limit of ≤200 nodes. It distinguishes itself by mentioning a full paid endpoint, and the sibling tools are different types (summary, stats, leaderboards), so there is no ambiguity.
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 says 'Use it to see who pays whom in the agent economy; the full graph... is the paid endpoint below,' which gives an implicit usage context but does not explicitly state when not to use it or compare to sibling tools. It provides enough guidance for a simple tool.
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 distinct aspect: single-agent summary, overall economy stats, leaderboards, and payment graph preview. No overlap or ambiguity.
All tool names follow a consistent 'get_' prefix with descriptive nouns (summary, stats, leaderboards, teaser). No mixing of conventions.
Four tools are well-scoped for a trust filter server, covering individual vetting, market sizing, rankings, and network preview without being too few or too many.
The tool set provides a complete free-tier coverage for trust assessment: check an agent, understand the ecosystem, find top agents, and see payment connections. No obvious gaps for the stated purpose.
