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SweetAI — On-chain AI Agent Intelligence

get_a2a_relationships

A2A platební graf agentů: top hrany (kdo→komu, USDC), recurentní platby ('předplatné mezi stroji'), huby (cíle s mnoha plátci = infra uzly).

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
limitNo
window_hoursNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

C2.8/5.0
Behavior2/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

No annotations are provided, so the description carries the full behavioral burden, and it discloses almost nothing beyond subject matter. It does not state that this is a read-only analytics query, does not explain the time window semantics (window_hours default 720) or result freshness, and does not mention the row cap implied by limit=50. The one useful interpretive hint — that hubs are 'infra nodes' — is domain framing rather than behavior.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

A single dense sentence that front-loads the subject (A2A payment graph) and then lists the three output categories in a scannable parenthetical structure. Nothing is padded, though the lack of an explicit verb makes the opening slightly less immediately actionable.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness3/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

An output schema exists, so return-value documentation is not required, and the description does convey what the graph is composed of. However, with zero annotation coverage and both parameters undocumented, an agent still lacks the usage and parameter context needed to call this correctly, leaving the definition adequate but incomplete.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters2/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 0% for both limit and window_hours, so the schema contributes nothing and the description must compensate. It never mentions either parameter or what a window or limit means for the returned graph, so the agent has no basis for choosing values beyond the bare defaults.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description names a specific resource and enumerates the concrete outputs an agent will get: top edges (who→whom, USDC), recurrent payments, and hub detection. That is far more specific than the sibling names like get_signals or get_trending_agents, and it clearly scopes the tool to the A2A payment graph rather than reputation, liveness, or SLA. The verb is only implied by the tool name, so it stops short of a 5.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines2/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

There is no when-to-use statement, no condition that distinguishes this from get_trust_forensics, get_reputation_summary, or the other graph-adjacent siblings, and no prerequisites or exclusions. The agent must infer from the noun phrase 'A2A payment graph' alone that this is the tool for machine-to-machine payment flow analysis.

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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