API-getStakersAndNodes
Retrieve stakers and nodes data from the RSS3 network to analyze network participation and infrastructure.
Instructions
Retrieve a list of stakers and Nodes
Input Schema
| Name | Required | Description | Default |
|---|---|---|---|
No arguments | |||
Retrieve stakers and nodes data from the RSS3 network to analyze network participation and infrastructure.
Retrieve a list of stakers and Nodes
| Name | Required | Description | Default |
|---|---|---|---|
No arguments | |||
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden of behavioral disclosure. It states the tool retrieves a list but doesn't specify whether this is a read-only operation, if it requires authentication, how results are formatted (e.g., pagination, sorting), or potential rate limits. This leaves significant gaps for an AI agent to understand the tool's behavior.
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 a single, efficient sentence that directly states the tool's purpose without any fluff or redundant information. It's appropriately sized and front-loaded, making it easy for an AI agent to parse quickly.
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 the lack of annotations and output schema, the description is incomplete. It doesn't explain what the returned list contains (e.g., fields, structure), how results are limited or ordered, or any error conditions. For a tool that likely returns complex data about stakers and nodes, this leaves the AI agent with insufficient context to use it effectively.
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 input schema has 0 parameters with 100% coverage, so no parameter documentation is needed. The description appropriately doesn't mention parameters, which aligns with the schema. A baseline of 4 is applied since it doesn't add unnecessary information beyond the schema's completeness.
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 the verb ('Retrieve') and resource ('list of stakers and Nodes'), making the tool's purpose understandable. However, it doesn't differentiate from sibling tools like 'API-getAllNodes' or 'API-getStakerStats', which appear to retrieve similar data subsets, so it doesn't achieve full sibling differentiation.
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 provides no guidance on when to use this tool versus alternatives. With sibling tools like 'API-getAllNodes' and 'API-getStakerStats' available, there's no indication of whether this tool combines data from both, serves a different scope, or should be preferred in specific contexts.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
We provide all the information about MCP servers via our MCP API.
curl -X GET 'https://glama.ai/api/mcp/v1/servers/RSS3-Network/mcp-server-rss3'
If you have feedback or need assistance with the MCP directory API, please join our Discord server