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RSS3-Network

RSS3 MCP Server

Official
by RSS3-Network

API-getAIDataByPath

Retrieve AI data from decentralized chains, social media platforms, and the RSS3 network using specific paths for querying information through natural language integration.

Instructions

Retrieve AI data by Path

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Behavior1/5

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

No annotations are provided, so the description must fully disclose behavioral traits. It only states the action ('Retrieve') without mentioning permissions, rate limits, response format, or error handling. For a tool with zero annotation coverage, this is inadequate as it fails to convey any operational context beyond the basic purpose.

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

Conciseness3/5

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

The description is concise with a single phrase, but it's under-specified rather than efficiently informative. It front-loads the core action but lacks necessary elaboration for clarity. While not verbose, it fails to earn its place by omitting key details, making it more of a placeholder than a helpful description.

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

Completeness2/5

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

Given the tool's apparent complexity (retrieving data by a 'Path'), no annotations, and no output schema, the description is incomplete. It doesn't explain what 'AI data' includes, how the 'Path' is structured, or what the return values look like. For a tool in a context with many similar siblings, this leaves significant gaps in understanding its role and behavior.

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

Parameters4/5

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 parameters need documentation. The description doesn't add param details, which is acceptable since there are none to explain. A baseline of 4 is appropriate as the schema fully covers the parameter semantics by indicating no inputs are required.

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

Purpose2/5

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

The description 'Retrieve AI data by Path' states the verb ('Retrieve') and resource ('AI data'), but it's vague about what 'AI data' entails and what 'Path' refers to. It doesn't differentiate from sibling tools like 'API-getRSSActivityByPath' or 'API-get_ai_intels_api_v1_ai_intel_get', which might retrieve similar data. This is a tautology that mostly restates the tool name without specificity.

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

Usage Guidelines1/5

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-get_ai_intels_api_v1_ai_intel_get' that might retrieve AI-related data, there's no indication of context, prerequisites, or exclusions. This lack of usage guidelines leaves the agent guessing about appropriate scenarios.

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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