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beare

opennews-mcp

by beare

get_news_by_engine

Retrieve crypto news articles filtered by engine type. Choose from news, listing, onchain, meme, or market engines to get targeted updates.

Instructions

Get news articles filtered by engine type.

Engine types: "news", "listing", "onchain", "meme", "market".

Args:
    engine_type: The engine type code.
    limit: Maximum results (default 10, max 100).

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
limitNo
engine_typeYes
Install Server

TDQS

A3.6/5.0
Behavior3/5

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

No annotations are present, so the description carries the behavioral burden. It discloses the allowed engine_type codes and the max limit beyond what the schema provides, but says nothing about return format, ordering, pagination, errors, or what each engine type actually represents. Adequate for a simple read operation, but thin.

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

Conciseness5/5

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

The description is compact and well-structured, front-loading the core purpose and following with a clear Args list. Every sentence contributes either the operation, allowed values, or parameter behavior, with no filler.

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?

For a two-parameter read tool, the core invocation details are present, including required engine_type and optional limit with defaults. However, with no output schema and no annotations, the description does not mention the result shape, invalid-value behavior, or how this tool fits among the many sibling news tools, leaving meaningful gaps.

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?

Schema description coverage is 0%, so the description must compensate. It adds meaning by defining engine_type as the engine type code with five allowed values, and it adds a maximum of 100 for limit that the schema lacks. This is valuable beyond the structured schema, though it does not explain the semantic differences between engine types.

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 states 'Get news articles filtered by engine type' — a specific verb and resource — and enumerates the five engine type values. It clearly differentiates this tool from siblings like get_news_by_source or search_news by naming the filtering dimension, though it does not explicitly name alternatives.

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

Usage Guidelines3/5

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

The description implies the tool is for engine-type filtering by providing the valid engine values and the default/max limit. It does not state when to prefer this tool over alternatives or when not to use it, so guidance is only implicit.

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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