get_social_sentiment_endpoints

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 describes what endpoints are included (e.g., social media analytics, sentiment analysis) but does not mention critical behaviors such as whether this is a read-only operation, if it requires authentication, rate limits, or what the output format looks like. For a tool with zero annotation coverage, this is a significant gap in transparency.

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 front-loaded with the core purpose in the first sentence, but it becomes verbose with a long list of examples (e.g., 'Galaxy Score™, AltRank™') that could be condensed. While informative, some sentences do not earn their place by adding critical value beyond the initial scope, reducing efficiency.

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 complexity (a tool retrieving endpoints with no output schema and no annotations), the description is incomplete. It details the category content but fails to explain the return format, pagination, error handling, or other behavioral aspects. Without annotations or an output schema, the description should provide more context to be fully helpful.

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 the schema fully documents the lack of inputs. The description does not add parameter information, which is unnecessary here. Since there are no parameters, the baseline score is 4, as the description does not need to compensate for any schema gaps.

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 tool's purpose: 'Get all endpoints in the "Social Media & Sentiment Analytics" category.' It specifies the resource (endpoints) and the category scope. However, it does not explicitly distinguish this tool from its siblings (e.g., get_defi_protocol_endpoints, get_market_and_price_endpoints), which all follow a similar 'get [category] endpoints' pattern, so it lacks 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. It lists the types of endpoints included but does not mention prerequisites, exclusions, or comparisons to other tools (e.g., when to use get_search_discovery_endpoints instead). This leaves the agent without explicit usage instructions.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.