get_active_research

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

No annotations are provided, but this is a zero-parameter read/list tool, so the behavioral surface is small. The description does not say whether results are static, cached, or how 'active' is determined, and only implies read-only through the verb 'List'. Adequate but not rich.

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 purpose is front-loaded in the first sentence, followed by the content inventory and a usage cue. The five-topic enumeration is somewhat list-heavy but each item conveys real scope rather than filler.

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?

Since there is no output schema, the description usefully enumerates the returned content so the agent can anticipate the response. For a zero-param read tool with no annotations, this is nearly complete; only return format/pagination details are absent.

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?

With zero parameters the baseline is 4; there is no input to document and the schema is trivially complete. The description correctly provides no parameter noise.

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 states a specific verb+resource (list Ali Can Efe's current research interests and active work) and enumerates the exact topics covered, so the agent knows what it will get. It implicitly distinguishes itself from get_projects/get_project_details but never names those siblings explicitly.

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 closing sentence gives clear triggering conditions ('Use when user asks about Ali's research focus areas or forward-looking work'), which is solid positive guidance. It stops short of stating when NOT to use it or naming query_expertise/get_projects as the alternative for project-level or broader questions.

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