market_research

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

With no annotations provided, the description carries the full burden of behavioral disclosure. It only states that the tool returns findings with sources, which is minimal. It does not mention any side effects, safety traits, authentication needs, or limitations (e.g., read-only nature, rate limits, or data freshness). The description is too sparse to adequately inform the agent about 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, concise sentence of 14 words that is front-loaded with the core purpose. Every word is necessary and there is no redundancy or wasted text. It is an excellent example of conciseness.

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 tool's simplicity (2 parameters, no output schema, no annotations), the description is minimally adequate. It tells the agent what the tool does and what it returns, but it lacks context on default scope behavior, how to formulate effective queries, or any limitations. For a straightforward research tool, the description is functional but leaves gaps.

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 already provides 100% coverage on both parameters with descriptions. The description adds general context about the research domains (crypto, AI, competitive analysis) but does not add meaningful parameter-specific details beyond what the schema offers. Thus, the description adds only marginal value, meeting the baseline of 3 for high schema coverage.

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 performs general market research specifically on crypto trends, AI developments, and competitive analysis, and returns findings with sources. This is a specific verb+resource combination. However, it does not explicitly differentiate from sibling tools like ai_agent_research or defi_analysis, so it does not fully achieve a 5.

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 nor any conditions for use. It simply states what the tool does without any explicit when-to-use or when-not-to-use instructions, leaving the agent to infer usage context.

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