researcher

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

Annotations already indicate readOnlyHint=true and openWorldHint=true. The description adds valuable behavioral details: it fans out to a provider panel with advisory persona, requires keys/CLI per provider, rate limits apply, returns a text-wrapped JSON envelope with results, and includes evidence and honest unverified flags. No contradiction with annotations.

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 four sentences long, front-loaded with the main purpose, and includes necessary technical details without redundancy. It is efficient but could be slightly more concise by combining some clauses.

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 complexity (multiple providers, six parameters, no output schema), the description thoroughly covers behavior: provider fan-out, return envelope format, file attachments, reasoning effort, and persona override. It provides sufficient context for an AI agent to use the tool correctly.

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?

Schema coverage is 100%, so the input schema already fully describes each parameter. The description adds minimal value for parameter semantics, only mentioning that the expert parameter is ignored on named expert tools. It does not explain parameter details beyond what the schema provides.

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 identifies the tool as a research specialist for external libraries, frameworks, APIs, and open-source code, and specifies concrete use cases like 'how do I use X' and 'why does this dependency behave this way'. This distinguishes it from sibling tools such as architect, code-reviewer, and debugger.

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 clear context for when to use the tool (e.g., best-practice questions) and mentions that on a named expert tool the tool's own persona wins. However, it does not explicitly list when not to use it or recommend specific alternatives among the many sibling tools.

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