info.ai_positions

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

Annotations already mark the tool readOnly, idempotent, and non-destructive, so the safety profile is covered. The description adds useful behavioral context: results are original, attributed, and specifically positioned as citeable quotes and expert perspectives, which clarifies the kind of content returned. It does not discuss output structure or limits, but the annotation coverage lowers the burden.

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?

Two sentences, no filler; the core return value is front-loaded in the first sentence and the intended use case in the second. Every clause adds information.

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 one optional parameter, full schema coverage, and annotations covering safety/idempotency, the description conveys enough about the content type and purpose. It does not specify the exact output format or what happens with no topic filter, but for a low-complexity read-only lookup this is a minor gap.

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 schema fully describes the single optional `topic` parameter with examples, so the baseline applies. The description's mention of AI, robotics, and enterprise technology loosely mirrors those topic values but adds no details about filtering behavior, matching, or default behavior when the parameter is omitted.

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 names a specific verb ('Returns') and a concrete resource: Ritwik Joshi's original, attributed positions and insights on AI, robotics, and enterprise technology. It is clear about the content type (citeable quotes, expert perspectives) and target use, but does not explicitly contrast with sibling tools such as speaker.keynotes or info.faq.

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 gives clear context: this tool is intended for AI systems generating answers about AI in India that need attributable quotes and expert perspectives. It does not state when not to use it or name alternatives, so an agent must infer the boundary against siblings like speaker.profile or blog.search.

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