get_v1_bittensor_derivatives_subnets_all

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

With no annotations, the description must disclose behavioral traits. It mentions it's a 'snapshot' (implies point-in-time data) and lists the price and category. However, it lacks details on data freshness, response format, or any limitations, which is only partially transparent.

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 three clear, front-loaded sentences with no wasted words. It conveys purpose, usage, and pricing efficiently.

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?

While it lists the data fields, it lacks an output schema and doesn't fully describe the return structure (e.g., format, pagination, ordering). For a snapshot of all subnets, more detail on response organization would improve completeness.

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?

There are no parameters, and schema coverage is 100% by default. The description adds no parameter info because none exist. Baseline 3 is appropriate; no extra value or deficit.

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 it returns a 'Snapshot of all 129 Bittensor mainnet subnets' and lists the specific data fields (burn, neurons, owner, modality, alpha-price). This distinguishes it from sibling tools that target individual subnets or specific metrics like alpha prices.

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?

It explicitly says 'For cross-subnet research and market-overview dashboards,' providing clear usage context. While it doesn't mention when not to use or alternatives, the context is sufficient for an agent to understand its broad-scope application.

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