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

No annotations are provided, so the description carries the full behavioral burden. It discloses partial success semantics (each query returns a result or a structured error, one failure doesn't abort the rest), the rate-limit accounting (batch saves roundtrips, not quota), and that payloads, tier gates, and source attribution are identical to the single tools. This gives the agent a precise model of side effects and error handling.

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 dense but every sentence adds information: purpose, allowed tools, failure behavior, rate-limit nuance, payload equivalence, and an exclusion. It is front-loaded with the core value proposition. While it is a longer description, it avoids filler and is well-structured for an agent to scan.

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 there is no output schema and no annotations, the description adequately covers all essential details: the allowed set of reads, query count limits (1-6, enforced by schema), behavior on partial failure, rate-limit implications, and how to route any request outside the batch to a single tool. The agent has enough to call the tool correctly without additional context.

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 already describes the queries array and the tool enum, with 100% coverage. The description adds value by providing an explicit example ({tool: 'iv_snapshot', args: {currency: 'BTC'}}), clarifying that args map to the single tool's parameters, and noting that args should be omitted when the underlying tool takes none. This goes beyond the schema's generic 'Args of the underlying single tool' text.

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 batches multiple market snapshot reads into one call, and it enumerates the 14 specific supported reads (spot_price, pulse, cycle, etc.). This distinguishes it from the sibling single-read tools (arena_get_spot_price, arena_get_cycle, etc.) and leaves no ambiguity about which tool to use for batching.

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 explicitly tells the agent when the batch tool is appropriate (multiple reads of the listed types) and when it is not: 'For history tools, backtests or anything not in the list, call the single tool.' It also explains the practical benefit (saves roundtrips, not quota) and gives a concrete example of query construction, so the agent knows exactly how to invoke it.

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