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

Annotations already declare readOnlyHint=true and destructiveHint=false. The description adds valuable context: it costs $0.02 USDC, is a pollable stream, and returns specific data (caller's measured record, deployer score, FDV). No contradictions 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 two sentences plus a brief cost note. It is well-front-loaded with the core concept. The cost note and instructions reference are slightly extraneous but do not harm clarity. Could be slightly tighter, but overall efficient.

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 no output schema, the description explains what each item carries (caller record + deployer score + FDV). It covers filtering criteria and cost. It does not detail pagination or ordering, but as a pollable stream with a since cursor, the essential mechanics are implied.

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?

All three parameters are documented in the schema with 100% coverage. The description adds extra context by stating default filter values (early_rate >= 0.5, >=4 calls) and that the since parameter is a captured_at cursor, enhancing understanding beyond the schema.

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 is a pollable stream of fresh Robinhood Chain calls filtered by measured early-callers with specific criteria (early_rate >= 0.5, >=4 calls, excluded clusters). It uniquely positions itself as the highest-alpha event in the corpus, distinguishing it from siblings like robinx_caller_calls or robinx_feed.

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 implies usage for high-alpha signal retrieval and mentions it is pollable. It does not explicitly list when to use versus alternatives or when not to use, but the context of 'measured early-callers' and 'highest-alpha event' gives clear contextual guidance.

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