compare_personas

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

Annotations cover safety (readOnlyHint=true, openWorldHint=false), and the description adds real behavioral substance beyond them: it discloses the computation (full annual all-in stack per persona per venue) and the demotion logic ('headline winners with no fiat/withdrawal rail are demoted') plus the best_complete pick semantics. That is genuinely useful context an agent would not get from 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 trigger condition is front-loaded, which is good, but the paragraph is long and the Chinese and English halves largely duplicate each other, so a substantial fraction of the text is redundant rather than additive.

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?

For an 11-parameter, no-output-schema tool, the description carries the burden of explaining return shape and largely does so (per-persona winner, best_complete pick, persona×venue matrix, win counts, most versatile venue). It is complete enough to call correctly, though a few optional parameters (spreadMode/fundingMode behavior) live only in the schema.

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 description coverage is 100%, so the 11 parameters are already documented in the schema. The description only restates that country is required and that personas/useToken are optional, adding no syntax or format detail beyond the schema. Baseline 3 is appropriate when the schema does the heavy lifting.

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?

States a specific verb+resource (run all 7 persona stacks side-by-side for a country) and explicitly scopes it as a single-call multi-persona comparison, which distinguishes it from the sibling analyze_persona (single persona). An agent can tell what it produces without opening the schema.

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?

Front-loads explicit trigger conditions in Chinese ('当用户想…时使用') and mirrors them in English ('Use when the user wants a side-by-side decision matrix of ALL trader personas…'). It gives clear context for when to reach for this tool but never names the alternative (analyze_persona) or states when-not to use it.

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