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

Annotations already cover read-only, idempotent, non-destructive, closed-world behavior, so the bar is lower. The description still adds real value by disclosing the return shape ('verdict status and a plain-language teaser') and an important limitation ('exact thresholds are not public'), which prevents an agent from promising precise numbers.

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?

Three tight sentences: what it is, when to use it, what you get back. The most decision-relevant facts (scope and trigger) are front-loaded with no filler.

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?

Output schema exists, so return-value detail is optional, and the safety profile is fully annotated. Minor gaps remain: it does not mention the 25-result cap or any paging behavior, which an agent querying a registry might need.

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 coverage is 75% and the enums (asset, group) are already self-documenting. The description implies what the 'group' filter is for by emphasizing rejected hypotheses, and its example keywords ('max pain', 'whales') mirror the query parameter, but it adds no syntax or semantics for limit.

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?

Names a specific verb and resource ('Search INDICIA DESK's public registry of BTC/ETH market beliefs tested on its own data') and adds distinguishing scope ('including the rejected ones'). This is clearly separable from siblings like market_state or decision_journal, which do not return tested-belief verdicts.

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?

Explicitly states the trigger condition: 'Use when someone asks whether a popular crypto trading belief holds,' backed by three concrete example questions. It stops short of naming alternatives or when-not conditions, so it is clear but not fully routing.

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