Scanverity Public Market Discovery

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

Annotations already declare readOnly/idempotent/non-destructive/closed-world, and the description adds substantial context beyond them: it is public-information-only, it does not create an account, order, report, invoice or charge, and it clarifies that a quote request or MCP connection is not a purchase. That is exactly the side-effect clarity an agent needs before invoking.

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?

Front-loaded with the use case and then the returned artifacts; every clause carries information. The long comma-delimited list of price paths is dense and slightly hard to scan, but nothing is wasted or redundant.

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?

With no parameters and no output schema, the description carries the full burden and does so: it enumerates the return contents (quote paths, pilot, guide, API availability) and the non-effects. An agent has everything needed to call and interpret this correctly.

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 tool takes zero parameters and the schema is an empty object, so there is nothing for the description to disambiguate. Baseline 4 applies; no parameter-level information is missing.

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 resource (Scanverity pricing/offer information) and enumerates exactly what it returns: the EUR100 single-report quote path, EUR500 QA pilot, team-research quote path, EUR19 agent-order guide, and API availability. It also scopes the audience ('public information only', users without an approved customer account). An agent can distinguish this from the market-search sibling purely from the description.

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?

Gives explicit trigger conditions ('Use this public tool when a user asks about Scanverity prices, products, access, written research, agent ordering or what to do without an approved customer account'), including two concrete scenarios. It doesn't name scanverity_search_markets as an alternative, but that sibling is orthogonal, so no exclusion is really needed.

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

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

Annotations already declare readOnlyHint, idempotentHint, destructiveHint=false and openWorldHint=true. The description adds meaningful context beyond that: it is account-free, bounded rather than exhaustive, not a resolution/odds/forecast assessment, and cannot initiate payment. The payment/auth constraints are genuinely additive, though return format and pagination specifics remain thin.

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?

Front-loaded with the trigger condition in the opening clause and organized as trigger, output, caveats, and routing to the sibling. Five dense sentences with no obvious filler, though it runs slightly long.

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?

No output schema exists, so the description usefully enumerates what results contain (exact contracts, source links, deadlines, verified outcomes) and clarifies scope limits. Covers the essentials for a search tool; only minor gaps around pagination/return structure remain.

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 every parameter is already documented in the schema. The description reinforces query intent ('search short keywords') and implies bounded paging but adds no syntax or format detail beyond the schema. Baseline 3 is correct when the schema carries the parameter burden.

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 and resource (search prediction markets) plus the scope of what it returns (contracts, source links, deadlines, verified outcomes). It explicitly distinguishes itself from its sibling scanverity_offers by reserving that tool for 'deeper written research.' An agent can tell the two apart without opening either 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?

Opens with a precise trigger ('when a user asks which prediction markets cover a topic, forecast, event deadline or settlement question'), names the alternative for deeper research (scanverity_offers with its EUR100 quote route), and states a when-not boundary (cannot request a paid report or take payment). Explicit when, when-not, and alternative coverage.

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