FairStash — Roblox trade values

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

Annotations already mark this as read-only and non-destructive. The description adds useful behavioral details beyond the schema: the tool returns a verdict with a percentage gap, accepts player-style phrasing including Russian, infers the game when omitted, and refuses mixed-game trades because their scales are incompatible.

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 compact sentences deliver the core behavior, output, input style, and a key constraint. Examples are illustrative without bloating the description, and the most important information about the verdict comes first.

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 a simple, read-only evaluation tool with three well-documented parameters and no output schema, the description covers input format, language support, game inference, cross-game refusal, and the nature of the result. The only minor omission is an exact example of the output structure, but the stated 'win, fair or lose' plus percentage gap is sufficient for an agent to invoke it 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?

Schema description coverage is 100%, so each parameter is already documented. The description still adds meaningful context: the 'game' parameter is optional and may be inferred from item names, and give/get should use comma-separated player-style phrasing rather than internal item IDs. The Russian-language examples further clarify accepted input.

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 states a specific verb and resource: it 'adds up both sides of a proposed trade' and returns 'win, fair or lose' with the percentage gap. This clearly differentiates check_trade from the sibling tools get_value, list_values, and search_items, which are about looking up values or lists rather than evaluating a trade.

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 clarifies when the tool applies: a single game's trade, phrased the way a player would say it, and it explicitly says mixed-game trades are refused. It does not name alternative sibling tools directly, but the trade-specific framing and constraints make the intended use clear.

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=true and destructiveHint=false, and the description adds meaningful behavioral context: values are community estimates rather than official prices)Skip; this prevents the agent from treating the result as authoritative. It also discloses the inclusion of a data-collection datecherish; with no contradiction and useful additions, this exceeds the baseline.

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 compact and front-loaded: the core purpose appears first, followed by return-value details, an application example, and an important caveat. Every sentence contributes value, and there is no redundant repetition of schema or annotation information.

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 sufficiently explains what the tool returns: community trade value, popularity, catalogue position, marketplace frequency, and collection date. It also manages expectations by noting that values are unofficial estimates, making the tool's behavior clear and usable without further 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?

Schema description coverage is 100% and both parameters are well documented in the schema. The description reinforces the item parameter with an example but does not add semantic detail beyond the schema, so the baseline score of 3 is appropriate.

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 states a specific verb ('look up'), a concrete resource (item value in Roblox trading games), and narrows the scope to three named games. It clearly differentiates this single-item value lookup from the sibling tools focused on checking trades, listing values, and searching items.

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 gives explicit use-case guidance with a concrete example question, making it clear when to invoke this tool. It does not explicitly mention when not to use it or name alternatives, but the provided application context is sufficient for an agent to route requests correctly.

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 cover the read-only, non-destructive, closed-world profile, and the description adds meaningful context on return shape and ordering. It doesn't discuss the limit/default behavior or any pagination concerns, but for a safe read tool this is solid extra detail.

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 core purpose and ordering, with the optional narrowing and example queries following. Slightly verbose with two example phrasings, but each sentence carries information.

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 output schema, the description usefully discloses that items carry community values and page links and are sorted most-valuable-first. Coverage of the limit/default behavior is left entirely to the schema, which is a minor gap for a listing tool.

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 all three parameters are already documented, including the MM2 section slugs. The description's section examples restate what the schema provides, so the baseline of 3 is appropriate.

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 (list) and resource (most valuable items) with the ordering (most valuable first) and the returned fields (community values, page links). This clearly separates it from siblings like get_value (single item) and search_items (query-driven).

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 concrete use cases ("what are the most expensive knives in MM2", understanding a game's scale) and explains the optional section narrowing. It does not explicitly name when to prefer search_items or get_value instead, so it stops short of full alternative routing.

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=true and destructiveHint=false, so the safety profile is covered. The description adds useful behavioral context: it searches across all three games and returns candidates rather than a single exact match. It does not disclose ranking or failure behavior, but that is a minor gap for a search tool.

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?

Two sentences, no filler. The core function and return payload come first, and the usage guidance is compact and direct.

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 output schema, the description still explains what the tool returns and in what context it should be used. Given the simple two-parameter input and safe read-only annotations, nothing essential is missing.

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 parameters are already fully documented. The description reinforces the partial-match semantics of query but adds little beyond what the schema provides.

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: finds items across all three games by partial name. It also names the return payload (candidates with game, value, page link), which clearly separates it from get_value and list_values.

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 says when to use it: when the name is ambiguous, misspelled, or could belong to more than one game. It also points the agent to get_value for the exact one, providing a clear alternative.

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