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

With no annotations, the description carries the full behavioral disclosure burden. It does disclose the key behavioral attributes: it returns movers, covers both gainers and losers, uses a 24h price change window, and scopes to the Robinhood Chain RWA universe. It does not mention ordering, pagination, or whether both sides are limited separately, but this is sufficient for a simple read-oriented 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?

The description is a single, focused sentence with no filler. It front-loads the core output and immediately adds the universe scope and timeframe, making it both concise and informative.

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 the tool's low complexity, one optional parameter, and no output schema, the description is largely complete. It tells the agent what the tool returns and the universe/timeframe, but it does not describe the response shape or explicitly differentiate from sibling tools.

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 input schema already documents the single parameter 'limit' with a clear description and default value, so schema coverage is 100%. The tool description adds no additional parameter semantics, 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 clearly identifies the tool's resource: top gainers and losers within the Robinhood Chain RWA universe. It specifies the timeframe (24h price change), which distinguishes it from generic price or search tools. However, it lacks an explicit verb like 'returns' or 'lists', so it is clear but not maximally explicit.

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 does not state when to use this tool versus alternatives such as get_price, search_token, or list_universe. It implies use for market movers, but there is no explicit guidance on when it is appropriate or when a sibling tool would be better.

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?

With no annotations, the description carries the full burden of disclosing behavior. It usefully reveals that stablecoins return 1 and ETH is priced via WETH, which are non-obvious. It does not mention what happens for unknown symbols or whether the price is a number, but the core behavior is reasonably exposed.

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 short sentences with no filler. The primary purpose is stated first, and the special cases are added in the second sentence efficiently.

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 one-parameter tool, the description covers the core use and important exceptions (stablecoins, ETH/WETH). It does not specify return shape, but the absence of an output schema and the simplicity of the task make this a minor gap.

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 input schema already describes the symbol parameter with examples, and schema coverage is 100%. The description adds value by noting special symbol cases, but it does not materially expand on the parameter's meaning 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 the tool returns the USD price for a single symbol, which distinguishes it from list/search/movers siblings. It does not use an explicit verb like 'get' or 'return', but the meaning is unambiguous and specific.

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 phrase 'for a single symbol' implies when to use it, and the special handling of stablecoins and ETH adds useful context. However, it does not explicitly compare with sibling tools like search_token or list_universe, nor state 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.

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

With no annotations, the description carries the burden of behavioral disclosure. It adds meaningful context: the list is curated, resolved to live verified markets, and counterfeit tickers are filtered out. However, it does not mention response shape, pagination, ordering, or whether results are real-time, leaving some behavioral aspects undisclosed.

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, with two sentences that each earn their place: one defines the universe and its verification behavior, the other explains the optional filter. There is no redundant or filler wording.

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 one-optional-parameter list tool, the description covers the essential aspects: what is listed, the asset categories, the fact that results are curated/verified, and the filtering capability. It does not describe the return format, but given the tool's simplicity and lack of output schema, the description is largely 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 the baseline is 3. The description's 'Optionally filter by category' adds no meaning beyond the schema's parameter description, though the enumerated asset types in the first sentence do reinforce the enum values. No additional syntax or format details are provided.

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 identifies the resource: a curated universe of tokenized asset types on Robinhood Chain, and implies the list operation from the tool name. It distinguishes itself by emphasizing verified, counterfeit-filtered assets, which sets it apart from search-oriented siblings, though it does not explicitly name a sibling.

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 says the result can be filtered by category but gives no explicit guidance on when to use this tool versus search_token or search_markets. The use case is only implied: when you want the full curated universe, not a free-text search. No exclusions or alternatives are mentioned.

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?

With no annotations, the description must bear the burden. It does disclose useful behavior: results span 'all chains', are 'ranked by 24h volume', and are 'candidate' markets rather than guaranteed matches. However, it omits output shape, pagination, or any caveats about the candidate nature. The disclosed behaviors are helpful but incomplete.

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 with no fluff: the first states purpose and ranking, the second gives usage direction. The core behavior is front-loaded and every word earns its place.

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 two-parameter list tool with no output schema, the description covers what the tool does, its scope, ranking order, and when to use it. A small gap is that it does not describe the shape of the returned markets, but 'List ... markets' implies a list and the absence of an output schema lowers the burden.

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 schema covers both parameters with descriptions (query as 'Ticker symbol or token name', limit with min/max/default), so the baseline is 3. The description only says 'for a query', which adds no new meaning beyond the schema. It does not clarify query format or how limit interacts with ranking.

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 opens with a specific verb and resource: 'List candidate DEX markets for a query across all chains, ranked by 24h volume.' It clearly distinguishes the tool from siblings by emphasizing 'candidate' alternatives and 'across all chains', and by contrasting with the 'single best match' implied to be handled elsewhere.

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 an explicit usage trigger: 'Use when you need alternatives beyond the single best match, or to compare venues for the same asset.' This provides clear decision context, though it does not name the sibling tool for the single best match directly, so it stops short of fully explicit when-not/alternative guidance.

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?

With no annotations provided, the description carries the burden of behavioral disclosure and mostly succeeds. It reveals the selection preference (Robinhood Chain pairs, then honest stable-quoted volume) and states exactly what fields are returned. It doesn't mention caching, staleness, or error behavior, but for a read-only search tool this is reasonably transparent.

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 deliver the purpose, scope, selection logic, and output fields without redundancy. The most important usage information is front-loaded, and every clause earns its place.

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 a single required parameter and no output schema, the description covers the input semantics, selection behavior, and return fields well. Minor gaps remain around the exact behavior when no matching market exists and whether the result is a single market object, but the tool is sufficiently specified for correct invocation.

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 for the single parameter is 100%, and the schema already explains that 'query' is a ticker symbol or token name. The description reinforces this with examples (AAPL, TSLA, WETH) but adds little new semantic information beyond confirming search can match names as well as symbols.

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 clear verb and resource: find the best live market for a token using a ticker or name. It also provides examples and lists returned fields, making the tool's purpose concrete. However, it does not explicitly distinguish this from sibling tools like search_markets or get_price, so it stops short of full sibling differentiation.

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 when to use the tool: when an agent needs the best live market for a token by ticker or name. It does not, however, state when to prefer search_markets, get_price, or other alternatives, nor does it give exclusion criteria such as 'use get_price for a simple quote'.

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