Coinfuty

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

No annotations are provided, so description carries the burden. It describes the live data fields and mentions sorting/filtering, but does not explicitly state read-only nature, return format, or any limitations (e.g., max rows). This is adequate for a list tool but lacks depth.

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 one concise sentence plus two short clauses. It front-loads the core action and packs the data fields efficiently without redundancy.

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 simplicity (list with filters) and full schema coverage, the description covers the main functionality and data returned. It lacks details on response structure but that's not required since no output schema exists, though such info would be helpful.

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 already documents all 4 parameters with 100% coverage. The description adds context by mentioning 'Sortable' and 'filter to specific symbols with `symbols`', which reinforces the purpose of the sort and symbols parameters beyond their schema descriptions.

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 starts with 'List coins with live futures market data' which clearly states the action and resource. It enumerates specific data fields (price, open interest, funding rate, etc.), distinguishing it from siblings like get_funding_rates which focuses only on funding rates.

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 provides context on usage (sortable, filterable) but does not explicitly state when to choose this over siblings like get_funding_rates or get_market_overview. 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 carries the full burden of disclosure. It thoroughly lists what data is returned and even notes the OI-weighted aggregate for funding rates. It does not cover potential edge cases like rate limits or response structure, but the level of detail is strong for a snapshot 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 concise sentences. The first sentence lists the content in a clear, front-loaded format; the second provides a memorable usage recommendation. No wasted words.

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?

The description enumerates all major return components, which is important since there is no output schema. However, it could benefit from clarifying the structure (e.g., per-exchange values vs. aggregate), but the information provided is sufficiently complete for a summary 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 coverage is 100% for the single 'symbol' parameter, which is already described as 'Coin ticker, e.g. BTC'. The description adds no additional parameter semantics (e.g., case sensitivity, whether to include the 'USDT' suffix), but given the high schema coverage, 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?

The description clearly states it provides a 'Full derivatives snapshot for one coin' and enumerates the exact metrics included (price, open interest, volume, liquidations, long/short ratio, funding rate). This distinguishes it from sibling tools that focus on narrower aspects like funding rates or exchange breakdowns.

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 explicitly claims it is 'The single best tool for “what's happening with X futures”', which gives clear context for when to use it. However, it does not explicitly mention alternative tools or conditions when a different tool might be more appropriate.

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 full burden. It discloses key behaviors: window is ignored for oi, and `total` is the coin-level aggregate. It also details what each metric returns (e.g., long_short returns ratio and taker buy/sell volume). While it does not discuss error handling or rate limits, it transparently explains the tool's core behavior.

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 two sentences long and packs all essential information. The first sentence states the purpose, and the second lists each metric with its return details. No redundant or vague wording; every clause contributes to understanding the tool.

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 complexity (three params, no output schema), the description covers the main aspects: purpose, metric behaviors, and the window exception. It does not describe output structure or error cases, but for a data retrieval tool, it is sufficiently complete. Sibling tools are contextually distinct, so no ambiguity remains.

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 description adds significant meaning beyond the schema. The schema only lists the metric enum without descriptions, but the description explains exactly what each metric value returns. It also clarifies the window parameter's behavior (ignored for oi). This fully compensates for the schema's lack of metric description, making parameter semantics clear.

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's function: 'How one coin's futures activity splits across exchanges.' This is a specific verb (splits) with a clear resource (coin's futures activity by exchange). It distinguishes itself from siblings by focusing on per-exchange breakdown, which is unique among the listed tools.

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 provides clear context on what each metric returns, which implies when to use this tool (when per-exchange data is needed). However, it does not explicitly mention alternative tools or exclusions, such as using get_market_overview for an aggregate market view. The guidance is understood but not directly stated.

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?

No annotations are provided, so the description carries the full burden. It discloses the output scope (per exchange, included metrics like current rate, accumulated periods, settlement interval, next funding time, and OI-weighted aggregate). It does not mention potential errors, rate limits, or that it is a read-only call, but the read-only nature is inherent. This is a strong behavioral disclosure for a data-fetch 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, dense sentence that front-loads the primary action and resource. It packs in field specifics without excessive verbosity. Slightly long but every phrase adds value, so it earns a 4.

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 needs to enumerate the return contents, and it does so thoroughly (current rate, accumulated 1d/7d/30d/1y, settlement interval hours, next funding time, OI-weighted aggregate). It does not explain what happens for invalid symbols or when no exchange lists the coin, but for a simple parameter tool this is largely sufficient.

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 already fully documents the single parameter 'symbol' with a clear description ('Coin ticker, e.g. BTC'). The tool description adds minor context ('for one coin') but does not significantly expand parameter meaning beyond the schema. With 100% schema coverage, a 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?

The description clearly states the tool returns 'Current and accumulated funding rates for one coin on every exchange that lists it', which is a specific verb ('get') and resource ('funding rates'). It distinguishes from sibling tools like get_price_history (prices) and get_exchange_breakdown (exchange data), making its purpose unmistakable.

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 funding rate data is needed) but does not explicitly compare it to alternatives or state exclusions. It is clear that it is for a single coin across exchanges, but there is no guidance on when to choose this over related tools.

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 full burden of behavioral transparency. It discloses the data contents in detail, including time windows (1h/24h, 30-day series) and aggregation across major exchanges. It does not explicitly state read-only behavior or potential rate limits, but the detail provided is sufficient for a clear behavioral model.

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 two sentences with no redundant phrasing. It front-loads the core purpose ('Aggregated crypto futures market snapshot') and then lists the specific data points, earning every word.

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?

Despite having no output schema or annotations, the description fully specifies the tool's output by enumerating all key metrics and timeframes. For a zero-parameter read-only snapshot tool, this is complete and leaves no ambiguity for an agent.

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 has zero parameters, and the input schema contains no properties, meaning the description inherently covers the entire input space. The baseline for zero parameters is 4, and the description adds no irrelevant parameter details, so this score 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 as an aggregated crypto futures market snapshot, enumerating specific metrics such as open interest, liquidations, Fear & Greed index, and average RSI. This specificity distinguishes it from sibling tools like get_coin_summary or get_funding_rates, which are more narrowly focused.

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 use for a broad market-level overview rather than per-coin or per-exchange queries, providing clear context for when to use it. However, it does not explicitly name alternatives or state when not to use it, so it falls short of a 5.

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 behavioral disclosure. It clearly states output compositions for each metric (e.g., 'oi returns open-interest candles (USD)'), and reveals that timestamps are UTC ISO 8601 and results are the newest N points. This adds significant transparency about return format and ordering, though it omits rate limits or error behavior.

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 three sentences: purpose, per-metric returns, and timestamp/order info. Every sentence provides essential information with no fluff. The density in the metric list is acceptable given the number of metrics, and the structure is front-loaded with the core purpose.

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?

There is no output schema, so the description must explain return values, which it does thoroughly for each metric. It also clarifies ordering and timestamp format. However, it does not describe the exact JSON field names (e.g., 'open', 'high', 'low') or clarify whether prices are aggregated across exchanges, which leaves some ambiguity in a no-schema 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?

The schema covers symbol, tf, and limit with descriptions, but metric has no schema description. The description compensates by explaining exactly what each metric enum value returns (e.g., 'funding returns OI-weighted funding-rate candles (% per interval)'). This adds meaningful semantic detail beyond the raw enum list, though tf and limit rely on 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 opens with 'Historical time series for one coin' and then enumerates exactly what each metric returns (OHLC, OI, funding, long/short, liquidation, volume). This is a specific verb + resource + scope, and the detailed metric list clearly distinguishes it from sibling tools like get_funding_rates (which likely handles current rates) and get_market_overview.

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 clear context for when to use the tool: any time historical series for these specific metrics are needed for a single coin. It does not explicitly mention alternatives or exclusions, but the per-metric breakdown implicitly tells the agent which metric to choose. A 5 would require explicit 'instead of X' 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, the description carries the burden of disclosing behavioral traits. It specifies the data fields returned, but does not explicitly state that the operation is read-only or non-destructive (though that is obvious from context). It also does not mention sorting, pagination, or any output format. The listing of metrics adds some transparency, but there are gaps.

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, well-structured sentence that front-loads the main subject ('Top cryptocurrency derivatives exchanges tracked by Coinfuty') and follows with a concise list of relevant data points. Every word earns its place, with no fluff or repetition.

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 simplicity of the tool (no params, no output schema), the description is largely complete: it lists the data fields returned. However, it is ambiguous what 'Top' means (ranking criterion) and does not mention any limits or default sorting. For a list tool, this missing detail slightly reduces completeness but does not severely hamper usability.

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 has zero parameters and the schema coverage is 100%, so the baseline is 4 per the rubric. The description adds no parameter-related meaning because there are none, but it appropriately describes what the tool returns, which is sufficient. There is no need for additional parameter semantics.

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 as providing top cryptocurrency derivatives exchanges with specific metrics (open interest, volume, liquidations, fees, markets, CMC rank). While it lacks an explicit verb like 'list', the tool name 'list_exchanges' and the noun phrase 'Top cryptocurrency derivatives exchanges' make the action unambiguous. It distinguishes itself from siblings by focusing exclusively on derivatives exchanges, which is distinct from coin markets, summaries, and funding rates.

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 usage: it is for retrieving an overview of derivatives exchanges with specific data points. However, it does not explicitly state when to use this tool versus alternatives, nor does it mention any exclusions or prerequisites. Sibling tools like get_exchange_breakdown or get_market_overview could be confused, but the description provides enough context for an experienced agent to infer appropriate use.

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