agentdata-mcp

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

With no annotations, the description carries the full burden. It discloses a $0.005 USDC threshold, suggesting a minimum spread filter, but does not state what the tool returns, whether it's current data, or any operational traits. No safety, authentication, or rate-limit context is given.

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 extremely short (six words) but this is under-specification rather than effective conciseness; it omits the verb and output type. Every word earns its place, but the message is incomplete.

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 no-parameter read tool, the description should clarify what output is produced (e.g., list of arbitrage opportunities vs. raw spreads). It doesn't explain the return payload or how the threshold is applied, leaving the tool under-defined.

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 accepts zero parameters, so the empty schema is complete. The description correctly adds no parameter information, and the baseline for zero-param tools is 4.

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 'Cross-exchange spreads MEXC/Binance/Bybit/OKX ($0.005 USDC)' identifies the resource (spreads across specific exchanges) and a threshold, but lacks a directive verb, making it a phrase rather than a clear statement of action. It does differentiate from siblings by naming exchanges and threshold, but the omission of 'get' or 'list' leaves the operation implied.

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 no explicit guidance on when to use this tool over siblings, nor any exclusions or alternative recommendations. The intended usage is only implied by the tool name and the fragmented description.

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 is the sole source of behavioral info. It discloses the data content but doesn't clarify whether it's a read-only operation, what block activity includes, or what the $0.003 USDC figure means.

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 extremely brief, nearly a label. It is not verbose, but the lack of a full sentence and the ambiguous parenthetical keep it from being perfectly structured.

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 should explain the return format. It only names two metrics without details on units, time range, or response structure. The $0.003 USDC is unexplained, making the description incomplete.

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, so the description need not explain parameter semantics. The baseline of 4 applies as there is nothing to clarify.

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 output: Base network TPS and block activity. This distinguishes it from sibling tools focused on prices, yields, and other market data. However, it lacks an explicit verb and the $0.003 USDC parenthetical is ambiguous.

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 no guidance on when to use this tool versus alternatives. It does not mention scenarios requiring Base network metrics or exclude other 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 available, the description carries the full burden of behavioral disclosure. It mentions the 30-day window and the $0.002 cost, but does not explain the output format, which assets are covered, or whether this is a read-only operation. This leaves key behavioral traits 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 a single, highly efficient phrase conveying the essential function, time period, and cost. Every word earns its place, with no filler or redundancy. This sets a strong example of conciseness.

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 annotations, no output schema, and no parameters, the description must offer complete context. It fails to specify which assets are correlated, the structure of the matrix, or any prerequisites, leaving significant ambiguity for an agent deciding whether to invoke the 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?

The tool has zero parameters, so the baseline of 4 applies. The description correctly adds no parameter explanation, which is appropriate for a parameterless tool. Schema coverage is 100% vacuously, so no gaps exist.

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 a 30-day price correlation matrix, which is a specific, distinct resource compared to sibling tools like get_crypto_prices or get_volatility. The purpose is unambiguous despite lacking an explicit verb.

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?

No guidance is given on when to use this tool versus alternatives. It only states the time horizon and cost, with no mention of scenarios, exclusions, or comparison to related tools like get_correlation.

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 of disclosure. It only hints at 'real-time' but doesn't explicitly state that this is a read-only operation, what the output looks like, or any rate limits or data freshness caveats.

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 short but the parenthetical '($0.002 USDC)' is a confusing distraction that doesn't earn its place and appears factually incorrect. It would be cleaner and more focused without it.

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 no-parameter tool, the description identifies the specific assets, which is useful for selection. However, it doesn't specify the price currency (presumably USD), clarify the odd USDC mention, or reference sibling tools, leaving some ambiguity for an agent deciding between this and similar market 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?

With zero parameters and 100% schema coverage, there is no parameter detail to explain. The description adds context by listing the covered coins, which is helpful, and the baseline for 0-param tools is 4.

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 provides real-time prices for BTC, ETH, SOL, BNB, and XRP, distinguishing it from sibling tools that focus on other market metrics. The parenthetical '($0.002 USDC)' is confusing and possibly erroneous, which slightly dims the clarity.

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?

There is no guidance on when to use this tool versus alternatives like get_market_pulse or get_historical. It doesn't mention any exclusions, prerequisites, or complementary 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?

The description discloses the cost ($0.003 USDC), which is a behavioral trait, but it omits other important behavioral context such as whether the operation is read-only, the return format, or any rate limits. With no annotations provided, the description carries the full burden and falls short.

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 extremely concise and includes key details (yields, protocols, cost), but it is a sentence fragment lacking a verb. It is appropriately short for a zero-parameter tool, but it could be more structured as a complete sentence.

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 is minimal and does not clarify important context such as what 'yields' means (APY/APR), how the data is sourced, or the output structure. Given the absence of an output schema and annotations, the description alone is insufficient for an agent to fully understand the tool's behavior.

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, so the schema provides no parameter details. The description adds context by specifying the protocols and cost, which helps set expectations. With no parameters, the baseline is 4, and the description does not need to explain 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's output as top DeFi yields from specific protocols (Aave, Compound, Morpho, Pendle). While the description lacks an explicit verb, the tool name 'get_defi_yields' and the resource mention make the purpose clear. It distinguishes itself from sibling tools that focus on other market metrics.

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?

No guidance is provided on when to use this tool versus alternative tools. The description simply states what the tool returns without any context on use cases, prerequisites, or mention of alternatives among the sibling 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 disclosing behavior. It only mentions a threshold of $0.005 USDC, but doesn't explain what that means (e.g., minimum spread, fee, tick size). It doesn't disclose return format, whether it shows raw prices or differences, or any side effects. The tool is effectively opaque.

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 very short and front-loaded, but it's under-specified. 'DEX vs CEX price comparison' is too terse to be useful. It includes a parenthetical numeric detail that may be meaningful but is left unexplained. It doesn't waste words, but it omits essential content.

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 and no annotations, the description needs to explain what the tool returns and how the comparison works. It fails to do so. The meaning of $0.005 USDC is ambiguous. For a simple tool it might be acceptable, but it's not complete enough for an agent to confidently call it.

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, so the schema trivially covers all parameters. Description adds minimal context by mentioning $0.005 USDC, which might relate to the comparison threshold, but there is no parameter to clarify. Per rubric, 0 params baseline is 4, and the description doesn't need to explain parameters.

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 is a noun phrase ('DEX vs CEX price comparison') rather than a clear verb+resource statement. It doesn't specify what action the tool performs or what output is produced. It also fails to distinguish from sibling tools like get_arbitrage_opportunities, which likely also deals with DEX/CEX price differences.

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?

There is no guidance on when to use this tool versus alternatives. No mention of context, prerequisites, or exclusions. The sibling tools list includes get_arbitrage_opportunities and get_crypto_prices, but the description gives no hint of when this tool would be preferred over those.

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 burden. It discloses key behavioral details: data content, units, historical range, and cost ($0.005 USDC). It does not describe the response format or any limitations like refresh frequency or access requirements.

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, information-dense sentence that front-loads the core purpose and includes practical details (units, history length, cost). 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?

Given the tool has no parameters and no output schema, the description covers the essential context: what data is returned, units, time range, and cost. It could mention the expected response shape (e.g., a time series) but is fairly complete for a simple data retrieval 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?

There are zero parameters, so the schema provides no information. The description adds useful context about what the tool returns (net flows, USD millions, 30-day history), which is enough for a parameterless tool.

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 specifies the resource (Spot BTC & ETH ETF daily net flows) and the scope (institutional demand, USD millions, latest + 30-day history). It is distinct from sibling tools that cover other data types like funding rates, prices, or sentiment.

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 this tool: when ETF flow data is needed, with clear context on units and time range. However, it does not explicitly mention alternatives or exclusions, so it falls short of full 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 full burden. It discloses the predictive nature, the asset scope, exchange (MEXC), and the cost/fee ($0.003 USDC). However, it does not clarify what 'time to settlement' means, the prediction horizon, or return format. This is adequate but not rich.

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 sentence that is front-loaded with the core purpose ('Predicted next funding rate') and packs relevant details (assets, exchange, time to settlement, cost) without waste. Every token 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 zero-parameter tool with no output schema, the description covers the essential scope (BTC/ETH/SOL, MEXC, predicted rates, settlement time, cost). It lacks explicit return-value details, but given the simplicity, it is largely complete for an agent to invoke and understand the result.

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 schema coverage is 100%, so no parameter explanation is needed. The description goes beyond the schema by specifying the asset list, exchange, and cost, adding value even though no parameters exist.

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 'Predicted next funding rate for BTC/ETH/SOL on MEXC' and includes additional context about time to settlement. It distinguishes itself from the sibling tool get_funding_rates by explicitly saying 'Predicted', making it clear this is the forecast variant.

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 for obtaining predicted funding rates but provides no explicit guidance on when to choose this over get_funding_rates or other tools. The distinction is inferable from the 'Predicted' keyword, but no alternatives or exclusions 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 full responsibility for behavioral disclosure. It mentions a cost ($0.002 USDC) and output signals, which is helpful, but it does not explicitly state that the operation is read-only, nor does it describe any rate limits, data sources, or potential side effects.

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 concise phrase with no redundant words. It front-loads the key information (perpetual funding rates, signals, cost), though it lacks a verb, which slightly reduces its structural completeness.

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 zero-parameter tool with no output schema, the description provides a reasonable overview but omits important context such as the time period covered, data source, or any limitations. It is minimally adequate but leaves room for clarification.

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, so the description is not required to explain parameter details. The baseline of 4 is appropriate because there is nothing to compensate for.

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 perpetual funding rates with long/short signals and pricing. Although it lacks an explicit verb, the tool name 'get_funding_rates' supplies the action, and the description adds specific resource details that distinguish it from siblings like get_funding_predictions.

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?

No guidance is provided on when to use this tool versus alternatives such as get_funding_predictions or get_market_pulse. The description is purely descriptive and does not mention any use cases, prerequisites, or exclusions.

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 disclose behavioral traits, but it only mentions the data scope. It does not clarify whether the tool is read-only, the meaning of the $0.002 USDC, data freshness, or any rate limits. The cost notation adds confusion rather than transparency.

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 sentence with minimal wording, making it highly concise. However, the parenthetical '$0.002 USDC' is potentially extraneous and unclear, preventing a perfect score for zero-waste structure.

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 (no params, no output schema), the description covers the core purpose but leaves ambiguity about the response format and the meaning of $0.002 USDC. It is adequate but has gaps that could be filled without unnecessary length.

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 has zero parameters, so the description has nothing to explain about parameters. According to the scoring guidelines, 0-param tools receive a baseline of 4, and the description adds appropriate value by indicating the tool requires no 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 clearly identifies the tool as providing gas prices for Base, Ethereum, and Solana, which distinguishes it from sibling tools focused on other market metrics. However, the parenthetical '$0.002 USDC' is ambiguous and not clearly explained, slightly detracting from full clarity.

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 offers no explicit guidance on when to use this tool versus alternatives, nor does it mention any prerequisites, exclusions, or context. The implied use case of retrieving gas prices is apparent but not stated as a recommendation.

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 behavioral disclosure burden. It does add the cost ($0.010 USDC) which is a useful behavioral trait, but it omits other important details like read-only nature, response ordering, or rate limits. The cost disclosure is a partial contribution, hence a middle score.

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 extremely concise, using a short fragment that communicates the core function and cost. It avoids fluff, but it is arguably too terse given the lack of annotations and schema descriptions, so it loses a point for under-specification.

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?

Without annotations or an output schema, the description must provide a complete picture, but it does not. It fails to mention return format (e.g., candle structure), parameter semantics, or when to use the tool versus siblings. The cost information is helpful but insufficient for a complex data-fetching 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 0% and the description does not explain any of the three parameters (limit, symbol, interval). The schema provides defaults and an enum for interval, but the meaning of each parameter is left unstated. The description adds no parameter-level value.

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 historical OHLCV candles, which is a specific verb+resource. It distinguishes from sibling tools like get_crypto_prices (current prices) and get_technical_indicators (derived indicators), making the purpose unambiguous.

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?

There is no guidance on when to use this tool versus alternatives. The description does not mention any scenarios, prerequisites, or exclusions, leaving the agent to infer usage from the tool name and context.

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 transparency burden. It notes that the zones are 'estimated' and includes a price reference, but it does not clarify the output format, accuracy, or what '$0.003 USDC' refers to, leaving significant ambiguity.

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 extremely concise with a single fragment, which is efficient in length. However, it is not a complete sentence, which slightly hampers clarity and structure.

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 tool with no parameters and no output schema, the description is too terse. It omits critical context such as the asset, the meaning of the price, and the nature of the liquidation zones, making it incomplete for an agent to understand the tool's output.

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 has zero parameters, so the baseline is 4. The description's mention of leverage levels and a price is a fixed characteristic rather than a parameter, and there is nothing to clarify 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 states the tool provides estimated liquidation zones and specifies leverage levels (5x/10x/20x), but it lacks an explicit verb and does not identify the underlying asset or market. This makes the purpose somewhat ambiguous beyond what the tool name already implies.

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?

There is no guidance on when to use this tool versus the many sibling tools. The description does not mention any context, prerequisites, or exclusions, so the agent must infer usage solely from the tool name.

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 behavioral disclosure burden. It does list the types of data included, but it does not explain the return format, update frequency, or any limitations. The parenthetical '$0.003 USDC' is ambiguous—whether it's a cost, a metric, or something else is unclear.

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 brief and front-loaded with the main topic, but the trailing '($0.003 USDC)' is ambiguous and disrupts the flow. It does not clearly earn its place and could confuse an agent about whether it is a cost indicator or a data field.

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 zero-parameter tool, the description lists the core topics but omits important context such as time ranges, units, or data sources. Without an output schema, this leaves some ambiguity about what exactly is returned and how the data is presented.

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, so there are no parameter semantics to explain. Baseline 4 is appropriate since there is no schema information that the description could enhance.

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 names the resource (macro & on-chain context) and lists specific data points (stablecoin supply, BTC/ETH dominance, etc.), which distinguishes it from sibling tools like get_crypto_prices or get_sentiment. However, it lacks an explicit verb like 'retrieves' or 'returns,' making it a sentence fragment rather than a full statement of purpose.

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?

There is no explicit guidance on when to use this tool versus alternatives such as get_market_overview or get_sentiment. The list of topics implies a use case for macro/on-chain analysis, but no exclusions or comparisons are provided.

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 disclosure. It reveals the content (sentiment and arb signals) and the cost ($0.003 USDC), but does not disclose return format, pagination, rate limits, or permissions. The cost detail is a positive, but overall transparency is limited.

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, concise sentence that front-loads the core purpose and adds a practical cost detail. Every word earns its place, with no filler or redundancy. Ideal for a zero-parameter 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?

The tool has no output schema, so the description must convey what the agent can expect. It mentions sentiment and arbitrage signals, but 'full market overview' is vague and does not enumerate other potential fields (e.g., prices, funding, volatility). The cost detail is useful, but the return content is only partial.

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 trivially 100% with no properties. Baseline for 0 params is 4, and the description correctly does not need to add parameter explanations. No gaps exist.

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 provides a 'full market overview' with sentiment and arbitrage signals, distinguishing it from more focused sibling tools like get_sentiment or get_arbitrage_opportunities. The verb 'get' is in the name, and the description specifies the resource and scope, making the purpose evident.

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 no explicit guidance on when to use this tool versus alternatives. It implies a broad 'full market overview' use case, but does not mention exclusions, prerequisites, or relationships to sibling tools. The cost mention ($0.003 USDC) hints at a paid call but does not provide direction.

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 behavioral disclosure burden. It adds transparency about the payment requirement (one payment vs. eight settlements) and confirms the return includes eight specified signal types. However, it does not disclose the response format, rate limits, or other operational behaviors. The cost information is genuinely useful context beyond the structured data.

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 concise at two sentences, but the first sentence is somewhat dense with a price point and an eight-item list. The second sentence provides a clear cost comparison. Both sentences contribute meaningfully, but the flow could be slightly improved by front-loading the functional aspect before the pricing details.

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 has no parameters and no output schema, the description is fairly complete for a bundle tool. It lists all eight included signals, which provides sufficient clarity about the product's coverage. However, it does not describe the shape or structure of the returned data, though the sibling tools likely offer that context. The pricing focus is relevant but somewhat unusual for an API tool description.

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, so per the rubric baseline is 4. The description appropriately focuses on the bundle contents and pricing, and there is no parameter information needed. The schema is empty, so the description does not need to elaborate on any 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 states that this tool provides a bundle of 8 market signals in a single call, listing them explicitly ('sentiment, liquidation levels, volatility, correlation, funding predictions, positioning, supply, stablecoin health'). This distinguishes it from individual signal tools like get_sentiment or get_volatility, though the verb is implicit rather than explicit. The tool name 'get_market_pulse' reinforces the purpose.

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 by comparing the bundled cost ($0.018) to the cost of buying signals separately ($0.022 and eight settlements), suggesting this tool is cost-effective when you need all eight signals. However, it does not explicitly state when to use this versus individual tools, nor does it provide guidance on scenarios where individual tools might be preferable (e.g., needing only one signal).

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. It discloses a notable behavior: a cost of $0.005 USDC, and specifies the exchanges covered. However, it does not mention whether data is real-time, historical, or the response structure. It is transparent but not exhaustive.

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 core purpose and includes valuable specifics (metrics, exchanges, cost). 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?

For a no-parameter, read-only data tool, the description is quite complete. It lists the key data elements and exchanges, and even notes the fee. It lacks details on timeframes or format, but the complexity is low and the schema provides no further clues.

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, so the baseline is 4. The description adds meaning by detailing what data is included, effectively explaining the tool's scope beyond the empty 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 what the tool retrieves: trader positioning data including open interest, long/short ratios (global and top traders), and funding. It also names specific exchanges (Binance, CoinEx), distinguishing it from siblings like get_funding_rates which likely covers only 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 when to use the tool by listing its specific data scope, but it does not explicitly compare it to alternatives or state when not to use it. Users can infer it is for positioning metrics, but there is no direct guidance on selecting among siblings like get_funding_rates or get_arbitrage_opportunities.

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. It discloses a per-call cost of $0.002 USDC, which is useful behavioral information. However, it does not mention read-only semantics, return format, or any limitations, so transparency is partial.

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, front-loaded fragment with zero filler: it names the resource and includes a cost note. It is appropriately sized for a zero-parameter 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?

For a simple zero-param data tool with no output schema, the description provides the semantic content (Fear & Greed and sentiment) but not the return structure. It is minimally complete but lacks context on how this compares to 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 tool has zero parameters, so schema coverage is 100% by construction. The baseline for 0 params is 4, and the description correctly omits parameter details.

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 'Fear & Greed + composite sentiment' clearly identifies what the tool provides, and the tool name 'get_sentiment' reinforces the retrieval action. It distinguishes from siblings by naming specific sentiment metrics, though it lacks an explicit verb in 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?

No guidance is given on when to use this tool versus alternatives like get_market_pulse or get_positioning. The description provides no context for selection or exclusions, leaving the agent to guess.

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 and discloses important behavioral traits: hourly granularity, a 7-day retention window, a cost of $0.005 USDC, and the irreplaceable nature of the data. It does not mention response format or error handling, but the disclosed traits go beyond a minimal description.

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 concise and front-loaded, with the core purpose stated first. The parenthetical cost and the two-sentence caveat about reconstruction add value without redundancy. Every word serves a 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?

Given the tool's low complexity (one parameter, no output schema, no annotations), the description covers essential context: what data is returned, its granularity, duration, cost, and why it is valuable. It could hint at the response structure, but 'hourly history' is reasonably informative, so a 4 is warranted.

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 provides full coverage for the single 'signal' parameter, including a description and examples (sentiment, volatility, funding-rates). The tool description adds no additional parameter-specific context, 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 purpose: it retrieves recorded hourly history for a derived signal over the most recent 7 days. The phrase 'derived signal' and the 7-day window distinguish it from sibling tools like get_historical or get_sentiment, making its specific role clear.

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 this tool by stating the data 'cannot be reconstructed from public sources after the fact,' which signals that this is the only way to obtain this historical signal data. However, it does not explicitly mention alternatives or when not to use it, so it falls just 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 only mentions '$0.002 USDC' as a cryptic threshold without explaining its meaning, return format, or how depeg is assessed. This is insufficient for a monitoring 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 short phrase with no wasted words. It is concise and front-loaded, but its extreme brevity omits important context. It earns a high score for not being verbose, though it could be more 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?

The description lacks details about return values, how to interpret 'health', and the significance of '$0.002 USDC'. For a monitoring tool with no output schema, this is inadequate for an agent to understand what to expect or how to act on the result.

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, so the description does not need to explain any. Schema coverage is 100% vacuously, and the baseline for 0 parameters is 4. The description adds no parameter-specific semantics because there are none.

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 monitoring USDC/DAI depeg, which distinguishes it from sibling tools like get_crypto_prices or get_volatility. The verb 'monitoring' is implicit rather than explicit, but the resource and function are clear. It is not a tautology and conveys specific purpose.

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?

No guidance is provided on when to use this tool versus alternatives. The description does not mention scenarios, prerequisites, or exclusions, leaving the agent without direction for choosing this over sibling 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?

No annotations are provided, so the description carries the burden. It adds useful context like the $0.003 USDC cost and the 'per major coin' scope, but does not disclose output format, freshness, or any potential side effects. Since it is a read-only data tool, the lack of additional behavioral notes is acceptable but not comprehensive.

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, information-dense sentence. It includes the specific metrics, the scope ('per major coin'), the application ('structural sell-pressure signal'), and even the cost, all without redundancy or fluff.

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 tool with no parameters and no output schema, the description is largely complete: it tells what data to expect and why it might be used. The only minor gap is the ambiguity of 'major coin' (which coins exactly?), but this is acceptable for a quick-reference 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?

With zero parameters, the schema provides no parameter details. The description compensates by explaining exactly what data is returned (supply metrics and overhang ratio), which fulfills the baseline expectation for a parameterless tool and adds meaning beyond the empty 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 provides circulating, total, and max supply along with overhang ratio per major coin, using a specific verb ('get' is implied) and defining the resource. It distinguishes itself from sibling tools by focusing exclusively on supply metrics and the structural sell-pressure signal, even noting a cost.

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 use case is implied through 'structural sell-pressure signal,' which suggests when an investor might want supply data. However, there is no explicit mention of when not to use this tool or which alternative tools to prefer for other types of market data, especially given the large sibling list.

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 a cost hint '($0.005 USDC)' and the method 'fractal analysis', but does not explain what the function returns, whether it's current/historical, or any limitations. The cost hint is ambiguous (is it a fee per call?).

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 extremely concise, with no fluff, but it is under-specified to the point of cryptic. All words are relevant, yet the structure does not provide enough context, and the parenthetical is ambiguous.

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 annotations, no output schema, and minimal description, this is incomplete for a tool that likely returns a set of price levels. It lacks explanation of output format, parameter meaning, and potential cost implications, making it hard for an agent to use 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 0%. The description does not mention the 'symbol' parameter or its default value, leaving the agent to guess that the tool likely expects a trading pair. No added meaning beyond the schema's bare existence.

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 it computes support/resistance (S/R) levels via fractal analysis, which is a specific verb+resource. However, it doesn't differentiate from closely related siblings like get_technical_indicators or get_liquidation_levels, and the abbreviation 'S/R' may be ambiguous.

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?

No explicit guidance is given on when to use this tool vs alternatives. The phrase 'S/R levels' implies a use case, but there is no mention of exclusions, prerequisites, or sibling alternatives, leaving the agent to infer eligibility.

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?

The description discloses the cost per call ($0.003 USDC), which is a useful behavioral trait not present in annotations (since there are none). However, it omits other behavioral details such as data source, update frequency, latency, or any side effects. Given no annotations, the description carries the transparency burden but only partially fulfills it.

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 extremely concise, using a single short string to list indicators and cost. Every word is functional, with no filler. However, it lacks structure (e.g., a sentence explaining purpose) and reads more like a shorthand note than a structured description, yet it is efficient and front-loaded.

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 and lack of an output schema, the description is under-specified. It does not explain the return format, how to use the parameters, or the data source. For an agent to invoke it correctly, it needs to know that symbol and interval are configurable and what the response contains. The description leaves critical gaps for a tool with no annotations or output schema.

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 does not mention the parameters symbol or interval. With schema description coverage at 0%, the description adds no meaning beyond what the schema itself provides. While the parameter names and enum/default values are self-explanatory, the description should still clarify their roles or formats to aid correct invocation.

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 lists the specific technical indicators (RSI, MACD, Bollinger Bands, ATR), making it clear this tool returns technical indicator data. The name 'get_technical_indicators' reinforces this. However, it does not explicitly distinguish from closely related sibling tools like get_volatility or get_support_resistance, which may rely on similar indicators.

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 no guidance on when to use this tool versus alternatives. It only lists indicators and a cost, with no mention of use cases, prerequisites, or comparisons to sibling tools. This leaves the agent without clear direction for tool selection.

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 of explaining behavior. The description only states the metric and asset list, but does not disclose the nature of the return value (e.g., a single percentage, a series), data update frequency, or any limitations. The parenthetical '$0.002 USDC' is cryptic—likely a cost per call, but it is not explicitly stated as a fee, causing confusion rather than transparency.

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, front-loaded sentence that conveys the core purpose efficiently. However, the parenthetical '$0.002 USDC' is ambiguous and does not earn its place without explanation, slightly detracting from overall conciseness by adding potential confusion.

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 that there is no output schema, the description should explain what the returned volatility data looks like (e.g., percentage, annualized, historical points). It does not. The cryptic cost reference and lack of detail about the data source or interpretation make the description incomplete for a tool that has no other documentation.

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?

With zero parameters, the baseline is 4. The description adds meaning by explicitly naming the assets (BTC/ETH/SOL) and time window (24h), which would otherwise be entirely unspecified. There are no parameter details to clarify, so the description adequately covers the semantic scope.

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 provides 24h volatility for a specific set of assets (BTC/ETH/SOL). This is a specific verb ('get volatility') with a clear resource scope, distinguishing it from sibling tools like get_funding_rates or get_correlation. The purpose is immediately understandable.

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 when one needs volatility data for the specified assets, but it does not explicitly state when to use this tool over alternatives or provide exclusions. For example, it doesn't mention that this is a quick snapshot versus more detailed volatility metrics available elsewhere. Guidance is minimal and relies on inference from the name and context.

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