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

No annotations provided, so description must carry behavioral info. It only says 'measures money flow' but doesn't disclose whether it's lagging, how it's calculated, or any limitations. Response format is not described despite output schema existence.

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?

A single sentence is concise, but it omits critical information. Front-loading is good, but the sentence lacks substance for a tool with 3 parameters and no schema descriptions.

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 3 parameters, no schema descriptions, no annotations, and an output schema not explained, the description is insufficient. It does not cover required usage details or output interpretation.

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 has 0% description coverage, and the description does not mention any parameters. Users get no insight into symbol, interval, or limit meanings, defaults, or allowed values.

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?

Description clearly states it's the Accumulation/Distribution Line and measures money flow. However, it doesn't distinguish from sibling tools like get_adosc (which is the oscillator version) or explain what it returns (line values).

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

No guidance on when to use this tool vs alternatives like get_obv or get_mfi. No context about best use cases, 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?

No annotations exist, so the description carries the full burden of transparency. It fails to disclose any behavioral traits such as data source, rate limits, or how the momentum is calculated (e.g., formula, default periods). The minimal description is insufficient for an agent to understand the tool's 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 a single sentence, which is efficient, but it is too terse for a tool with 5 parameters and no schema descriptions. It front-loads the indicator name but omits critical details, making it under-specified rather than appropriately concise.

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 complexity of a technical indicator with 5 parameters and an output schema (unseen), the description is extremely incomplete. It provides no information on output structure, parameter ranges, or how this indicator differs from siblings, leaving the agent with inadequate context to use the tool correctly.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The input schema has 5 parameters with zero description coverage, and the tool description adds no semantic information about any parameter. The agent has no explanation of what 'fast', 'slow', 'limit', 'symbol', or 'interval' mean in context of the A/D Oscillator.

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 the Chaikin A/D Oscillator, a specific technical indicator measuring momentum of the Accumulation/Distribution line. This is a precise verb-resource pair. However, it does not distinguish this oscillator from other similar oscillators among sibling tools (e.g., get_apo, get_ultosc).

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 the many sibling indicators (e.g., get_ad, get_macd). The description only names the indicator without any context of market conditions or analysis scenarios where this oscillator is preferred.

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 ADX interpretation scale (0-100) and indicates the tool returns ADX values with trend strength interpretation. However, it does not specify data retrieval methods or side effects, though for a computation tool this is adequate.

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 well-structured with separate sections for purpose, interpretation, parameters, and returns. It is relatively concise, though the parameter list could be slightly more compact without losing clarity.

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 existence of an output schema (context signal), the description sufficiently explains the return value concept (ADX values with trend interpretation). All six parameters are covered with examples, and the tool's behavior is adequately explained for its complexity.

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 0% description coverage, but the tool description includes a detailed 'Args' section explaining each parameter, including examples and defaults (e.g., 'symbol: Trading pair symbol (e.g., BTCUSDT, ETHUSDT)'). This fully compensates for the missing 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 clearly states 'Get ADX (Average Directional Index) for a cryptocurrency,' using a specific verb and resource. It explains what ADX is and its interpretation, distinguishing it from sibling tools like get_dx or get_plus_di, which focus on direction.

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 mentions that ADX measures trend strength (not direction), but does not explicitly state when to use this tool versus alternatives like get_dx, get_plus_di, or other trend indicators. No exclusions or comparative guidance is 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?

The description lacks behavioral details beyond 'smoothed ADX', but the tool is a read-only data retrieval with an output schema, reducing the need for extensive transparency. No annotations are present, so the description carries the burden, but the one-line definition is insufficient for safety or rate limit context.

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 (one sentence) but lacks essential details. While it is front-loaded with the full indicator name, the brevity undermines clarity and completeness, making it minimally acceptable.

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 (4 parameters, no parameter descriptions, and many similar siblings), the description is incomplete. It fails to provide parameter context, usage guidance, or differentiation, leaving the agent underinformed despite the presence of an 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?

Schema description coverage is 0%, and the description does not explain any parameter (limit, period, symbol, interval) in the context of ADXR. The parameter names provide minimal hints, but the description adds no semantic value, making it hard to invoke correctly.

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 returns the Average Directional Movement Index Rating, a smoothed version of ADX. It clearly identifies the resource and action (get) but does not explicitly distinguish it from similar siblings like get_adx or get_dx, relying on the name 'adxr' for differentiation.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

No guidance is provided on when to use this tool versus alternatives such as get_adx or other indicators. There are no context clues, exclusions, or prerequisites, leaving the agent to infer usage from the name alone.

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 fails to mention any effects, data sources, or return characteristics beyond a brief definition.

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 line, but it is under-specified rather than concise. It lacks structure and important details, sacrificing completeness for brevity.

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 5 parameters and no parameter documentation, the description is extremely incomplete. It does not explain output, interpretation, or any special behavior, making it nearly unusable without external knowledge.

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 0% description coverage, meaning no parameter is explained. The description does not add any meaning to parameters like fast, slow, or interval, leaving the agent to infer usage.

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 defines the Absolute Price Oscillator but does not explicitly state that the tool calculates or returns its values. The verb 'get' in the name implies retrieval, but the description lacks an action verb, making it slightly vague.

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 its 48 sibling tools, such as get_ppo or get_macd. The agent receives no context for 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, and the description does not disclose behavioral details such as return format, required permissions, or any side effects. It only gives a brief interpretation of the indicator.

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 but it is too brief to be fully informative. It is not verbose, but it sacrifices completeness for brevity.

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 4 parameters and no annotations, the description provides minimal context. The presence of an output schema is noted but not referenced. The description is insufficient for adequate agent understanding.

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 provide any explanation of the parameters (symbol, interval, limit, period). The agent must rely solely on the schema, which lacks 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 clearly states that the tool identifies trend and trend strength using the Aroon indicator, and gives a condition for bullishness. However, it does not explicitly differentiate it from sibling 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?

No guidance is provided on when to use this tool vs alternative indicators. The description only explains what the tool does without 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 full burden. It only defines the oscillator value but omits behavioral details like data sources, calculation method, error handling, or performance considerations. Limited transparency for a technical indicator.

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?

Extremely concise at two short sentences with no unnecessary verbiage. However, conciseness trades off completeness; the description could include more utility without losing brevity.

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 four parameters with zero schema descriptions, no annotations, and an output schema, the description is too sparse. It covers the core purpose but leaves the agent uninformed about parameter roles, usage context, and return structure.

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%, so description must explain parameters. It does not mention any of the four parameters (symbol, limit, period, interval) or their meaning. The mention of 'AroonUp' and 'AroonDown' hints at period dependency but provides no concrete guidance.

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 returning the Aroon Oscillator, defined as the difference between AroonUp and AroonDown with a bullish indication when >0. It names the specific indicator but does not distinguish it from sibling tools like get_aroon or get_oscillator-based 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?

No guidance on when to use this tool versus alternatives (e.g., other oscillators). No context about market conditions, timeframes, or comparisons to sibling tools like get_apo or get_ppo.

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 burden. It explains the tool retrieves ATR values and interprets volatility, but doesn't disclose data sourcing, rate limits, or any side effects. This is adequate 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 concise with a clear summary, followed by parameter explanations and return value. It is well-structured and front-loaded, with no unnecessary information.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a technical indicator tool with six parameters and an output schema, the description covers purpose, parameter semantics, and usage context. The output schema handles return format, so no further detail is needed.

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%, so the description compensates fully. It lists all parameters with example values and formats (e.g., 'BTCUSDT' for symbol, '1m, 5m...' for interval, default 14 for period), adding significant meaning beyond the schema.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states 'Get ATR (Average True Range) for a cryptocurrency' with a specific verb and resource. It explains that ATR measures volatility and differentiates it from sibling indicators like get_sma or get_rsi by focusing on volatility.

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 notes ATR is 'useful for setting stop-losses and position sizing,' providing context. However, it doesn't explicitly state when not to use this tool versus alternatives, leaving some ambiguity among many siblings.

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 value by explaining the return interpretation (%B), but does not disclose whether the operation is read-only, any side effects, data freshness, or rate limits. Partial disclosure.

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 front-loaded with purpose and a helpful interpretation guide. It is structured with Args and Returns sections, but the interpretation explanation could be slightly more concise. Still, it 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?

An output schema exists, so return value details are not required in the description. The description covers purpose, parameter usage, and interpretation, which is sufficient for a technical indicator tool with 7 parameters. Missing usage guidelines slightly reduce completeness.

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 has 0% coverage (no descriptions on properties), but the description provides detailed explanations for all 7 parameters, including examples, defaults, and formats (e.g., ISO time, interval units). This fully compensates for the schema's lack of 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 clearly states it retrieves Bollinger Bands for a cryptocurrency, explains the indicator's purpose (volatility and reversal points), and distinguishes from sibling tools like get_sma and get_ema by focusing on the specific indicator.

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?

Usage is implied through the description of Bollinger Bands and %B interpretation, but there is no explicit guidance on when to use this tool over alternatives, when not to use it, or any prerequisites.

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 exist, so description carries full burden. It discloses the output range (-1 to +1) but lacks details on whether it uses volume, is lagging, or requires specific intervals. Behavioral traits beyond the range are omitted.

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 (one sentence), which is concise but incomplete. It lacks structure and does not earn its place as it omits critical information about parameters and usage.

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?

Even though an output schema exists, the description is insufficient for a 3-parameter tool. It misses parameter semantics, usage context, and detailed behavior, making it incomplete for effective agent use.

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 (symbol, limit, interval). It adds no meaning beyond the raw schema, failing to compensate for the lack of 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?

Clearly states the tool computes Balance of Power, measuring buying vs selling pressure, with a range of -1 to +1. However, it does not differentiate from sibling tools like get_obv or get_mfi, which also measure market pressure.

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 on when to use this tool versus alternatives like get_obv or get_mfi. The description implies its use for balance of power analysis but provides no context for 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 full burden for behavioral disclosure. The description only lists parameters and return fields, but does not indicate whether the tool is read-only, requires authentication, has rate limits, or any side effects. This is a significant gap for a data retrieval 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 well-structured with 'Args' and 'Returns' sections, making it easy to scan. The purpose statement is front-loaded. While it could be slightly more concise, it is clear and effective.

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 5 parameters (1 required) and an output schema exists (though not shown). The description covers all parameters and returns, but lacks usage guidance and behavioral context. It is adequate for a simple data retrieval tool but not fully complete.

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%, so the description must compensate. It adds meaning by explaining each parameter with examples (e.g., 'symbol: Trading pair symbol (e.g., BTCUSDT, ETHUSDT)'), enumerating intervals, and specifying limit range/default. This adds significant value beyond the bare 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's purpose: 'Get OHLCV candlestick data for a cryptocurrency.' The verb 'Get' and resource 'OHLCV candlestick data' are specific and unambiguous. It distinguishes well from sibling tools, which are mostly technical indicators (e.g., get_sma, get_rsi) rather than raw price data.

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 specify when not to use it or mention any preconditions. Given the many sibling tools, explicit guidance would be valuable but is absent.

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 bears full responsibility for behavioral disclosure. It shares typical CCI threshold levels but omits any details about data source, computation method, or operational constraints like rate limits or data freshness.

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 two-sentence description is concise and front-loaded with the tool's identity. However, it sacrifices necessary detail for brevity, missing parameter explanations.

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 4-parameter tool with zero parameter documentation and an output schema whose contents are unknown, the description is severely incomplete. It does not cover return values, parameter roles, or any usage context.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema coverage is 0%, and the description provides no explanation for any of the four parameters (symbol, limit, period, interval). It entirely fails to add meaning beyond the raw schema structure.

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 the Commodity Channel Index, states it measures price deviation, and provides concrete thresholds for overbought (>100) and oversold (<-100) conditions, making it distinctive from sibling 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?

No guidance on when to use CCI versus alternatives like RSI or Stochastic, nor any exclusions or prerequisites. The description only hints at overbought/oversold detection without explicit usage 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?

With no annotations, the description carries full burden for behavioral disclosure. It only mentions the oscillation range, omitting details like data requirements, calculation behavior, or side effects. This is insufficient for safe invocation.

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 at one sentence, but it sacrifices meaningful content. It could include key parameter explanations or usage tips without losing brevity.

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 an output schema, the description fails to explain the return format or what the tool produces. With 4 undocumented parameters and no behavioral notes, the tool definition is severely incomplete 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 coverage is 0%, and the description does not explain any of the four parameters (symbol, limit, period, interval). The agent receives no context on how these inputs affect the CMO calculation.

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 identifies the Chande Momentum Oscillator and notes its range (-100 to +100), indicating it is a momentum indicator. However, it does not explicitly state that the tool returns CMO values or calculates them, and it does not differentiate from sibling oscillators like RSI or stochastic.

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 the many sibling tools (e.g., other momentum oscillators). The description lacks any context for selection or exclusion.

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 must disclose behavioral traits. It only states the functional effect (reduces lag) but omits details such as data source, calculation specifics, or any limitations. For a technical indicator tool, this minimal disclosure is insufficient for an agent to anticipate 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 very concise (one sentence) but at the expense of completeness. While it front-loads the core purpose, it omits necessary details about parameters and usage. Every sentence should earn its place; here, the single sentence does not fully inform.

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 an output schema present, return value documentation is not required. However, the description lacks context for 4 parameters and does not guide usage or disclose behavioral traits. Given the complexity of technical indicators, this description is incomplete for an agent to correctly select and 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?

Schema description coverage is 0%, meaning the description is the sole source for parameter meaning. However, the description says nothing about 'symbol', 'period', 'interval', or 'limit'. For example, 'period' is a critical parameter for moving averages but is not explained. This adds no value beyond the schema.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly identifies the tool as a Double Exponential Moving Average and distinguishes it from EMA by stating it reduces lag. The verb 'get' and resource 'DEMA' are explicit, and the function is differentiated from sibling tools like get_ema and get_tema.

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 on when to use this tool versus alternatives like get_ema or get_tema. The description implies it is for reducing lag, but does not state when this is beneficial or what trade-offs exist. No exclusions or prerequisites 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?

No annotations are present, so the description carries the full burden. The one-line description fails to disclose any behavioral traits beyond the basic function. There is no mention of authentication, rate limits, what the tool consumes or modifies, or any 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 extremely concise at one sentence, but it sacrifices meaningful content. While it is short, it lacks structure and fails to include critical information. True conciseness would pack more value into the limited space.

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 (4 parameters, many siblings, an output schema), the description is incomplete. It does not explain the mathematical concept of DX, how to interpret values, or common use cases. The existence of an output schema does not excuse the lack of usage context.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 0%, meaning the schema provides no parameter descriptions. The description does not explain any of the 4 parameters (symbol, limit, period, interval). The agent must infer their meaning from names alone, which is insufficient for correct usage.

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 measures trend strength via the Directional Movement Index, which is clear. However, it does not differentiate this tool from similar siblings like get_adx, which also relates to DMI. The brief description is insufficient for distinguishing among many technical indicator 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?

No guidance is provided on when to use this tool versus alternatives. With over 50 sibling tools, explicit usage recommendations or exclusions are essential. The description lacks any context about its relation to other indicators or appropriate scenarios.

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 full burden. It explains the tool is read-only and lists event categories but omits potential limitations such as maximum days, data source, or update frequency.

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 well-structured with a header, bullet points for events, and an Args/Returns section. Every sentence provides necessary information 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 no annotations and low schema coverage, the description explains purpose, parameters, and output adequately. However, it could be more complete by mentioning any constraints on the 'days' parameter or data range.

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 0% schema coverage, the description adds value by explaining both parameters: 'days' as lookahead period and 'event_type' as optional filter. It gives examples (FOMC, CPI, NFP) but does not enumerate all valid values.

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 retrieves 'upcoming high-impact economic events' and lists specific types like FOMC, CPI, NFP. This distinguishes it from sibling tools that focus on technical indicators or news.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description does not provide guidance on when to use this tool versus alternatives. It mentions event types but lacks explicit comparison with sibling tools like get_next_events or any criteria for exclusion.

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 should disclose behavioral traits like data retrieval impact, rate limits, or permissions. It does not, leaving the agent without safety or performance context.

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 concise at one sentence, but it omits essential details. It is front-loaded but insufficient, balancing conciseness against 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?

Given the 4 parameters, 0% schema coverage, and no output schema details, the description is far from complete. It does not explain return format, data sources, or how to interpret the EMA values.

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%, yet the description adds no explanation for parameters (symbol, period, limit, interval). The agent receives no guidance on what values each parameter expects or their effect.

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 calculates the Exponential Moving Average, emphasizing it gives more weight to recent prices and is faster than SMA. This effectively communicates the core function and differentiates from sibling tool get_sma.

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 on when to use EMA vs other indicators like SMA or DEMA. The description only mentions faster response than SMA, but does not provide criteria for selection or contextual usage scenarios.

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 burden. It details the index classification and ranges, including typical investor sayings. It does not mention side effects, auth, or rate limits, but for a simple read-only data retrieval, the behavioral context is adequate.

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 well-structured with a clear summary, bullet points for ranges, and a returns section. The inclusion of quotes adds flavor but slightly reduces conciseness. Overall 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 (no input parameters) and the presence of an output schema, the description covers purpose, usage context, and return classification. It is complete for an agent to understand and use 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 and schema coverage is 100%. The description adds no parameter information because none is needed. Baseline 3 applies.

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 retrieves the Crypto Fear & Greed Index and measures market sentiment. The verb 'Get' and resource 'Fear & Greed Index' are specific, and the tool is distinct from sibling technical indicators and other sentiment 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?

Description provides context for use ('timing entries/exits') and explains the index range and interpretation. However, it does not contrast with sibling tools that also measure sentiment (e.g., get_long_short_ratio), so no explicit when-not 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 full burden. It discloses that the tool returns current funding rates and explains the meaning of positive/negative rates. However, it does not mention rate limits, data freshness, or any potential side effects, which is adequate but not thorough.

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 fairly concise with a clear first sentence. The explanatory paragraph adds useful context but could be shortened. Overall, it is well-structured 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 has only one optional parameter and an output schema, the description adequately explains what is returned (current funding rates) and how to interpret them. Nothing critical is missing for basic usage.

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 0% coverage, meaning no parameter descriptions. The description adds valuable semantics: it specifies that 'symbols' is a comma-separated list of trading pairs with an example, which goes beyond the schema's empty description.

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 'Get funding rates from Binance Futures', specifying the verb 'Get', the resource 'funding rates', and the source. It distinguishes itself from many sibling tools which are technical indicators or other data types.

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 for when to use this tool by explaining what funding rates indicate about sentiment and potential reversals. However, it does not explicitly compare to alternatives or state when not to use it, though the context is sufficient for most agents.

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 describes the return type as OHLCV data but does not disclose any behavioral traits such as rate limits, data freshness, or side effects. It is adequate but not detailed.

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 well-structured: a clear title line, supported symbols, args list, and return value. Every sentence adds value with no 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?

Given the tool's simplicity and the presence of an output schema, the description adequately covers the purpose, parameters, and return type. However, it does not mention potential errors or prerequisites.

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 has no descriptions (0% coverage), so the description adds meaning by listing allowed values for symbol (US30, SPX, NASDAQ) and providing examples for interval and range. This goes beyond the schema types and defaults.

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 gets OHLCV candles for a stock index and lists supported symbols. However, it does not explicitly differentiate from the sibling tool 'get_candles', which likely serves a similar purpose for individual stocks.

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 lists supported symbols and parameter examples, implying usage context. It does not explicitly state when to use this tool versus alternatives, nor does it provide exclusions or prerequisites.

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 explicitly states the tool returns 'current index price with daily change percentage', which is transparent. It does not mention potential edge cases like data freshness or error handling, but for a simple read operation it is sufficient.

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 yet complete. It includes a one-line summary, usage context, a formatted list of symbols with mappings, and structured Args/Returns sections. No word is wasted.

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 (one parameter, output schema exists), the description is fully complete. It covers what the tool does, when to use it, valid inputs, and what is returned. No gaps remain.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The input schema has one required parameter 'symbol' with 0% description coverage. The description compensates thoroughly by listing valid symbols, their alternate names, and the market each represents. This provides essential meaning that the schema alone lacks.

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 purpose: 'Get current quote for a stock index'. It lists specific supported symbols (US30, SPX, NASDAQ) and distinguishes itself from siblings like get_price (crypto) and get_index_candles (candles).

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: 'Use this to check traditional market conditions... BTC often correlates with US stock indices.' It suggests when to use this tool versus crypto-specific tools. However, it could explicitly state when not to use it (e.g., for crypto quotes).

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 only states the indicator name and its adaptive property. It does not mention that the tool returns time series data, requires price history, or any rate limits or 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 short sentence, which is concise but lacks structure such as separating purpose from usage or parameter details. It is front-loaded but insufficient.

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?

Although an output schema exists, the description does not clarify that the tool returns calculated KAMA values for a given symbol and interval. Missing context on what the tool produces and how it relates to other moving averages.

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 0% description coverage and the description adds no parameter information. Parameters like symbol, period, limit, and interval are not explained in context of KAMA.

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 identifies the tool as returning the Kaufman Adaptive Moving Average, a specific indicator. However, it does not differentiate from sibling tools like get_sma, get_ema, or get_dema, which are also moving averages.

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 KAMA versus other technical indicators. The description lacks context for appropriate use cases.

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 provided. The description discloses that it shows percentage of accounts long vs short and how to interpret ratio values. However, it does not mention data source, update frequency, or whether it requires specific permissions. Adds some value 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 well-structured with a summary, interpretation notes, args, and returns sections. It is concise but not overly terse. Could be slightly shorter without losing clarity.

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 single-parameter tool with an output schema, the description covers purpose, parameter meaning, and how to interpret results. Missing aspects like data source or typical use scenarios are minor given the tool's simplicity.

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 only parameter 'symbol' is described with 'Trading pair symbol (e.g., BTCUSDT, ETHUSDT)', which adds meaning beyond the schema's type string and title. Given 0% schema description coverage, the description compensates well.

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: getting the long/short account ratio for a futures symbol. The verb 'get' and specific resource 'long/short account ratio' make it unambiguous. Among many indicator tools in siblings, this is distinct for sentiment analysis.

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 sentiment analysis and mentions contrarian signals from extreme ratios, but does not explicitly state when to use this tool versus alternatives like get_top_trader_ratio or get_funding_rates. No exclusions or context on when not to use it.

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

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

No annotations are provided, so the description must cover behavioral traits. It describes MACD calculation and output interpretation but omits side effects, error handling, or access requirements. As a read-only indicator tool, it implicitly suggests safety, but lacks explicit disclosure.

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 well-structured with sections for interpretation, arguments, and returns. It is informative but could be slightly more concise, especially the interpretation section which is helpful but somewhat lengthy.

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 8 parameters, one required, and an output schema present, the description covers all aspects: parameter descriptions, defaults, allowed values, and output interpretation. It is complete for an agent to understand usage without external resources.

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 provides detailed explanations for all 8 parameters, including defaults (e.g., fast=12, slow=26), allowed values (e.g., interval options), and format examples (e.g., ISO dates for start_time). Since the schema has 0% description coverage, the description fully compensates.

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 retrieves MACD for a cryptocurrency and explains what MACD indicates. However, it does not explicitly differentiate from sibling indicators like get_rsi or get_sma, which also analyze price trends.

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 interpretation of MACD signals but lacks explicit guidance on when to use MACD over other indicators or when not to use it. 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?

No annotations are provided, so the description must disclose behavioral traits. It only mentions thresholds, lacking details on data source, computation assumptions, or return characteristics.

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, front-loading the indicator's identity and key thresholds. It could be expanded slightly for clarity without losing efficiency.

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 0% schema coverage and 4 parameters, the description is too sparse. While output schema exists, the tool would benefit from explaining parameter roles and usage context.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 0%. The description does not explain any of the 4 parameters (like period meaning or interval options), leaving the agent to rely solely on parameter names.

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 computes Money Flow Index, a volume-weighted RSI, and provides overbought (>80) and oversold (<20) thresholds, distinguishing it from other indicators like RSI or stochastic.

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 volume-weighted momentum analysis with overbought/oversold levels, but does not explicitly state when to prefer this over siblings like RSI or volume-based 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, and the description fails to mention behavioral traits such as required parameters (symbol is required), output format, or any constraints like rate limits or data availability. The tool has an output schema, but the description adds no functional context.

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 no extraneous text, achieving conciseness. However, it is too brief for a tool with multiple parameters and an output schema, sacrificing necessary detail.

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 4 parameters and an output schema, the description is severely incomplete. It does not explain the indicator's inputs, how parameters affect it, or what the output represents. The tool's complexity demands more context.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 0%, meaning parameters have no descriptions. The description does not explain what 'limit', 'period', 'symbol', or 'interval' mean or how they affect the indicator calculation. This leaves the agent with no guidance on parameter usage.

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 is the Minus Directional Indicator and measures downward trend strength, which is a specific and relevant purpose. It differentiates from siblings like get_plus_di by focusing on downward direction, but does not explicitly compare.

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 on when to use this indicator over alternatives like get_plus_di, get_adx, or other trend strength tools. The description implies usage for downward trend measurement but lacks context 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?

With no annotations, the description carries the full burden. It reveals that output sign indicates trend direction but omits behavioral details like what the output value represents (e.g., raw momentum, scaled, or as a series), how periods are calculated, or any side effects. An output schema exists, but the description offers no additional behavioral context.

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 (one sentence) and to the point. However, it could benefit from a second sentence to add usage context without losing conciseness. It avoids fluff but is arguably under-specified.

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 (technical indicator with 4 parameters, 0% schema description, many siblings, no annotations), the description is incomplete. It does not explain return structure (despite output schema existing), does not address parameters, and provides no selection context among siblings.

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%, so the description must compensate. It mentions 'period' only implicitly and provides no explanation for 'limit', 'symbol', or 'interval'. The parameter names are generic and ambiguous without elaboration, leaving the agent to guess their roles.

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 measures price change over a period (momentum) and provides interpretation hints (positive=uptrend, negative=downtrend). This distinguishes it to some extent among 50+ sibling technical indicators, though it doesn't explicitly compare to similar ones like ROC or MACD.

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 on when to use this tool versus alternatives. Among many sibling indicators, it fails to describe ideal scenarios or conditions where momentum is preferred over other oscillators or trend-following 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 must fully disclose behavior. It only defines the indicator but does not mention what the tool returns (despite an output schema existing), data source, or any side effects. The description is insufficient for behavioral 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 very short (one sentence), which is concise but lacks structure. It does not organize information about parameters or usage, making it less useful despite its brevity.

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 4 parameters, 0% schema coverage, and an existing output schema, the description is extremely incomplete. It fails to explain how to use the parameters or what the tool returns, which is critical for a technical indicator 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 provides no information about any of the four parameters (symbol, interval, period, limit). It does not add meaning beyond the schema.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states it is a Normalized Average True Range, expressed as a percentage of close price, which distinguishes it from the sibling tool 'get_atr'. However, it does not explicitly state the verb (e.g., 'calculate' or 'get'), but the tool name implies it.

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 on when to use this tool versus alternatives. It does not mention typical use cases or prerequisites, leaving the agent without context for 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 full burden. It fails to disclose behavioral traits like read-only nature, rate limits, data freshness, or authentication requirements. For a news tool, such information is important for proper agent 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 concise and well-structured: a one-sentence purpose, a usage note, then clearly separated Args and Returns sections. Every sentence serves a purpose with no superfluous text.

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 (2 optional parameters) and the existence of an output schema, the description provides adequate context. However, the lack of behavioral transparency (rate limits, updates) leaves a gap. The Returns description is vague, but since an output schema exists, it's partially excused.

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 0% description coverage, but the description adds meaningful information: it lists values for 'category' (general, forex, crypto, merger) and explains 'limit' as number of items with default 10. This adds value beyond the schema, though it doesn't enumerate all possible categories.

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 'Get latest market news' with a specific verb and resource. It distinguishes itself from sibling tools which are mostly technical indicators (e.g., get_rsi, get_macd), making its purpose unique.

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 advises to use it 'to understand what's happening in the markets right now' and explains that news can explain price movements and predict trends. While it doesn't explicitly state when not to use, the context of sibling tools implicitly suggests using this for news vs. technical analysis.

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 provided, so description carries full burden. It only mentions the limit parameter and that it returns events, but does not disclose any side effects, permissions, rate limits, or how events are ordered.

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?

Very concise: three sentences plus an Args section. Front-loaded with main purpose, no redundant information.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a simple tool with one optional parameter and an output schema, the description is adequate. However, it lacks details like sorting order or inclusion of current vs future events.

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 0%, but the description provides an Args section explaining 'limit' as 'Number of events to return (default 5)', adding basic meaning beyond the schema.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states it retrieves 'next upcoming economic events' and provides context about market-moving implications. Among siblings, it is distinct from 'get_economic_calendar' which might be more detailed.

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 'a quick way to see what's coming up that could move markets' but does not explicitly state when to prefer this over alternatives like 'get_economic_calendar'.

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 full burden for behavioral disclosure. It only states a definition and purpose, without revealing that the tool calculates a cumulative volume indicator based on price movements, that it depends on historical data, or that it may have limitations like requiring a minimum number of data points. No behavioral traits beyond the definition are disclosed.

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, which is concise but severely under-informative. It does not front-load the most critical information (e.g., required parameter, output format). The brevity sacrifices completeness, making it insufficient for effective tool selection.

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 an output schema and 3 parameters, the description provides no context about return values, parameter effects, or tool behavior. For a technical indicator, this is highly incomplete—the agent cannot understand what OBV calculates, how to interpret results, or how to use parameters like limit and interval 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%, and the description does not explain any of the three parameters (symbol, limit, interval). The agent receives no guidance on how to use these parameters, what formats they expect, or how they affect results. This is a critical gap.

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 identifies the resource as 'On Balance Volume' and states its purpose as 'cumulative volume, confirms price trends'. However, it is somewhat tautological (restates the name) and does not clearly differentiate from sibling volume indicators like get_ad or get_mfi, leaving ambiguity about when to use this specific tool.

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 on when to use this tool versus alternatives. The phrase 'confirms price trends' implies a use case, but there is no mention of prerequisites, exclusions, or comparison to sibling tools such as get_ad, get_adosc, or get_mfi, which are also volume-related.

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 must carry the full burden. It correctly implies a read-only operation ('Get') and mentions return format. However, it does not disclose potential behavioral aspects like rate limits, data freshness, or authentication 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 front-loaded with a clear first sentence but includes additional educational content about OI interpretation that, while useful, increases length. The structured Args/Returns sections are helpful, but the overall verbosity is higher than necessary for a simple 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 simplicity (one parameter) and the presence of an output schema, the description adequately covers what the tool does, the parameter format, and the return content (contracts and USD value). No critical information appears missing for effective agent use.

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 only defines 'symbol' as a string with no description (0% coverage). The description adds meaningful context by providing examples (e.g., BTCUSDT) and stating it expects a trading pair symbol, significantly improving parameter understanding.

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 'Get open interest for a futures symbol,' specifying the verb and resource. It distinguishes from sibling tools (e.g., technical indicators) by focusing on a distinct market metric, and provides interpretive context that clarifies the tool's unique 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 explains what open interest is and how to interpret trends, which implicitly guides when to use it (e.g., for futures market sentiment). However, it lacks explicit guidance on when not to use this tool or alternatives among the many sibling indicators.

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 provided. The description lacks behavioral details like data prerequisites, timeframe considerations, or computational requirements. A single sentence does not cover the necessary transparency for a technical indicator.

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?

Extremely concise (6 words) but at the cost of missing essential information. Conciseness is positive only when the content remains helpful.

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 (4 parameters, output schema), the description is severely incomplete. No explanation of return values, default behaviors, or interpretation cues is provided.

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 has 0% description coverage. The description adds no information about parameters such as period, limit, or interval. Users get no help on what these mean for the Plus DI calculation.

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 'Plus Directional Indicator - measures upward trend strength' clearly identifies the tool's output and its purpose. It distinguishes from siblings like get_minus_di and get_dx by specifying it measures upward strength.

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 on when to use Plus DI versus other directional indicators or technical analysis tools. With many sibling tools, explicit context is missing.

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, and the description fails to disclose any behavioral traits such as side effects, data accessibility, rate limits, or whether it is read-only. The agent has no information beyond the tool's existence.

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 but excessively short, omitting essential information. It is not front-loaded with critical details, and every word does not earn its place due to missing context.

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 complexity (5 parameters, no schema descriptions, no annotations), the description is highly incomplete. It does not explain return values even though an output schema exists, and fails to compensate for the lack of parameter 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?

Schema description coverage is 0%, and the description does not explain any parameters (fast, slow, limit, interval). It provides no additional meaning beyond the schema, making parameter usage ambiguous.

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 identifies it as a 'Percentage Price Oscillator' similar to MACD, giving a basic understanding. However, it does not fully distinguish it from siblings like get_apo or get_macd, and lacks specifics on what the tool computes (e.g., returns a time series).

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 on when to use this tool vs. alternatives. The only hint is 'similar to MACD but as percentage', implying it's for percentage-based analysis, but no when-not or alternative recommendations 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?

The description only states it returns 'Current price information' without elaborating on data freshness, rate limits, or other behavioral traits. With no annotations, the description bears full responsibility but offers minimal 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 extremely concise, with a single sentence for the main purpose and clear Args/Returns sections. Every part is necessary and no extraneous information is present.

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 the presence of an output schema (signaled), the description covers the basic purpose and parameter. However, it omits any mention of data source, latency, or edge cases, which would be helpful for a complete understanding.

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 value by providing examples for the symbol parameter (e.g., BTCUSDT, ETHUSDT), which the schema lacks due to 0% description coverage. However, it does not explain the expected format or constraints beyond the examples.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the tool returns the current price of a cryptocurrency. The verb 'Get' and resource 'price' are specific, and it distinguishes from sibling technical indicator 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?

No guidance is provided on when to use this tool versus the many sibling tools. It does not specify prerequisites or conditions, leaving the agent to infer usage 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?

No annotations provided, so description carries full burden. Only states basic definition; does not disclose whether it returns a single value or time series, any side effects (none expected), or important behavioral constraints like data 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?

Single sentence, very concise. No wasted words, but lacks structure that could improve readability for multiple aspects.

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 4 parameters and no param descriptions, the tool is insufficiently documented. Despite output schema existing, the description doesn't orient the AI on what the ROC output represents (e.g., values above zero indicate bullish momentum). Incomplete for effective use.

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 0% and description adds no information about parameters. The 'period' parameter is central to ROC but not described. Limit, interval, and symbol are also ignored. Agent has to infer from schema alone.

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's about Rate of Change indicator as percentage price change, which is clear. However, it doesn't specify the resource type (e.g., historical values) and doesn't differentiate from other sibling indicators beyond being a different technical analysis tool.

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 on when to use this tool versus alternatives. No mention of prerequisites, best practices, or scenarios where ROC is preferred over other indicators like momentum or moving averages.

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?

Despite no annotations, the description discloses that the tool returns 'RSI values with interpretation' and explains the meaning of the indicator. It does not mention rate limits or data freshness, but it is sufficiently transparent for a simple read operation.

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 well-structured with a brief overview, a bulleted list for parameters, and a returns line. It is front-loaded with the RSI interpretation, though the 'Args:' and 'Returns:' headers could be omitted for 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 the presence of an output schema (though unseen) and many sibling indicators, the description adequately explains the tool's purpose, parameters, and output interpretation. It could mention error handling or time zone assumptions, but it is complete enough 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?

Schema description coverage is 0%, but the description compensates by listing each parameter (symbol, interval, period, limit, start_time, end_time) with clear examples and defaults, adding significant meaning beyond the schema.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly specifies 'Get RSI' for a cryptocurrency, explains the RSI scale (0-100) with oversold/overbought thresholds, and provides examples. This distinguishes it from sibling 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 implies usage context through the RSI interpretation (oversold/overbought signals) but does not explicitly state when to use this tool versus alternatives like get_stochrsi or get_mfi, nor does it provide exclusion criteria.

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 provided, so description must carry full burden. It only states the basic indicator definition and a simple bullish/bearish rule, but does not disclose return format, error behavior, data source, or any 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?

Extremely short, but under-specified. It does not earn its place by covering essential information about parameters or usage. More text with parameter explanations would be appropriate.

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 5 parameters with no documentation and an output schema that is not referenced, the description is completely inadequate for an agent to select and invoke this tool 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?

Zero schema coverage and no parameter descriptions in the text. Key parameters like acceleration, maximum, interval, limit, and symbol are not explained. The agent has no help understanding what values to provide.

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 names the indicator (Parabolic SAR) and its function as a trailing stop and trend indicator, with a specific interpretation rule. This distinguishes it from the many sibling indicator 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?

No guidance on when to use this tool vs alternatives. Does not mention suitable market conditions, timeframes, or limitations of the Parabolic SAR indicator.

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. It only states 'smooths price data' but does not explain the calculation, side effects, permissions needed, or what the output contains. This is insufficient for safe usage.

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 (one sentence), but it is not overly concise—it sacrifices necessary detail. It front-loads the purpose, but the lack of structure and substance reduces effectiveness.

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 four parameters, no param descriptions, no annotations, and a likely complex output (though output schema exists), the description is woefully incomplete. It fails to cover return format, defaults, or how the tool should be invoked.

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 adds no information about the four parameters (symbol, period, interval, limit). The agent must rely solely on the schema, which lacks 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 clearly states the tool's function: computing a Simple Moving Average to smooth price data and identify trend direction. This differentiates it from many sibling indicators, though it could be more specific about its type relative to other moving averages.

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 SMA over other moving averages like EMA or WMA, nor any contextual or prerequisite information. The description does not help the agent choose between numerous similar 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 must cover behavioral traits. It clearly states the return is 'Stochastic values with interpretation' and outlines the scale (0-100). However, it does not disclose idempotency, rate limits, or any side effects. Since the tool is read-only, this is adequate but leaves room for more detail.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is well-structured with a clear first sentence, a paragraph on interpretation, and an Args/Returns section. It is concise but includes necessary details. Minor redundancy with defaults already in schema does not harm conciseness significantly.

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 7 parameters and an output schema, the description covers the indicator's purpose, parameter examples, and return value interpretation. It does not elaborate on error handling or data source freshness, but it is sufficient for an indicator tool with standard usage. The output schema existence reduces the need for extensive return 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?

Schema description coverage is 0%, so the description fully compensates by listing each parameter with examples (e.g., 'BTCUSDT', '1h'), defaults, and interpretation (fastk_period, slowk_period). This adds significant meaning beyond the schema's type and default values, making the tool easy to use correctly.

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 explicitly states 'Get Stochastic Oscillator for a cryptocurrency' with a clear verb and resource. It also explains the indicator's purpose (momentum on a scale of 0-100), which distinguishes it from sibling tools like get_rsi or get_macd. The description provides specific interpretation thresholds, making it easy to identify.

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 explains when to interpret the oscillator (oversold/overbought) but does not explicitly state when to use this tool versus alternative indicators like RSI or StochRSI. No exclusions or context for when not to use this tool are provided. Usage is implied by the indicator's common application.

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 full burden. It only describes the algorithmic nature (applying stochastic to RSI) but fails to disclose behavioral traits such as whether it is read-only, data requirements, rate limits, or output characteristics beyond the indicator meaning.

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 (one sentence) and direct, but it is not well-structured: it compresses the definition and a comparative note without clear separation. It earns no extra credit for conciseness beyond minimalism.

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 six parameters, no annotations, and an output schema that is not referenced, the description lacks essential completeness. It explains the indicator concept but omits parameter roles, return structure, and usage context, leaving significant gaps for correct invocation.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The schema has 0% parameter descriptions, and the description adds no meaning or context for any of the six parameters (fastd, fastk, limit, period, symbol, interval). The AI agent must rely solely on parameter names and defaults, which is insufficient.

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 computes Stochastic RSI by applying stochastic to RSI, and distinguishes it from RSI by noting higher sensitivity. This is specific enough given the large set of sibling technical 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 hints at when to choose this over RSI ('More sensitive than RSI'), but does not provide explicit guidance on when to use it versus other stochastic or oscillatory indicators among the siblings. No when-not-to-use or alternative recommendations.

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 but only adds a qualitative claim ('smooth with minimal lag'). No information about behavior such as data source, calculation method, or response format 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 very short (one sentence) but lacks necessary details. It is not effectively front-loaded with the most critical usage information.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Despite having 4 parameters and an output schema, the description provides almost no context. It fails to explain what T3 is, how parameters affect it, or what the output contains.

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% for 4 parameters. The description does not explain any parameter's meaning or role, leaving the agent to infer from schema names alone.

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 'T3 Moving Average' and highlights a differentiating feature ('very smooth with minimal lag'). This is clearer than a tautology, but it could be more specific about what the tool computes.

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 sibling tools like get_sma or get_ema. There is no mention of use cases or alternatives.

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 should disclose behavioral traits. It only provides a comparative performance claim (less lag) but omits any information about it being read-only, authorization needs, rate limits, or 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, efficient sentence that conveys the core purpose and a key comparative advantage without any redundant 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 zero description coverage, lack of annotations, and four parameters, the description is insufficient for complete understanding. While an output schema exists, the tool definition still lacks essential context about parameters and 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?

Schema description coverage is 0%, and the description adds no meaning to any of the four parameters (symbol, limit, period, interval). This leaves agents without understanding of parameter roles.

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 explicitly states 'Triple Exponential Moving Average' and distinguishes itself from DEMA by noting 'even less lag than DEMA', making the tool's purpose and differentiation 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?

No guidance is provided on when to use TEMA over other moving averages or indicators. The description merely mentions less lag relative to DEMA, but does not offer context on scenarios 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?

No annotations provided. Description does not disclose behavioral traits such as data frequency, definition of 'top traders', or error handling. Minimal 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?

Description is concise and well-structured: a clear one-line summary, explanatory sentence, then Args/Returns. No filler.

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?

Adequate for a simple one-parameter tool with an output schema. Lacks details like update frequency and definition of top traders, but overall 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?

With 0% schema coverage, description adds a format example (e.g., BTCUSDT) and notes it's a trading pair. This adds value beyond the schema's 'string' type but lacks depth.

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?

Clearly states it gets the top trader long/short ratio and distinguishes from overall ratio by noting it's a more reliable signal from whales. Sibling tool get_long_short_ratio exists, and this description explicitly contrasts.

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?

Implies use when following smart money and contrasts with overall ratio. However, no explicit when-not or prerequisites are given.

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 bears full responsibility for behavioral disclosure. It fails to mention that the calculation requires a previous close price, meaning it needs historical data. There is no information on error handling, rate limits, or required permissions. The formula is given but important behavioral traits are omitted.

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 (12 words) and front-loads the core definition. However, it lacks essential details, making it under-informative. Conciseness is achieved but at the expense of 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?

Given three parameters, no schema descriptions, and an existing output schema, the description should provide more context about what the output contains and any data requirements. It fails to mention that the tool depends on previous close data or how to interpret the results. The description is insufficient for the tool's complexity.

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 0% description coverage, and the description does not explain any of the three parameters (symbol, limit, interval). It does not clarify how they relate to the True Range calculation. This leaves the agent to guess the meaning and constraints of each parameter.

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 defines what True Range is by providing its mathematical formula. It distinguishes the tool from siblings by specifying a unique technical indicator. However, it does not explicitly state that the tool returns a series of True Range values for a given symbol and time interval, which could be inferred but is not directly stated.

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_atr or other volatility indicators. There is no mention of use cases, prerequisites, or exclusions. The description only states the formula without contextual usage advice.

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 only says 'double-smoothed SMA,' which implies a calculation but does not disclose that it is read-only, requires price data, or any other behavioral traits. The output schema exists but is not referenced.

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 (one phrase), which is concise but lacks essential structure. It does not start with a clear action-oriented 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?

Given the tool's complexity (technical indicator with four parameters and an output schema), the description is too sparse. It does not explain input semantics or output characteristics, leaving the agent to guess.

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 four parameters (limit, period, symbol, interval). The agent must infer their meaning from names, which is insufficient for 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 states 'Triangular Moving Average - double-smoothed SMA,' which identifies the resource but lacks a verb (e.g., 'calculates' or 'returns'). It distinguishes from other moving average tools by specifying the type, but the purpose is not fully explicit.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

No guidance is given on when to use this tool versus alternatives like SMA, EMA, or other MAs. There is no mention of prerequisites, context, 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?

The description does not disclose behavioral traits such as whether the operation is read-only, any destructive potential, or permission requirements. Without annotations, this lack of transparency is a significant gap.

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 concise, but it sacrifices clarity. While every sentence earns its place, it is too brief to be fully effective.

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 an output schema, the description lacks essential details for correct usage, such as how to specify parameters. It is not complete enough for an agent to invoke the tool confidently.

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 provides zero parameter information. With 0% schema description coverage, the tool description must explain parameters like symbol, limit, period, and interval, but it does not.

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 names the indicator and explains its purpose as a momentum oscillator that filters noise. It distinguishes TRIX from other indicators like RSI or MACD. However, it could explicitly state that it returns TRIX values for a given symbol.

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 on when to use this tool versus alternatives like get_rsi or get_macd. It does not mention any prerequisites or contexts where TRIX is 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, the description is the sole source of behavioral info. It only states the indicator combines momentum but does not disclose that it is a read-only calculation, what the output contains, or any 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, clear sentence with no fluff. It is front-loaded but could benefit from a brief usage note without harming 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?

Despite having an output schema (reducing need for return value explanation), the description lacks parameter descriptions, usage context, and behavioral traits. For a tool with 6 parameters and many siblings, it is 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?

Schema description coverage is 0%, but the tool description adds no explanation for parameters like period1, period2, period3, interval, limit, or symbol. The agent has no semantic aid beyond default values.

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 computes the Ultimate Oscillator, which combines short, medium, and long-term momentum. This verb-resource pairing is specific and distinguishes it from sibling tools like RSI or stochastic.

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 (e.g., RSI, stochastic). The description does not mention prerequisites, typical intervals, or context for best use.

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 only states the threshold levels but does not disclose behavioral aspects like read-only nature, data source, or whether the indicator uses historical data. The parameter 'limit' implies pagination or count control, but that is not described.

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 concise—two short sentences with no wasted words. It efficiently conveys the indicator identity and key thresholds. However, it could be slightly more informative without losing 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?

For a tool with 4 parameters, no schema descriptions, no annotations, and an output schema that is not documented in the description, this is incomplete. The description does not explain how parameters affect the output or what the return structure looks like, leaving significant gaps for effective use.

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%, yet the description adds no parameter information beyond the thresholds. The four parameters (symbol, limit, period, interval) are not explained; the agent must infer meaning from names alone, which may be ambiguous (e.g., interval could mean time frame or step).

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 a Williams %R momentum oscillator and provides key thresholds (>-20 overbought, <-80 oversold). This distinguishes it from sibling indicators like RSI or Stochastics, though it lacks an explicit verb like 'calculates' or 'returns'.

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 Williams %R compared to other momentum oscillators such as get_rsi or get_stochastic. The description does not mention typical use cases, prerequisites, or context, leaving the agent without selection advice.

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?

Discloses linear weighting and emphasis on recent prices, but no annotations exist; output schema covers return structure, but behavioral details like weight application are absent.

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?

Single sentence efficiently conveys core purpose; lacks parameter details but remains clear 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?

With zero schema coverage and no parameter explanations, the description is insufficient for correct invocation despite output schema existing; missing usage guidance and parameter semantics.

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?

No parameter descriptions in schema or description; critical parameters like period, limit, interval are unexplained.

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?

Clearly states it calculates a linearly weighted moving average that emphasizes recent prices, distinguishing it from simple and exponential moving averages.

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 on when to use this vs. sibling tools like get_sma or get_ema; the description only states what it is, not when to apply it.

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