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

Discloses concurrency and that it surfaces the highest and lowest paying venues with spread. However, with no annotations, it lacks details on error handling, rate limits, authentication, or what happens if symbol/exchange not found. Moderate 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?

Two sentences, front-loaded with action, no redundant text. Every sentence adds value.

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 simple behavior and existence of output schema, the description is fairly complete. It could mention that exchanges parameter defaults to all, but that is in schema. Minor gaps in not specifying single-symbol constraint explicitly.

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

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

Schema coverage is 100%, so baseline is 3. The description adds no new meaning beyond the schema; it does not elaborate on parameter defaults or behaviors.

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 compares funding rates for one perpetual symbol across exchanges, with a specific verb 'compare' and resource. Distinguishes from siblings like get_funding_rate and get_funding_rate_history by focusing on cross-exchange arbitrage.

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 for funding rate arbitrage but does not explicitly state when to use versus alternatives, nor does it provide exclusions or prerequisites. No mention of when-not-to-use or specific 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?

Notes 'no network call', disclosing a key behavioral trait. With no annotations, this adds value. No additional behavioral details needed.

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

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

Two sentences, front-loaded with main action, no wasted words. Highly concise and structured.

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

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

For a simple capability tool, description is sufficient. Output schema likely covers return format, so no need for more detail.

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 parameters; schema coverage is 100%, so baseline applies. Description adds nothing about parameters, but none needed.

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 shows which data each exchange can return, distinguishing it from sibling tools that retrieve actual 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?

Explicitly instructs to use this before calling a data tool to pick an exchange, providing clear when-to-use guidance. Lacks explicit when-not-to-use 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?

No annotations provided, so description bears full burden. Only states it returns current rate; does not disclose whether authentication is needed, rate limits, data freshness, or error cases. Minimal 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?

Single sentence of six words with no superfluous information. Concise and front-loaded with the key action.

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 an output schema exists, return values need not be described. However, among 13 sibling tools, no differentiation context provided. Still, for a simple parameter set, the description covers the essential functionality adequately.

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

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

Schema coverage is 100% with descriptions for both parameters. Description adds no extra meaning beyond schema. Baseline of 3 is appropriate as description does not hinder understanding, but also does not enhance it.

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 gets the current perpetual funding rate for a symbol. Verb 'get', resource 'funding rate', and qualifiers 'current' and 'for a symbol' make purpose specific. Distinguishes from siblings like get_funding_rate_history (history) and compare_funding (comparison).

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., compare_funding, get_funding_rate_history). No context about prerequisites or limitations. Simply states what it does without 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 only states ordering ('newest last') but omits other behavioral details like data range limits, pagination behavior, or latency implications. The output schema exists but does not cover behavioral traits.

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, direct sentence with no wasted words. Front-loaded with the core action and resource.

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 an output schema and simple parameters (3, 1 required), the description covers the essential purpose but lacks context on data range, pagination, or error conditions. Sufficient for a basic tool but not thorough.

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

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

Schema coverage is 100% with parameter descriptions already explaining symbol, exchange, and limit. The description adds no additional meaning beyond what the schema provides, meeting the baseline but not exceeding.

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 historical funding rates for a perpetual symbol, with ordering 'newest last'. It uses a specific verb ('get') and resource ('funding rate history'), and distinguishes from siblings like 'get_funding_rate' (current rate) and 'compare_funding'.

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

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

The description provides no guidance on when to use this tool versus alternatives. It does not mention that it is for historical data only, nor does it exclude use cases where other tools are more appropriate.

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

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

With no annotations provided, the description carries full burden for behavioral disclosure. It only says 'Recent public liquidations' but does not clarify recency, rate limits, pagination, or whether it applies to all symbols. This is 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 a single, concise sentence that is front-loaded and easy to parse. However, it could be slightly more structured (e.g., adding an example or clarifying 'recent'), but overall it is efficient.

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 lack of annotations and the presence of an output schema, the description still feels incomplete. It does not explain what 'recent' means, how liquidations are returned, or any limitations, which is insufficient for an agent to reliably 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 coverage is 100%, so the input schema already documents each parameter adequately. The description adds no additional semantic value beyond what the schema provides, justifying the baseline score.

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 'Recent public liquidations for a perp symbol,' specifying the verb (implicit get), resource (liquidations), and scope (perp symbol). This distinguishes it from sibling tools like get_recent_trades or get_open_interest.

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 any guidance on when to use this tool versus alternatives, nor does it mention prerequisites or exclusions. It simply states what it does, leaving the agent to infer usage from context.

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

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

With no annotations, the description carries the full burden. It discloses the metric is a ratio and the venue, but omits details on data aggregation, update frequency, or any rate limits.

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 with no wasted words, though it could include a bit more context 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?

An output schema exists, so return values are covered. The description is adequate for a simple metric tool but lacks caveats like data availability only for certain symbols.

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

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

Schema coverage is 100%, so the schema documents parameters. The description adds no extra meaning beyond 'global' and 'futures only', which is already implied by the tool name.

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 a global long/short account ratio specifically for Binance USDⓈ-M futures, which distinguishes it from sibling tools like get_funding_rate or get_open_interest.

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 it's only for Binance futures but provides no guidance on when to use this tool versus alternatives like get_funding_rate or get_liquidations.

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 disclose behavioral traits. It only says 'recent', which is vague regarding update frequency, data source, or ordering. Does not describe whether results are calculated or cached.

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 (3 words) but front-loaded. While concise, it sacrifices substance — the single word 'Recent' does not clarify the time window or default behavior (e.g., last 24 hours). Could be more informative without verbosity.

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 4 parameters, missing guidance on required timeframes vs optional, date ranges, or candle ordering. Output schema exists but description doesn't hint at structure. Sibling tools suggest a financial domain, but the description fails to elaborate on typical use cases.

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

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

Schema coverage is 100% with detailed descriptions for all 4 parameters (symbol example, exchange default, timeframe options, limit default/max). The description adds no extra meaning, so 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 'Recent OHLCV candles' clearly conveys the tool returns recent OHLCV data, distinguishing it from siblings like get_price (single price) and get_recent_trades (trades). The verb is implicit in the tool name but the description is a noun phrase, falling short of 'get OHLCV 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?

No guidance on when to use this tool vs alternatives like get_price or get_recent_trades. No mention of time ranges, live vs historical data, or prerequisites. The agent has 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?

With no annotations, the description carries full burden but only states the output type. It does not disclose whether the operation is read-only, requires authentication, or any side effects. The description implies a safe read but lacks explicit 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 concise (one sentence, no fluff) and front-loads the key purpose. However, it is very brief and could benefit from more detail 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?

Given the existence of an output schema and simple parameters, the description covers the basic purpose. However, it omits context like the restricted exchange and the fact it returns only current open interest, not historical.

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

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

The input schema already describes both parameters with examples and a note. The description adds no additional semantics beyond the schema, so baseline 3 is appropriate.

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

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

The description clearly states the tool returns 'Current open interest for a perp symbol.', which is a specific verb-resource combination that distinguishes it from sibling tools like get_funding_rate or get_long_short_ratio.

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

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

No guidance is given on when to use this tool versus alternatives. It does not mention that the exchange parameter has a restriction ('gate' not supported) or that this is for current data only.

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 says 'top-of-book' which typically means only the best bid and ask, but the depth parameter allows multiple levels (up to 50). This is misleading. No annotations exist, so the description should clarify the behavior but does not.

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), but it omits important context such as the return format or the effect of the depth parameter. It is concise 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 the tool has three parameters and an output schema, the description is insufficient. It does not explain that order book data includes both bids and asks, how depth affects the output, or that exchange defaults to Bybit. The output schema may cover return values, but the description should provide more context for an agent to understand what is returned.

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

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

Schema coverage is 100% with descriptions for all three parameters. The tool description adds no extra meaning beyond the schema, so baseline score of 3 is appropriate.

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

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

The description 'Top-of-book bids and asks' combined with the tool name 'get_order_book' clearly indicates it returns order book data, focusing on best bids and asks. However, it doesn't explicitly state that it returns a snapshot of multiple levels, which is suggested by the depth parameter.

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 siblings like get_price or get_ohlcv. There is no mention of use cases, prerequisites, 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 provided, the description carries full burden for behavioral transparency. It only states the output type (price and stats) without mentioning any behavioral traits like destructuring, rate limits, or whether it returns data from multiple exchanges. This is insufficient.

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

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

The description is a single, front-loaded sentence with no unnecessary words. Every word contributes to understanding the tool's purpose.

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

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

Given the simple nature (2 parameters, 100% schema coverage, output schema exists), the description is largely complete. It could mention what the '24h stats' include, but overall it adequately covers the basics.

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

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

Schema description coverage is 100% with clear parameter descriptions (symbol format, exchange default). The description adds minimal value beyond what the schema provides; it confirms the purpose but does not enhance 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 the tool returns 'last price and 24h stats for a symbol', using a specific verb ('get') and resource. It distinguishes from siblings like get_ohlcv (detailed OHLCV) and get_order_book (order book) by focusing on price and 24h summary stats.

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 fetching current price and 24h stats, but does not explicitly state when to use this versus alternatives like get_ohlcv or get_order_book. No guidance on when not to use it 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?

No annotations are provided, so the description must carry the burden. It mentions 'public' (non-critical) and 'recent' but does not disclose rate limits, auth requirements, or pagination behavior. The presence of an output schema partly compensates.

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?

One clear sentence with no fluff. Could be slightly restructured for clarity (e.g., 'Get recent public trades for a symbol.') but effective as is.

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 retrieval tool with full schema and output schema, the description is largely complete. It lacks details like default ordering or rate limits but remains functional.

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

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

Schema coverage is 100%, so the description adds value by clarifying 'public trades' (not private or included in other scopes). This semantic beyond the schema justifies a score above baseline 3.

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 'most recent public trades for a symbol.' This distinguishes it from sibling tools like get_ohlcv (candles), get_order_book (order depth), and get_liquidations (liquidation events).

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 indicates when to use (when you need recent public trades for a symbol) but does not provide explicit when-not-to-use or comparisons to alternatives. Many siblings exist, so more guidance would help.

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 only states 'list' without disclosing behavioral traits such as ordering, pagination, or caching behavior. For a read-only list, this is minimal but not informative enough for an agent to understand side effects or constraints.

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

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

The description is a single concise sentence, front-loading the key action. Every word is necessary, and there is no extraneous content.

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

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

Given the tool has no parameters and an output schema is present, the description is complete enough. It clearly states the tool's purpose, and the output schema will define the return structure. No additional context is necessary.

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

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

The tool has zero parameters, so schema coverage is 100%. The description adds no parameter semantics, which is acceptable as no parameters exist. Baseline for 0 parameters is 4.

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

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

The description clearly states the tool lists exchanges supported by the server. It uses a specific verb ('List') and resource ('exchanges'). It distinguishes from sibling tools that operate on specific exchange data rather than the list itself.

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

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

The description implies usage when needing to know available exchanges, but it does not explicitly state when to use or when not to use, nor does it provide alternatives. For a simple list tool, this is acceptable but could be improved with context like 'Use before querying exchange-specific data.'

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 the description must carry the burden. It mentions query matching but omits details like case-insensitivity, default exchange (bybit), and limit constraints. The input schema fills some gaps, but the description lacks behavioral disclosure (e.g., pagination behavior, empty result handling).

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

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

Two sentences, front-loaded with purpose and usage scenario. No redundant information; every sentence earns its place.

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

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

Given simple parameters and existence of output schema, the description is nearly complete. However, it could mention the output format briefly or note that results are partial matches (implied by 'substring'). Still sufficient for an adequately documented tool.

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

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

Schema coverage is 100%, so baseline is 3. The description adds context with examples but does not elaborate on parameters beyond the schema. No additional semantics provided for query, exchange, or limit.

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 searches for market symbols matching a query, with examples 'BTC' and 'SOL/USDT'. It distinguishes itself from sibling tools (e.g., get_price, list_exchanges) by focusing on symbol discovery, which is a distinct 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?

Explicitly says 'Useful when you don't know the exact symbol format an exchange expects.' This provides clear context for when to use the tool, but does not cover when not to use or mention alternative tools.

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