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 mentions that the operation is 'faster than cancel + recreate,' which adds useful behavioral context about performance. However, it does not disclose critical details such as required permissions, whether the edit is atomic or reversible, error conditions, or rate limits, leaving gaps for a mutation 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 concise and front-loaded, with two sentences that efficiently convey the tool's purpose and a key advantage. Every word earns its place, with no redundant or vague language, making it easy to parse quickly.

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 mutation tool with no annotations and no output schema, the description is adequate but incomplete. It covers the basic purpose and a performance hint, but lacks details on behavioral traits, error handling, or return values, which are important for safe and effective use in this 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 100%, so the schema fully documents all 7 parameters. The description adds minimal value beyond the schema by listing the editable fields ('price, quantity, or slippage'), but does not provide additional semantics like unit explanations or constraints. This meets the baseline for high schema coverage.

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 verb ('Edit'), resource ('existing unfilled Alpha Arcade order'), and scope ('in-place'), specifying what can be changed ('price, quantity, or slippage'). It distinguishes from the sibling 'alpha_cancel_order' by noting it's 'faster than cancel + recreate,' making the purpose specific and differentiated.

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

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

The description provides clear context for when to use this tool: for editing unfilled orders in-place, and implies an alternative ('cancel + recreate') without explicitly naming it. However, it lacks explicit exclusions or comparisons with other order-related tools like 'alpha_create_limit_order' or 'alpha_create_market_order,' which could be relevant for order modifications.

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

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

With no annotations provided, the description carries the full burden of behavioral disclosure. It effectively describes key behaviors: it's a destructive action (cancels orders), specifies prerequisites (requires escrowAppId and orderOwner), and outlines outcomes (refunds USDC/tokens and ~0.957 ALGO collateral). This adds valuable context beyond the input schema, though it doesn't cover error conditions or 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?

The description is front-loaded with the core purpose in the first sentence, followed by prerequisites and outcomes. Every sentence earns its place by providing essential information without redundancy, making it highly efficient and well-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?

Given the complexity of a cancellation tool with no annotations and no output schema, the description does a good job covering purpose, prerequisites, and outcomes. It could be more complete by explaining error cases or return values, but it provides sufficient context for an agent to understand the tool's role and effects in the system.

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

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

Schema description coverage is 100%, so the schema already documents all parameters. The description mentions 'escrowAppId and orderOwner' as required, which aligns with the schema but doesn't add meaning beyond it. It doesn't explain parameter interactions or provide additional context, so it meets the baseline for high schema coverage.

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 specific action ('Cancel an open Alpha Arcade order'), identifies the resource ('Alpha Arcade order'), and distinguishes it from siblings like 'alpha_amend_order' by focusing on cancellation rather than modification. It's precise and action-oriented.

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 open orders (via 'Cancel an open Alpha Arcade order') and mentions required parameters ('Requires escrowAppId and orderOwner'), but doesn't explicitly state when to use this tool versus alternatives like 'alpha_amend_order' or 'alpha_get_open_orders'. It provides some context but lacks explicit guidance on alternatives 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 are provided, so the description carries full burden. It mentions 'Winning = 1:1 USDC,' which hints at conversion rates, but lacks critical behavioral details: whether this is a read-only or mutating operation, authentication requirements, rate limits, error conditions, or what happens on failure. The description is insufficient for a tool that likely involves financial transactions.

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

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

The description is concise and front-loaded with the core purpose in one sentence. The second sentence adds useful rate information ('1:1 USDC'), but could be integrated more smoothly. Overall, it's efficient with minimal waste.

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 (financial claiming tool with 5 parameters, no annotations, no output schema), the description is incomplete. It lacks details on behavioral traits, error handling, return values, and how it fits among siblings. The absence of annotations and output schema increases the burden, which the description does not adequately meet.

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

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

Schema description coverage is 100%, so the schema already documents all parameters. The description adds no additional semantic context beyond implying 'marketAppId' and 'assetId' relate to a resolved market and outcome tokens. It doesn't explain parameter interactions or provide examples, meeting the baseline for high schema coverage.

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: 'Claim USDC from a resolved Alpha Arcade market by redeeming outcome tokens.' It specifies the verb ('claim'), resource ('USDC'), and context ('resolved Alpha Arcade market'), but does not explicitly differentiate it from sibling tools like 'alpha_get_positions' or 'alpha_merge_shares' that might involve similar assets or markets.

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 minimal guidance: it implies usage when a market is resolved and tokens are redeemable, but offers no explicit when-to-use rules, prerequisites (e.g., market must be resolved), or alternatives among siblings. For example, it doesn't clarify if this is for winners only or how it differs from 'alpha_merge_shares' in handling tokens.

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 and delivers well. It discloses critical behavioral traits: collateral locking ('Locks ~0.957 ALGO collateral'), return value ('Returns escrowAppId'), and post-action requirement ('save it for cancel_order'). It doesn't mention error conditions or rate limits, but covers essential mutation 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?

Perfectly concise with three information-dense sentences: purpose statement, parameter unit explanation, and behavioral/post-action guidance. Every sentence earns its place with zero wasted words, and the most critical information (tool purpose) is 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?

For a mutation tool with no annotations and no output schema, the description does well by explaining the action, units, collateral impact, and return value. It could be more complete by mentioning error cases or authorization requirements, but covers the essential context given the tool's complexity and lack of structured metadata.

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%, providing detailed parameter documentation. The description adds value by explaining the microunit convention with examples (500000 = $0.50, 1000000 = 1 share) and mentioning collateral implications, but doesn't provide additional parameter semantics beyond what the schema already covers thoroughly.

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 specific action ('Place a limit order') on a specific resource ('Alpha Arcade prediction market'), distinguishing it from siblings like 'alpha_create_market_order' (different order type) and 'alpha_cancel_order' (different action). It precisely defines the tool's function without being tautological.

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

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

The description provides clear context for when to use this tool (placing limit orders with specific price/quantity units) and implicitly contrasts with 'alpha_create_market_order' by specifying 'limit order'. However, it doesn't explicitly state when NOT to use it or mention all relevant alternatives like 'alpha_amend_order' for modifications.

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

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

With no annotations provided, the description carries the full burden of behavioral disclosure. It mentions that the order is placed 'with auto-matching' and specifies the return values, but fails to describe critical behaviors: whether this is a read-only or mutating operation (implied mutation from 'Place'), authentication requirements, rate limits, error handling, or side effects. The description is insufficient for a tool that likely executes financial transactions.

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 front-loads the core action ('Place a market order') and includes key details (system, unit specification, return values). There's no wasted text, though it could be slightly more structured for readability.

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 8 parameters (6 required), no annotations, and no output schema, the description is inadequate. It lacks behavioral context (e.g., mutation effects, auth needs), usage guidance, and fails to explain the purpose of parameters like 'position' or 'itemsPerPage'. The return values are listed but not explained, leaving the agent with significant gaps in 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 100%, so the schema fully documents all parameters. The description adds minimal value beyond the schema: it clarifies that price, quantity, and slippage are in 'microunits' (already in schema descriptions) and mentions 'auto-matching' (not parameter-related). No additional parameter semantics, constraints, or interactions are explained.

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 action ('Place a market order') and the target system ('Alpha Arcade'), with specific mention of 'auto-matching' as a key feature. It distinguishes itself from sibling tools like 'alpha_create_limit_order' by specifying 'market order', but doesn't explicitly contrast with other order-related tools like 'alpha_amend_order' or 'alpha_cancel_order'.

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

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

No guidance is provided on when to use this tool versus alternatives. The description doesn't mention when a market order is appropriate compared to limit orders (available via 'alpha_create_limit_order'), nor does it discuss prerequisites, error conditions, or typical use cases. The agent must infer usage from the tool name and description 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 provided, the description carries full burden. It discloses that the tool fetches data (implied read-only) and describes return format details like the options array for multi-choice markets. However, it doesn't mention pagination behavior (implied by itemsPerPage parameter but not explained), rate limits, authentication needs, or error conditions.

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

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

Two sentences with zero waste. The first sentence states purpose and return format. The second provides crucial behavioral detail about multi-choice markets. Every word earns its place, and information is front-loaded appropriately.

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 read-only tool with 2 optional parameters and no output schema, the description is reasonably complete. It explains what data is returned and includes important behavioral details about market structure. However, it doesn't address pagination behavior (implied but not explained) or potential limitations, leaving minor gaps.

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

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

Schema description coverage is 100%, so the schema fully documents both parameters. The description adds no parameter-specific information beyond what's in the schema. This meets the baseline of 3 since the schema does all the work, but the description doesn't compensate with additional context about parameter interactions or effects.

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 specific action ('Fetch all live Alpha Arcade prediction markets') and resource ('prediction markets'), distinguishing it from siblings like alpha_get_market (single market) and alpha_get_reward_markets (different market type). It explicitly mentions what data is returned, making the purpose unambiguous.

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

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

The description implies usage context by specifying it returns 'live' markets and summary data, suggesting it's for overview rather than detailed trading. However, it doesn't explicitly state when to use this versus alternatives like alpha_get_market or alpha_get_reward_markets, nor does it mention prerequisites or exclusions.

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

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

No annotations are provided, so the description carries the full burden. It mentions that marketId is 'used for API mode when ALPHA_API_KEY is set', adding some behavioral context about authentication dependencies. However, it lacks details on rate limits, error handling, response format, or whether it's read-only/destructive, which are critical for a tool with no annotations.

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 front-loads the purpose and key parameters. It avoids unnecessary words, though it could be slightly more structured by separating usage guidance into a second sentence for 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 no annotations and no output schema, the description is moderately complete for a read operation. It covers the main purpose and parameter usage but lacks details on behavioral traits like response format, error conditions, or authentication requirements. This leaves gaps for an agent to use the tool effectively without additional 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 100%, so the schema already documents all parameters thoroughly. The description adds marginal value by emphasizing that marketAppId is 'always required' and that marketId provides 'richer API data', but doesn't explain semantics beyond what the schema provides. Baseline 3 is appropriate given high schema coverage.

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 fetches details for a single prediction market ('Fetch full details for a single Alpha Arcade prediction market'), specifying the resource and action. It distinguishes from siblings like 'alpha_get_live_markets' (which likely lists multiple markets) by focusing on a single market, though it doesn't explicitly name alternatives.

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

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

The description implies usage by stating 'Pass marketAppId... and optionally marketId... for richer API data', which suggests when to use the optional parameter. However, it doesn't provide explicit guidance on when to use this tool versus siblings like 'alpha_get_live_markets' or 'alpha_get_reward_markets', leaving the context somewhat implied.

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

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

With no annotations provided, the description carries the full burden. It discloses the default wallet behavior, which is valuable, but doesn't mention other behavioral traits like whether this is a read-only operation, potential rate limits, error conditions, or pagination details (implied by itemsPerPage but not explained). The description adds some context but leaves significant gaps.

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

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

The description is a single, efficient sentence that front-loads the core purpose and includes essential contextual information about default behavior. Every word earns its place with zero redundancy or wasted 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?

For a tool with 4 parameters, 100% schema coverage, but no annotations and no output schema, the description is adequate but incomplete. It covers the purpose and a key default behavior, but lacks information about return format, error handling, or other behavioral expectations that would help an agent use it correctly in complex scenarios.

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

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

Schema description coverage is 100%, so the schema already fully documents all parameters. The description adds marginal value by clarifying the default behavior for walletAddress (uses active MCP wallet if omitted), but doesn't provide additional semantic context beyond what's in the schema descriptions. This meets the baseline for high schema coverage.

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 specific action ('Fetch all open orders') and resource ('for a wallet on a specific Alpha Arcade market'), distinguishing it from siblings like alpha_get_positions (positions) or alpha_get_orderbook (orderbook). It precisely defines scope without ambiguity.

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

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

The description provides clear context for when to use this tool (to get open orders for a wallet on a market) and includes a helpful default behavior (uses active MCP wallet if walletAddress omitted). However, it doesn't explicitly differentiate from potential alternatives like alpha_get_positions or specify when not to use it.

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

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

With no annotations provided, the description carries the full burden of behavioral disclosure. It states the tool fetches and merges data, implying a read-only operation, but doesn't address critical aspects like rate limits, authentication requirements, error handling, or the format of the returned data. The mention of 'paginated responses' in the schema hints at behavior, but the description doesn't elaborate on this.

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

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

The description is extremely concise and front-loaded, consisting of just two sentences that directly convey the tool's purpose and key features. Every word earns its place, with no redundant or vague language.

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 fetching and merging orderbook data, the lack of annotations, and no output schema, the description is incomplete. It doesn't explain the structure of the returned data, how the merging works, what 'YES-perspective view' means, or how the spread calculation is performed. This leaves significant gaps for an agent to understand the tool's behavior fully.

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 description coverage is 100%, so the schema already documents all parameters thoroughly. The description adds no additional meaning about the parameters beyond what the schema provides, such as explaining the significance of 'marketAppId' or the implications of network choice. However, it doesn't contradict the schema, so the baseline score of 3 is appropriate.

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

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

The description clearly states the specific action ('Fetch'), the resource ('on-chain orderbook'), and the distinctive transformation ('unified YES-perspective view'). It explicitly distinguishes this tool from siblings by mentioning the merging of all 4 sides and spread calculation, which no other tool in the list addresses.

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. While it mentions the unified view, it doesn't specify scenarios where this is preferred over other order-related tools like alpha_get_open_orders or alpha_get_market, nor does it mention prerequisites or exclusions.

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

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

No annotations are provided, so the description carries the full burden of behavioral disclosure. It mentions the tool fetches data (implied read-only) and uses the active MCP wallet as a fallback, but lacks details on permissions required, rate limits, pagination behavior (despite itemsPerPage parameter), error handling, or response format. For a tool with no annotations, this leaves significant gaps in understanding its 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, efficient sentence that front-loads the core purpose and includes essential usage guidance without redundancy. Every word earns its place, making it appropriately sized and well-structured for quick comprehension.

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 (fetching positions across markets with pagination), lack of annotations, and no output schema, the description is incomplete. It does not explain what 'YES/NO token positions' entail, how pagination works with itemsPerPage, the structure of returned data, or potential errors, leaving the agent with insufficient context for reliable 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 100%, so the schema already documents all parameters (walletAddress, network, itemsPerPage) with descriptions and defaults. The description adds marginal value by clarifying walletAddress behavior (uses active MCP wallet if omitted), but does not provide additional syntax, format details, or constraints beyond what the schema provides, meeting the baseline for high coverage.

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 verb ('Fetch') and resource ('YES/NO token positions for a wallet across all Alpha Arcade markets'), making the purpose specific. It distinguishes from siblings like alpha_get_open_orders (which fetches orders, not positions) and alpha_get_market (which fetches market data, not wallet positions), providing clear differentiation.

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

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

The description provides clear context on when to use this tool: to fetch token positions for a wallet across Alpha Arcade markets, with guidance on walletAddress parameter usage (uses active MCP wallet if omitted). However, it does not explicitly state when not to use it or name alternatives (e.g., alpha_get_open_orders for orders instead of positions), which prevents a score of 5.

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

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

No annotations are provided, so the description carries the full burden. It discloses the authentication requirement (ALPHA_API_KEY) and hints at pagination through the parameter 'itemsPerPage', but lacks details on rate limits, error handling, or what happens if the key is missing. It adds some behavioral context but is incomplete for a tool with no annotations.

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 and efficiently structured in two sentences: the first states the purpose and key differentiator, the second adds authentication requirement. Every sentence earns its place with no wasted words, making it appropriately sized and clear.

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 no output schema, the description provides purpose, authentication, and sibling comparison, but lacks details on return values, error cases, or operational constraints. It is adequate for a read-only tool with simple parameters but could be more complete to fully guide an agent without structured data.

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

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

Schema description coverage is 100%, so the schema already documents both parameters (network with enum and default, itemsPerPage with default). The description does not add any parameter-specific semantics beyond what the schema provides, such as explaining network implications or pagination behavior, meeting the baseline for high schema coverage.

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 verb ('Fetch') and resource ('Alpha Arcade markets with liquidity rewards'), specifying the exact data returned (totalRewards, rewardsPaidOut, etc.). It explicitly distinguishes from sibling 'alpha_get_live_markets' by noting the same shape but with added reward info, making the purpose specific and differentiated.

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

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

The description provides clear context by mentioning the requirement for ALPHA_API_KEY and comparing to alpha_get_live_markets, which helps guide usage. However, it does not explicitly state when to use this tool versus alternatives like alpha_get_market or other market-related tools, missing explicit exclusions or named alternatives beyond the one sibling.

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. While it explains the core merging logic (1 YES + 1 NO = 1 USDC), it doesn't address critical aspects like whether this is a read-only or state-changing operation, authentication requirements, rate limits, error conditions, or what happens after merging. For a financial operation with no annotation coverage, this is inadequate.

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 just two sentences that directly convey the core functionality. Every word earns its place, and the key information is front-loaded. The mathematical relationship (1 YES + 1 NO = 1 USDC) is efficiently communicated.

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 financial merging operation with no annotations and no output schema, the description is incomplete. It doesn't explain what the tool returns, error conditions, side effects, or integration with the broader Alpha Arcade system. The presence of sibling tools like 'alpha_split_shares' suggests this is part of a token management system that needs more contextual explanation.

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

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

Schema description coverage is 100%, so the schema already documents all parameters thoroughly. The description adds no additional parameter context beyond what's in the schema. It doesn't explain how 'amount' relates to the YES/NO token pairing or provide examples of typical 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 specific action ('Merge'), the resources involved ('equal YES and NO outcome tokens'), the target ('back into USDC'), and the platform ('on Alpha Arcade'). It also distinguishes from its sibling 'alpha_split_shares' by describing the opposite operation.

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 doesn't mention prerequisites, timing considerations, or compare it to other tools like 'alpha_claim' or 'alpha_get_positions' that might be relevant in similar contexts.

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

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

No annotations are provided, so the description carries the full burden of behavioral disclosure. It mentions 'Propose a match,' which implies a transactional or write operation, but doesn't clarify if this is a read-only proposal, requires authentication, involves on-chain transactions, or has side effects like escrow interactions. Critical behavioral traits like permissions, reversibility, or network implications are missing.

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 directly states the tool's purpose without unnecessary words. It's front-loaded with the core action, making it easy to grasp quickly. However, it could be slightly more structured by including key usage notes, but it avoids redundancy.

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

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

Given the complexity of a financial transaction tool with no annotations and no output schema, the description is insufficient. It lacks details on what the tool returns (e.g., transaction ID, status), error conditions, or how it integrates with the broader Alpha Arcade system. For a tool that likely involves significant on-chain operations, more context is needed to ensure safe and correct 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?

Schema description coverage is 100%, meaning all parameters are documented in the schema itself. The description doesn't add any additional meaning or context for the parameters beyond what the schema provides (e.g., it doesn't explain relationships between 'marketAppId' and 'makerEscrowAppId'). Baseline score of 3 is appropriate as the schema handles parameter documentation adequately.

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 action ('Propose a match') and identifies the resources involved ('existing maker order' and 'your wallet as taker'), providing a specific verb+resource combination. However, it doesn't explicitly differentiate from sibling tools like 'alpha_create_limit_order' or 'alpha_create_market_order', which might also involve order matching in different contexts.

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 minimal guidance, stating only that it's for proposing a match as a taker. It doesn't specify when to use this tool versus alternatives (e.g., when to propose vs. create an order directly), nor does it mention prerequisites like needing an existing maker order or wallet setup. No explicit exclusions or context for usage 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 carries the full burden of behavioral disclosure. It states the tool performs a split operation but omits critical details: whether this is a transaction requiring signing/broadcasting, if it modifies on-chain state, what permissions or balances are needed, potential costs (e.g., transaction fees), or error conditions. The description lacks behavioral context beyond the basic action.

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—two sentences with zero wasted words. The first sentence states the core action and context, and the second provides essential unit conversion. It is front-loaded and efficiently communicates the tool's essence without redundancy.

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

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

Given the tool's complexity (a financial operation on a blockchain), lack of annotations, and no output schema, the description is incomplete. It fails to address behavioral aspects like transaction finality, error handling, or return values. For a tool that likely involves on-chain state changes, more context is needed to guide safe and 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 100%, so the schema fully documents all parameters. The description adds marginal value by clarifying the 'amount' parameter's unit conversion (1 USDC = 1,000,000 microunits) and implying 'marketAppId' relates to Alpha Arcade, but it does not explain parameter interactions or provide usage examples. This meets the baseline for high schema coverage.

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 specific action ('Split USDC into equal YES and NO outcome tokens'), identifies the resource ('on Alpha Arcade'), and distinguishes it from sibling tools like 'alpha_merge_shares' (which performs the opposite operation) and other Alpha Arcade tools that handle orders, markets, or claims. It provides a concrete conversion ratio that reinforces the purpose.

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

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

The description provides no guidance on when to use this tool versus alternatives. It does not mention prerequisites (e.g., needing USDC balance), compare it to 'alpha_merge_shares' (the inverse operation), or indicate typical use cases (e.g., preparing for prediction markets). Without such context, an agent must infer usage from the purpose 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?

No annotations are provided, so the description carries full burden. It states it's a read operation ('Get'), implying non-destructive behavior, but doesn't disclose any behavioral traits like authentication needs, rate limits, error conditions, or what the output contains. For a tool with no annotations, this leaves significant gaps in understanding how it behaves.

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 with zero wasted words. It's front-loaded with the core purpose and appropriately sized for a straightforward query 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 moderate complexity (4 parameters, no output schema, no annotations), the description is minimally adequate. It states what the tool does but lacks behavioral details, usage context, and output information. With no annotations to compensate, it's incomplete for safe and effective use by 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 100%, so the schema fully documents all parameters (address, appId, network, itemsPerPage). The description adds no additional meaning beyond the schema, such as explaining relationships between parameters or usage nuances. Baseline 3 is appropriate when the schema does all the work.

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 action ('Get') and target ('account-specific application information from algod'), making the purpose understandable. It distinguishes itself from siblings like 'api_algod_get_account_info' by specifying 'application' focus, though it doesn't explicitly contrast with similar tools like 'api_indexer_lookup_account_app_local_states'.

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 many sibling tools available for querying account and application data (e.g., 'api_indexer_lookup_account_app_local_states', 'api_algod_get_application_by_id'), the description lacks any context about use cases, prerequisites, or comparisons.

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

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

No annotations are provided, so the description carries the full burden of behavioral disclosure. While 'Get' implies a read-only operation, the description doesn't mention authentication requirements, rate limits, error conditions, response format, or whether this is a paginated endpoint (despite the 'itemsPerPage' parameter suggesting pagination). This leaves significant behavioral gaps.

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

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

The description is a single, efficient sentence with zero wasted words. It's appropriately sized for a tool with good schema documentation and gets straight to the point without unnecessary elaboration.

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 annotations, and no output schema, the description is insufficient. It doesn't explain what 'account-specific asset information' includes, how results are structured, whether pagination applies, or any error scenarios. Given the complexity of Algorand asset data and the lack of structured metadata, the description should provide more context about what information 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?

The schema description coverage is 100%, so all parameters are documented in the schema. The description adds no additional parameter information beyond what's already in the schema descriptions. This meets the baseline expectation when schema coverage is complete.

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 verb ('Get') and resource ('account-specific asset information from algod'), making the purpose understandable. However, it doesn't differentiate this tool from similar sibling tools like 'api_algod_get_account_info' or 'api_indexer_lookup_account_assets', which appear to serve related functions.

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. With many sibling tools related to accounts, assets, and algod/indexer APIs, there's no indication of when this specific tool is appropriate versus others like 'api_algod_get_asset_by_id' or 'api_indexer_lookup_account_assets'.

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 mentions the data returned but doesn't disclose behavioral traits like whether it's a read-only operation, potential rate limits, network latency, error conditions, or pagination handling (implied by 'itemsPerPage' parameter). For a tool with no annotation coverage, this leaves significant gaps.

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

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

The description is a single, efficient sentence with zero wasted words. It front-loads the core purpose and resource, making it immediately understandable without unnecessary elaboration.

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 moderate complexity (3 parameters, no output schema, no annotations), the description is minimally adequate. It states what data is returned but lacks context on behavioral aspects, error handling, or output structure. With no output schema, the description should ideally hint at return format, but it doesn't, leaving gaps in 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?

Schema description coverage is 100%, so the schema fully documents all three parameters. The description adds no additional parameter semantics beyond what's in the schema (e.g., format of 'address', meaning of 'network' options, how 'itemsPerPage' affects output). Baseline 3 is appropriate when the schema does the heavy lifting.

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 action ('Get') and the specific data returned ('current account balance, assets, and auth address'), with the resource being an Algorand account via the algod API. It distinguishes from siblings like 'api_algod_get_account_application_info' by focusing on general account info rather than application-specific data, but doesn't explicitly contrast with all similar 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 many sibling tools for account-related queries (e.g., 'api_indexer_lookup_account_by_id', 'api_indexer_lookup_account_assets'), the description lacks context on selection criteria, prerequisites, or typical 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 are provided, so the description carries full burden. It states 'Get application box by name', implying a read-only operation, but doesn't disclose behavioral traits such as authentication needs, rate limits, error conditions, or what the return value contains (since no output schema). This leaves significant gaps for a tool with 4 parameters.

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 with zero waste. It's front-loaded and appropriately sized for the tool's complexity, making it easy to parse quickly.

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 (4 parameters, no annotations, no output schema), the description is incomplete. It lacks details on behavioral aspects, return values, and differentiation from siblings. For a tool that likely interacts with Algorand blockchain data, more context is needed to guide 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 100%, so parameters are well-documented in the schema. The description adds no additional meaning beyond implying that 'boxName' is used to retrieve a specific box. With high schema coverage, the baseline score of 3 is appropriate, as the description doesn't compensate but doesn't detract either.

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 'Get application box by name' clearly states the action (get) and resource (application box), but it's vague about what an 'application box' is in the Algorand context and doesn't differentiate from sibling tools like 'api_algod_get_application_boxes' or 'api_indexer_lookup_application_box'. It provides basic purpose but lacks specificity and sibling distinction.

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. With many sibling tools related to applications and boxes (e.g., 'api_algod_get_application_boxes', 'api_indexer_lookup_application_box'), there's no indication of context, prerequisites, or exclusions. Usage is implied only by the tool name.

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

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

With no annotations provided, the description carries full burden but only states the action without behavioral details. It doesn't disclose if this is a read-only operation, how it handles pagination (implied by 'itemsPerPage' but not explained), rate limits, authentication needs, or what 'all' means in practice (e.g., completeness guarantees).

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 with zero wasted words. It's front-loaded and appropriately sized for the tool's apparent simplicity, though this conciseness comes at the cost of 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 no annotations, no output schema, and a tool that likely returns complex data (application boxes), the description is incomplete. It doesn't explain what boxes are, the return format, pagination behavior, or error conditions, leaving significant gaps for an agent to use it effectively.

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

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

Schema description coverage is 100%, so parameters are well-documented in the schema itself. The description adds no additional meaning about parameters beyond implying 'appId' is required and 'all boxes' relates to that ID, meeting the baseline for high schema coverage.

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 'Get all application boxes' clearly states the verb ('Get') and resource ('application boxes'), making the purpose understandable. However, it lacks specificity about what 'boxes' are in the Algorand context and doesn't distinguish from sibling tools like 'api_algod_get_application_box' (singular) or 'api_indexer_lookup_application_boxes'.

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

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

No guidance is provided on when to use this tool versus alternatives. The description doesn't mention prerequisites, appropriate contexts, or comparisons to similar tools in the extensive sibling list, leaving the agent without 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?

No annotations are provided, so the description carries the full burden of behavioral disclosure. It states this is a 'get' operation, implying read-only behavior, but doesn't mention any constraints like rate limits, authentication requirements, or what happens if the application ID doesn't exist. For a tool with no annotation coverage, this leaves significant gaps in understanding its 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, efficient sentence with zero wasted words. It's appropriately sized for a simple retrieval tool and front-loads the core purpose immediately.

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 (a read operation with 3 parameters) and no annotations or output schema, the description is incomplete. It doesn't explain what 'application information' entails, potential errors, or behavioral traits like pagination details. For a tool with no structured output documentation, the description should provide more context to be fully helpful.

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

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

The schema description coverage is 100%, so the schema fully documents all three parameters (appId, network, itemsPerPage). The description adds no additional meaning beyond what the schema provides, such as explaining what 'application information' includes or how pagination works. Baseline 3 is appropriate when the schema does all the work.

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 'Get application information' clearly states the action (get) and resource (application information), but it's vague about what specific information is retrieved. It doesn't distinguish this tool from sibling tools like 'api_algod_get_application_box' or 'api_indexer_lookup_applications', which also retrieve application-related 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?

No guidance is provided on when to use this tool versus alternatives. With many sibling tools dealing with applications (e.g., 'api_algod_get_application_box', 'api_indexer_lookup_applications'), the description fails to indicate this tool's specific context or prerequisites, leaving the agent to guess based on the tool 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?

No annotations are provided, so the description carries full burden. It mentions 'Get' which implies a read operation, but doesn't disclose behavioral traits like authentication requirements, rate limits, error handling, or what 'current' means (e.g., real-time vs. cached). The description is minimal and lacks necessary context 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 a single, efficient sentence with no wasted words. It's front-loaded with the core purpose, though it could be more structured by including key details. It earns a 4 for being concise but loses a point for lacking depth.

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 (3 parameters, no output schema, no annotations), the description is incomplete. It doesn't explain what information is returned, how errors are handled, or prerequisites for use. For a tool that likely interacts with a blockchain network, more context is needed 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 100%, so parameters are fully documented in the schema. The description adds no additional meaning beyond the schema, such as explaining what an 'assetId' represents or how 'itemsPerPage' affects pagination. Baseline 3 is appropriate since the schema does the heavy lifting.

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 action ('Get') and resource ('current asset information'), but is vague about what 'current asset information' entails. It doesn't distinguish from sibling tools like 'api_indexer_lookup_asset_by_id' or 'api_algod_get_account_asset_info', leaving ambiguity about which tool to use for asset queries.

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 is provided. With multiple asset-related tools in the sibling list (e.g., api_indexer_lookup_asset_by_id, api_algod_get_account_asset_info), the description offers no context for selection, leaving the agent to infer based on names 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?

No annotations are provided, so the description carries the full burden of behavioral disclosure. 'Get current node status' implies a read-only operation, but the description doesn't specify authentication requirements, rate limits, error conditions, or what 'node status' actually includes (health metrics, version info, network connectivity, etc.). For an API tool with zero annotation coverage, this is a significant gap in 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 concise at just three words ('Get current node status'), with zero wasted language. It's front-loaded with the core purpose. While it may be too brief for completeness, as a standalone statement it's efficiently 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?

Given the complexity of an API tool with no annotations, no output schema, and multiple sibling tools, the description is insufficiently complete. It doesn't explain what 'node status' returns, how it differs from the 'after_block' variant, what authentication might be needed, or typical use cases. The 100% schema coverage helps with parameters, but the overall context for proper tool selection and invocation is lacking.

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 mentions no parameters at all, while the schema documents two optional parameters with 100% coverage (network with enum values and itemsPerPage with default). Since schema_description_coverage is 100%, the baseline score is 3 even without parameter information in the description. The description adds no value beyond what the schema already provides about parameters.

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

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

The description 'Get current node status' clearly states the verb ('Get') and resource ('current node status'), making the basic purpose understandable. However, it doesn't distinguish this tool from its sibling 'api_algod_get_node_status_after_block', which appears to be a similar status-checking tool with different timing. The description is adequate but lacks sibling differentiation.

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

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

The description provides no guidance on when to use this tool versus alternatives. With many sibling tools available (including 'api_algod_get_node_status_after_block' and various other API tools), there's no indication of when this specific node status check is appropriate versus other status or information retrieval tools. No prerequisites, exclusions, or alternatives are mentioned.

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

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

No annotations are provided, so the description carries full burden. It states it's a read operation ('Get'), but doesn't disclose behavioral traits like rate limits, authentication needs, error conditions, or what 'node status' entails (e.g., health, metrics). For a tool with no annotations, this is a significant gap in transparency about how it behaves and what to expect.

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 with zero waste. It's front-loaded with the core action and condition, making it easy to parse. Every word earns its place, and there's no redundant or verbose language.

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 no output schema, the description is minimal. It states the purpose but lacks context on behavior, output format, or usage relative to siblings. For a tool with 3 parameters and no structured metadata, it's adequate as a basic descriptor but incomplete for guiding an agent effectively without additional inference.

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

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

Schema description coverage is 100%, so the schema fully documents parameters (round, network, itemsPerPage). The description adds no additional meaning beyond implying the 'round' parameter's purpose. With high schema coverage, the baseline is 3, as the description doesn't compensate but doesn't detract either.

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 'Get node status after a specific round' clearly states the action (get) and resource (node status) with a specific condition (after a specific round). It distinguishes from the sibling tool 'api_algod_get_node_status' by specifying the temporal condition, though it doesn't explicitly contrast them. The purpose is unambiguous but could be more explicit about 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 like 'api_algod_get_node_status' or other status-related tools. The description implies usage for post-round status but offers no context about prerequisites, typical use cases, or exclusions. This leaves 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?

No annotations are provided, so the description carries full burden. It states 'Get pending transaction information' which implies a read-only operation, but doesn't disclose any behavioral traits like authentication requirements, rate limits, error conditions, or what 'pending' specifically means in this context. The description is minimal and lacks operational 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 at just four words, with zero wasted language. It's front-loaded with the core purpose. While it may be too brief for completeness, it earns full marks 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 complexity of transaction lookup in a blockchain context, no annotations, and no output schema, the description is inadequate. It doesn't explain what 'pending transaction information' includes, how it differs from other transaction tools, or what the return format looks like. For a tool with one required parameter and two optional ones in a specialized domain, more context 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 100%, so the schema fully documents all three parameters (txId, network, itemsPerPage). The description doesn't add any parameter-specific context beyond what's in the schema. The baseline score of 3 reflects adequate parameter documentation through the 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 'Get pending transaction information' clearly states the action (get) and resource (pending transaction information), but it's quite generic. It doesn't specify what kind of information is retrieved or differentiate meaningfully from sibling tools like 'api_algod_get_pending_transactions' (plural) or 'api_indexer_lookup_transaction_by_id'.

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 many sibling tools for transaction lookup (e.g., api_algod_get_pending_transactions, api_indexer_lookup_transaction_by_id), the description offers no context about whether this is for pending vs. confirmed transactions, Algod vs. Indexer APIs, or single vs. batch queries.

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 states 'Get all pending transactions', implying a read-only operation, but doesn't disclose behavioral traits like whether it's paginated (hinted by 'itemsPerPage' in schema but not described), rate limits, authentication needs, or what 'all' entails (e.g., network-wide). This leaves significant gaps for a tool with parameters.

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 with zero waste—'Get all pending transactions'—front-loading the core action and resource. It's appropriately sized for a simple tool, though its brevity contributes to gaps in other dimensions.

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 no output schema, the description is incomplete. It doesn't explain return values (e.g., transaction format, pagination details), behavioral context (e.g., network defaults, error handling), or usage relative to siblings. For a tool with parameters and complex sibling relationships, this leaves the agent under-informed.

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

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

Schema description coverage is 100%, so the schema fully documents parameters like 'maxTxns', 'network', and 'itemsPerPage'. The description adds no additional meaning beyond implying retrieval of transactions, which is already clear from the tool name and schema. This meets the baseline for high schema coverage.

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 verb 'Get' and resource 'all pending transactions', making the purpose specific and understandable. However, it doesn't differentiate from sibling tools like 'api_algod_get_pending_transaction' (singular) or 'api_algod_get_pending_transactions_by_address', leaving room for ambiguity about scope.

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 siblings like 'api_algod_get_pending_transaction' (singular) and 'api_algod_get_pending_transactions_by_address', the description lacks context on whether this tool is for bulk retrieval, unfiltered access, or specific use cases, offering no help in 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 provided, the description carries full burden but offers minimal behavioral insight. It doesn't disclose whether this is a read-only operation (implied by 'Get'), potential rate limits, authentication requirements, pagination behavior (despite 'itemsPerPage' in schema), or what happens with invalid addresses. The description adds little beyond the basic action.

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 zero wasted words. It's front-loaded with the core action and resource, making it immediately scannable and 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?

For a tool with 3 parameters, no annotations, and no output schema, the description is insufficient. It doesn't cover behavioral aspects like error handling, response format, or pagination details. Given the complexity of blockchain transactions and sibling tools, more context is needed to guide 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 100%, so parameters are fully documented in the schema. The description doesn't add any semantic context beyond implying an address is needed. It doesn't explain parameter interactions (e.g., how network affects results) or provide examples, but the schema adequately covers basics, meeting the baseline.

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 verb ('Get') and resource ('pending transactions for an address'), making the purpose immediately understandable. However, it doesn't differentiate from sibling tools like 'api_algod_get_pending_transactions' (which likely gets all pending transactions) or 'api_indexer_lookup_account_transactions' (which might include confirmed transactions), missing explicit sibling distinction.

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

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

No guidance is provided on when to use this tool versus alternatives. The description doesn't mention prerequisites (e.g., whether the address must be valid or on a specific network), nor does it compare to similar tools like 'api_algod_get_pending_transactions' or transaction lookup tools in the indexer API.

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 states 'Get', implying a read-only operation, but doesn't disclose behavioral traits like rate limits, authentication needs, error conditions, or what 'suggested transaction parameters' entails (e.g., fee estimates, validity rounds). This is inadequate for a tool with zero annotation coverage.

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 with zero waste. It's front-loaded with the core purpose and appropriately sized for a simple retrieval 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 no annotations and no output schema, the description is incomplete. It doesn't explain what 'suggested transaction parameters' includes (e.g., first/last round, fee), potential errors, or typical use cases. For a tool in a complex Algorand ecosystem, this leaves significant gaps 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 100%, so the schema fully documents both parameters (network with enum, itemsPerPage with default). The description adds no parameter-specific information beyond what's in the schema, such as explaining why these parameters are relevant. Baseline 3 is appropriate when schema does the heavy lifting.

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 verb 'Get' and the resource 'suggested transaction parameters', making the purpose understandable. However, it doesn't differentiate from sibling tools like 'api_algod_get_account_info' or 'api_algod_get_pending_transactions', which also retrieve information from the Algorand network. The description is specific but lacks sibling distinction.

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 doesn't mention prerequisites, context (e.g., before submitting a transaction), or related tools. With many sibling tools for Algorand operations, this omission leaves the agent without 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 provided, the description carries the full burden of behavioral disclosure. It effectively describes key behaviors: it's an atomic transaction group that signs and submits using the active wallet account, and it confirms the swap. However, it lacks details on permissions needed, rate limits, error handling, or what 'confirm' entails (e.g., wait for blockchain confirmation).

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 appropriately sized and front-loaded, starting with the core purpose and key details. Both sentences earn their place: the first defines the tool's scope and process, and the second clarifies amount units. There is no wasted text, though it could be slightly more structured for readability.

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 (10 parameters, no output schema, no annotations), the description is moderately complete. It covers the high-level process and unit clarification but lacks details on output format, error cases, or confirmation specifics. For a tool that executes financial transactions, more behavioral context would be beneficial to fully guide 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 100%, so the schema already documents all 10 parameters thoroughly. The description adds minimal value beyond the schema, only reiterating that amounts are in base units and mentioning the all-in-one process, which doesn't provide additional parameter semantics. Baseline 3 is appropriate when the schema does the heavy lifting.

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 with specific verbs ('execute an optimized token swap') and resources ('via Haystack Router across multiple DEXes and LST protocols'). It distinguishes itself from sibling tools like api_haystack_get_swap_quote by emphasizing the all-in-one nature: 'quote → sign → submit → confirm'.

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

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

The description provides clear context for when to use this tool ('all-in-one tool: quote → sign → submit → confirm'), implying it should be used for complete swap execution rather than just quoting. However, it does not explicitly state when not to use it or name specific alternatives, though the sibling list includes quoting tools like api_haystack_get_swap_quote.

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

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

With no annotations provided, the description carries the full burden and does well by disclosing key behavioral traits: it's a read-only preview operation (not execution), mentions the DEX aggregator functionality, specifies base units for amounts, and describes the return content. It could improve by mentioning rate limits or error conditions.

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?

Perfectly concise and well-structured: three sentences that each earn their place (purpose, return details, usage guidance). No wasted words, and key information is 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?

For a read-only quote tool with 9 parameters and no output schema, the description provides good context about what the tool does and when to use it. It could be more complete by briefly mentioning the return format or potential limitations, but it's largely adequate given 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?

Schema description coverage is 100%, so the schema already documents all parameters thoroughly. The description adds some context about base units and the preview purpose, but doesn't provide additional parameter semantics beyond what's in the schema. Baseline 3 is appropriate when schema does the heavy lifting.

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 with specific verbs ('Get an optimized swap quote') and resources ('from Haystack Router'), and distinguishes it from siblings by specifying it's for previewing swaps before execution, unlike execution tools like api_haystack_execute_swap.

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 states when to use this tool ('Use this to preview a swap before executing'), providing clear context and distinguishing it from execution alternatives. It also mentions the tool's role in the swap workflow.

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

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

With no annotations provided, the description carries the full burden of behavioral disclosure. It effectively describes the tool's behavior: it returns a boolean (true/false) indicating opt-in necessity, specifies that it always returns false for ALGO (ASA 0), and clarifies its read-only nature through the 'check' verb. However, it doesn't mention potential errors, rate limits, or authentication requirements, which are minor gaps.

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

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

The description is front-loaded with the core purpose in the first sentence, followed by specific behavioral details and usage guidance. Every sentence earns its place by adding critical information without redundancy, making it highly efficient and well-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?

Given the tool's moderate complexity (4 parameters, no output schema, no annotations), the description is largely complete. It explains the tool's purpose, behavior, and usage context effectively. However, it doesn't detail the return format beyond 'true/false' or address potential edge cases, leaving minor gaps in full contextual 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 input schema has 100% description coverage, so the schema already documents all parameters thoroughly. The description adds no additional parameter semantics beyond what the schema provides, such as explaining the relationship between 'address' and 'assetId' or clarifying 'itemsPerPage' usage. This meets the baseline for high schema coverage.

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 with a specific verb ('Check'), resource ('Algorand address'), and condition ('needs to opt into an asset before swapping'). It distinguishes itself from siblings like 'wallet_optin_asset' by focusing on pre-swap verification rather than performing the opt-in action.

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 explicit usage guidance: 'Use before executing a swap to determine if wallet_optin_asset should be called first.' It names the alternative tool ('wallet_optin_asset') and specifies when to use it, offering clear context for decision-making.

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. While 'Get' implies a read-only operation, the description doesn't address important behavioral aspects: whether this requires authentication, rate limits, pagination behavior (despite the 'itemsPerPage' parameter), error conditions, or what format the 'local states' data returns. For a tool with no annotation coverage, this leaves significant gaps.

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

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

The description is maximally concise - a single clear sentence with zero wasted words. It's front-loaded with the essential purpose and contains no unnecessary elaboration. This is an excellent example of efficient communication within the constraints of minimal 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?

For a tool with no annotations and no output schema, the description is insufficiently complete. It doesn't explain what 'account application local states' are conceptually, what data format to expect, whether results are paginated (implied by itemsPerPage but not stated), or any behavioral constraints. Given the complexity of blockchain data retrieval and the lack of structured metadata, the description should provide more contextual information.

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

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

Schema description coverage is 100%, so the schema already fully documents all three parameters (address, network, itemsPerPage). The description adds no additional parameter semantics beyond what's in the schema - it doesn't explain what 'account application local states' are, how they relate to the address parameter, or provide context for the network selection. Baseline 3 is appropriate when the schema does all the parameter documentation work.

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 action ('Get') and resource ('account application local states'), making the purpose immediately understandable. However, it doesn't differentiate this tool from similar sibling tools like 'api_indexer_lookup_account_assets' or 'api_indexer_lookup_account_created_applications' - all appear to retrieve different types of account-related data without clear distinction in the description.

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

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

The description provides no guidance on when to use this tool versus alternatives. With many similar 'api_indexer_lookup_account_*' tools available, there's no indication of what distinguishes 'local states' from 'assets', 'created applications', or other account data retrievals. No prerequisites, timing considerations, or alternative suggestions 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 carries full burden. 'Get account assets' implies a read-only operation but doesn't disclose any behavioral traits: no mention of pagination behavior (implied by 'nextToken' and 'itemsPerPage'), rate limits, authentication requirements, error conditions, or what constitutes an 'asset' in the response. This leaves critical gaps for an agent.

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 three words, with zero wasted text. It's front-loaded with the core action, though this brevity comes at the cost of clarity and 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 complexity (6 parameters, no annotations, no output schema), the description is inadequate. It doesn't explain the tool's role in the Algorand ecosystem, what 'assets' refers to, pagination behavior, or error handling. For a lookup tool with multiple parameters and sibling overlaps, more context is needed to guide 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 100%, so the schema fully documents all 6 parameters. The description adds no meaning beyond what the schema provides—it doesn't explain relationships between parameters (e.g., how 'limit' interacts with 'itemsPerPage') or provide examples. Baseline 3 is appropriate when the schema does all the work.

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 'Get account assets' is a tautology that essentially restates the tool name 'api_indexer_lookup_account_assets'. While it indicates a read operation on assets for an account, it lacks specificity about what 'assets' means in this context (e.g., Algorand Standard Assets) and doesn't distinguish it from sibling tools like 'api_indexer_lookup_asset_balances' or 'wallet_get_assets'.

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. With many sibling tools dealing with assets, accounts, and lookups, there's no indication of context, prerequisites, or distinctions from tools like 'api_indexer_lookup_asset_balances' or 'api_algod_get_account_asset_info'.

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. While 'Get' implies a read-only operation, it doesn't specify whether this is a simple lookup or involves pagination (though the 'itemsPerPage' parameter hints at pagination). It doesn't mention rate limits, authentication requirements, error conditions, or what happens with invalid addresses. The description adds minimal behavioral context beyond the basic 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 a single, efficient sentence with no wasted words. It's front-loaded with the core purpose. However, given the complexity of the tool and lack of annotations, it could benefit from additional context to improve completeness without sacrificing 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 3 parameters, no annotations, and no output schema, the description is inadequate. It doesn't explain what 'account information' includes, how pagination works, or differences from sibling tools. The agent lacks sufficient context to use this tool effectively compared to alternatives, especially given the rich ecosystem of account-related tools on this server.

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

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

Schema description coverage is 100%, so the schema fully documents all three parameters. The description doesn't add any parameter semantics beyond what's already in the schema—it doesn't explain address format, network implications, or pagination behavior. This meets the baseline for high schema coverage but doesn't provide extra value.

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

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

The description 'Get account information from indexer' clearly states the verb ('Get') and resource ('account information'), but it's vague about what specific information is retrieved. It doesn't distinguish this tool from sibling tools like 'api_algod_get_account_info' or 'api_indexer_search_for_accounts', leaving ambiguity about when to use this particular lookup method.

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 about when to use this tool versus alternatives. With many sibling tools that also retrieve account information (e.g., 'api_algod_get_account_info', 'api_indexer_search_for_accounts'), the description offers no context about differences in data source, completeness, or performance. This leaves the agent guessing about the appropriate use case.

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

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

No annotations are provided, so the description carries the full burden of behavioral disclosure. While 'Get' implies a read-only operation, the description doesn't mention pagination behavior (despite the 'itemsPerPage' parameter), rate limits, authentication requirements, or what format the applications are returned in. This leaves significant gaps for a tool that fetches potentially large datasets.

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 gets straight to the point with zero wasted words. It's appropriately sized for a straightforward lookup tool and is perfectly 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?

For a tool with no annotations and no output schema, the description is insufficient. It doesn't explain what 'applications' are in this context (Algorand smart contracts?), what data is returned, or how pagination works despite having an 'itemsPerPage' parameter. The agent would be left guessing about the tool's behavior and output format.

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

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

Schema description coverage is 100%, so the schema already fully documents all three parameters. The description doesn't add any additional meaning about the parameters beyond what's in the schema (e.g., it doesn't clarify what 'applications' means in this context or provide examples). This meets the baseline for high schema coverage.

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 'Get applications created by this account' clearly states the verb ('Get') and resource ('applications created by this account'), making the purpose immediately understandable. However, it doesn't distinguish this tool from similar sibling tools like 'api_indexer_lookup_account_app_local_states' or 'api_indexer_search_for_applications', which prevents a perfect score.

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. With numerous sibling tools that also deal with applications and accounts (e.g., 'api_indexer_lookup_applications', 'api_indexer_search_for_applications'), the agent receives no help in selecting this specific tool for the 'created by' use case.

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

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

No annotations are provided, so the description carries the full burden of behavioral disclosure. It states 'Get account transaction history', which implies a read-only operation, but doesn't mention pagination behavior (implied by 'itemsPerPage' parameter), rate limits, authentication requirements, or what the return format looks like (no output schema). This leaves significant gaps for a tool with 10 parameters.

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 with zero wasted words. It's front-loaded with the core purpose ('Get account transaction history'), making it easy to parse quickly. No structural issues are 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 complexity (10 parameters, no annotations, no output schema), the description is inadequate. It doesn't explain the return format, pagination, error conditions, or how parameters interact (e.g., time vs. round filters). For a data retrieval tool with many filtering options, more context is needed to guide 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 100%, so the schema fully documents all 10 parameters with clear descriptions. The description adds no additional parameter semantics beyond implying transaction history retrieval, which is already covered by the schema. This meets the baseline for high schema coverage.

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 'Get account transaction history' clearly states the verb ('Get') and resource ('account transaction history'), making the purpose understandable. However, it doesn't differentiate from sibling tools like 'api_indexer_lookup_account_by_id' or 'api_indexer_search_for_transactions' that might also retrieve transaction-related data, making it somewhat generic.

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. With many sibling tools available (e.g., 'api_indexer_search_for_transactions', 'api_algod_get_pending_transactions_by_address'), there's no indication of context, prerequisites, or exclusions, leaving the agent to infer usage from the tool 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?

No annotations are provided, so the description carries full burden. It states 'Get' implying a read operation, but doesn't disclose behavioral traits like authentication needs, rate limits, error conditions, or what 'lookup' entails versus 'get'. For a tool with no annotations, this is insufficient to inform 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 a single, efficient sentence with zero waste—'Get application box by name' is front-loaded and appropriately sized for its purpose, earning its place without unnecessary elaboration.

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 no output schema, the description is incomplete. It lacks context on what an 'application box' is, how it differs from similar tools, and what the return value includes. For a lookup tool in a complex ecosystem with many siblings, this leaves significant gaps 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 100%, so parameters are well-documented in the schema. The description adds no additional meaning beyond implying 'boxName' is used for lookup, which is already clear from the schema. Baseline 3 is appropriate as the schema does the heavy lifting.

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 'Get application box by name' clearly states the action (Get) and resource (application box), but it's vague about what an 'application box' is in this context. It doesn't distinguish this tool from its sibling 'api_indexer_lookup_application_boxes' (plural) or 'api_algod_get_application_box', leaving ambiguity about when to use each.

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 multiple similar tools in the sibling list (e.g., 'api_indexer_lookup_application_boxes', 'api_algod_get_application_box'), the description offers no context about differences, prerequisites, or specific use cases, leaving the agent to guess.

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

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

No annotations are provided, so the description carries full burden. 'Get all application boxes' implies a read-only operation, but doesn't disclose behavioral traits like whether it's paginated (hinted by 'itemsPerPage' parameter but not explained), rate limits, authentication needs, or what 'all' means in practice (e.g., across all networks or per network). The description lacks critical context 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 a single, efficient sentence with no wasted words. However, it's overly terse and under-specified for a tool with four parameters and no annotations, missing opportunities to add necessary context. While structurally simple, it prioritizes brevity over 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 complexity (4 parameters, no annotations, no output schema), the description is incomplete. It doesn't explain what 'application boxes' are, the tool's behavior (e.g., pagination, network defaults), or return values. For a lookup tool in a crowded sibling set, more context is needed to guide the agent effectively.

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

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

Schema description coverage is 100%, so parameters are fully documented in the schema. The description adds no meaning beyond the schema—it doesn't explain relationships between parameters (e.g., how 'maxBoxes' interacts with 'itemsPerPage'), default behaviors, or semantic nuances. With high schema coverage, the baseline score of 3 is appropriate as the description doesn't compensate but doesn't detract either.

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 'Get all application boxes' restates the tool name 'api_indexer_lookup_application_boxes' without adding specificity. It uses the verb 'Get' which matches 'lookup', but doesn't clarify what 'application boxes' are or distinguish this from sibling tools like 'api_algod_get_application_boxes' or 'api_indexer_lookup_application_box' (singular). The purpose is tautological rather than informative.

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

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

No guidance is provided on when to use this tool versus alternatives. The description doesn't mention prerequisites, context, or compare it to similar tools like 'api_algod_get_application_boxes' (which might be for different networks or data sources). Without any usage instructions, the agent has no basis for choosing this tool appropriately.

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

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

No annotations are provided, so the description carries the full burden of behavioral disclosure. While 'Get' implies a read-only operation, the description doesn't mention pagination behavior (implied by 'nextToken' parameter), rate limits, authentication requirements, or what format/log level the log messages are returned in. For a tool with 9 parameters and no annotation coverage, this leaves significant behavioral gaps.

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

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

The description is extremely concise at just three words, with zero wasted language. It's front-loaded with the core purpose and contains no unnecessary elaboration. For a simple lookup tool, this level of brevity is 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 the complexity (9 parameters, no output schema, no annotations), the description is insufficiently complete. It doesn't explain what 'application' means in this Algorand context, what format the logs are returned in, whether this is a paginated API, or any error conditions. The agent would need to infer too much from the parameter names alone.

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 100% schema description coverage, all parameters are documented in the schema itself. The description adds no additional parameter semantics beyond what's already in the schema descriptions. This meets the baseline expectation when schema coverage is complete, but doesn't provide extra value like explaining relationships between parameters (e.g., how minRound/maxRound interact).

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 'Get application log messages' clearly states the verb ('Get') and resource ('application log messages'), making the purpose understandable. However, it lacks specificity about what 'application' refers to in this context (Algorand smart contracts) and doesn't distinguish itself from sibling tools like 'api_indexer_lookup_applications' or 'api_indexer_lookup_account_transactions', which also deal with application-related 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. With many sibling tools available for querying application data, transactions, and accounts, there's no indication of whether this is the primary method for accessing logs, when it should be preferred over other lookup tools, or any prerequisites for its 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 full burden. It mentions 'Get' which implies a read operation, but doesn't disclose behavioral traits like rate limits, authentication needs, pagination behavior (hinted by 'itemsPerPage' parameter), or what happens if the appId doesn't exist. This is inadequate for a tool with no annotation coverage.

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 with zero wasted words. It's appropriately sized and front-loaded, making it easy to parse quickly.

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 no output schema, the description is incomplete. It doesn't explain what 'application information' includes, how pagination works with 'itemsPerPage', or what the return format looks like. For a tool with 3 parameters and complex sibling context, this leaves significant gaps 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 100%, so the schema fully documents all three parameters (appId, network, itemsPerPage). The description adds no additional meaning beyond what's in the schema, such as explaining the relationship between parameters or typical usage patterns. Baseline 3 is appropriate when schema does all the work.

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 'Get application information from indexer' states the verb ('Get') and resource ('application information'), but it's vague about what specific information is retrieved. It doesn't distinguish from sibling tools like 'api_indexer_search_for_applications' or 'api_algod_get_application_by_id', leaving the scope unclear.

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 many sibling tools that also deal with applications (e.g., 'api_indexer_search_for_applications', 'api_algod_get_application_by_id'), the description offers no context about prerequisites, use cases, 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 are provided, so the description carries the full burden of behavioral disclosure. It mentions 'Get,' implying a read-only operation, but does not specify pagination behavior (beyond parameters like 'limit' and 'nextToken'), rate limits, authentication needs, or error handling. For a tool with 8 parameters and no annotations, this is insufficient to inform an agent adequately.

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: 'Get accounts holding this asset and their balances.' It is front-loaded with the core purpose, has zero wasted words, and is appropriately sized for the tool's complexity. Every part of the sentence earns its place by conveying essential 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?

Given the tool's complexity (8 parameters, no output schema, no annotations), the description is incomplete. It lacks details on behavioral traits, usage context, and output format. While the schema covers parameters, the description does not address how results are structured or any operational constraints, making it inadequate for full 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 100%, meaning all parameters are documented in the input schema. The description does not add any semantic details beyond what the schema provides (e.g., it doesn't explain how 'assetId' relates to assets or how filtering works). With high schema coverage, the baseline score is 3, as the description doesn't compensate but doesn't detract either.

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 accounts holding this asset and their balances.' It specifies the verb ('Get'), resource ('accounts holding this asset'), and what information is retrieved ('their balances'). However, it does not explicitly differentiate from sibling tools like 'api_indexer_lookup_account_assets' or 'api_indexer_search_for_accounts,' which might have overlapping functionality, so it falls short of a perfect score.

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. With many sibling tools related to assets and accounts (e.g., 'api_indexer_lookup_account_assets,' 'api_indexer_search_for_accounts'), there is no indication of context, prerequisites, or exclusions. This lack of guidance could lead to confusion in 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 provided, the description carries full burden for behavioral disclosure. While 'Get' implies a read operation, the description doesn't mention important behavioral aspects like whether this is a lookup by exact ID only, what format the response takes, whether it's paginated (despite the itemsPerPage parameter), or any rate limits 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 extremely concise at just 5 words, which is efficient. However, it's arguably too brief given the tool's context among many similar siblings and the lack of annotations - more information would be helpful but isn't provided.

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

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

For a tool with no annotations, no output schema, and operating in a crowded namespace of similar asset tools, the description is inadequate. It doesn't explain what differentiates this from other asset lookup tools, what format the response takes, or provide any context about the 'configuration' aspect mentioned. The agent would struggle to use this tool effectively without trial and error.

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

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

Schema description coverage is 100%, so the schema already documents all three parameters adequately. The description doesn't add any meaningful parameter semantics beyond what's in the schema - it doesn't explain what 'asset information and configuration' includes, how the network parameter affects results, or clarify the relationship between assetId lookup and pagination.

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 'Get asset information and configuration' clearly states the verb ('Get') and resource ('asset information and configuration'), making the purpose understandable. However, it doesn't distinguish this tool from sibling tools like 'api_algod_get_asset_by_id' or 'api_indexer_search_for_assets' - all appear to retrieve asset data, so differentiation is lacking.

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 about when to use this specific tool versus the many other asset-related tools in the sibling list. The description doesn't mention prerequisites, alternatives, or specific use cases that would help an agent choose this tool appropriately among similar options.

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

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

No annotations are provided, so the description carries the full burden of behavioral disclosure. While 'Get' implies a read operation, the description doesn't mention pagination behavior (though 'nextToken' and 'itemsPerPage' parameters suggest it), rate limits, authentication requirements, or what format the returned transactions will have. For a tool with 13 parameters and no annotation coverage, 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.