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

With no annotations, the description bears full burden. It discloses that the tool identifies, categorizes, calculates USD values, and flags unclassifiable tokens. It does not mention performance or error handling but provides sufficient behavioral context for a safe read operation.

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

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

The description is three concise sentences: purpose, capabilities, usage guidance. No redundant or wasted words; every sentence adds value.

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

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

For a tool with one simple parameter and no output schema, the description covers input, capabilities, and usage context adequately. It could mention output format but is sufficient overall.

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

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

Schema coverage is 100% with one parameter 'wallet' having a clear description. The tool description does not add further meaning beyond the schema's parameter description, so baseline score of 3 is appropriate.

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

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

The description clearly states the tool analyzes Solana wallet DeFi positions in depth, listing specific actions (staking, lending, LP tokens, idle assets) and positioning it as the most comprehensive wallet analysis tool, distinguishing it from siblings like get_token_balances and get_sol_balance.

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

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

The description explicitly says to use it when the user wants to understand DeFi exposure, portfolio breakdown, or position details. It implies it's the comprehensive option but does not explicitly exclude or name alternatives for simpler 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 must carry the burden of behavioral disclosure. It describes the return data (current TVL, by chain, category, recent changes) but does not mention error handling (e.g., invalid protocol), data freshness, or whether it requires special permissions. As a read-only query, it is adequately transparent for most scenarios but lacks depth.

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

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

The description is only two sentences, both front-loaded with essential information. Every sentence adds value: the first explains what the tool does, the second explains when to use it. No filler or redundancies.

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

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

Given no output schema, the description provides a reasonable outline of return fields (current TVL, TVL by chain, category, recent changes). It could be more complete by specifying units (e.g., USD) or data freshness, but it covers the key aspects for the agent to understand the tool's output.

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

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

Schema coverage is 100% with a single parameter described as 'Protocol name'. The description adds valuable context by listing examples (kamino, jito, marinade, raydium) and clarifying it is Solana DeFi protocols, which goes beyond the raw schema.

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

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

The description clearly states it returns detailed TVL and metrics for a specific Solana DeFi protocol, listing specific data points (current TVL, by chain, etc.). It distinguishes itself from sibling tools like 'get_top_solana_protocols' which lists multiple protocols, and 'analyze_wallet_defi_positions' which is wallet-specific.

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

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

The description explicitly says 'Use this when the user asks about a specific protocol's health or TVL.' This provides clear context for when to invoke the tool. It does not provide explicit when-not-to-use statements, but the sibling tools cover alternative 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?

With no annotations, the description carries full burden. It discloses output details (parsed transactions, timestamps, token transfers) and notes that USD values are current prices, not historical. This provides good 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 two sentences plus a note—efficient and front-loaded. Every sentence adds value 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?

For a tool with no output schema, the description covers return content well (parsed transactions, descriptions, timestamps, token transfers) and adds a note on USD pricing. It is moderately complete for its complexity.

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

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

Schema coverage is 100%, so baseline is 3. The description adds no additional meaning to the parameters beyond what the schema already provides (wallet address, limit).

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

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

The description clearly states the tool gets recent transaction history for a Solana wallet. It uses specific verbs and resources, and the context of sibling tools (balances, prices) distinguishes its 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 implicitly indicates when to use this tool (for transaction history) versus siblings (balances, prices). While no explicit when-not is given, the context is clear enough for an AI agent to differentiate.

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 describes the return value (balance in SOL and USD value), which is useful. However, it does not disclose any additional behavioral traits such as network dependencies, error conditions, or whether it is read-only.

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

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

The description is concise with two sentences. It is front-loaded with the core function and includes usage guidance. No extraneous words.

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

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

For a simple balance-checking tool with one parameter and no output schema, the description adequately explains what it returns (balance in SOL and USD value). The context signals and sibling tools provide additional orientation. No 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% (the 'wallet' parameter is described as 'Base58 Solana wallet address (32-44 characters)'). The description adds no additional parameter meaning beyond what the schema provides, which is sufficient. Baseline score of 3 applies.

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

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

The description clearly states the tool gets the SOL balance of a Solana wallet and returns balance in SOL and USD value. It explicitly distinguishes from siblings by noting 'Use this when the user asks specifically about SOL balance, not other tokens.'

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 ('when the user asks specifically about SOL balance') and implies when not to use ('not other tokens'). However, it does not explicitly name alternative tools or provide detailed when-not scenarios.

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

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

No annotations are provided, so the description carries full burden. It discloses that the tool returns every SPL token and fields including USD value where available. However, it does not mention error handling (e.g., invalid wallet), potential pagination, or rate limits, which slightly reduces transparency. Still mostly adequate for a simple read tool.

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

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

Two sentences: the first states purpose and scope, the second adds return fields and usage guidance. No fluff, front-loaded with key information. Every part earns its place.

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

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

Given the tool's low complexity (single parameter, no output schema, no annotations), the description covers the essential points: what it does, when to use it, and what it returns. It lacks details on return format or error behavior, but for this straightforward tool, it is sufficient.

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

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

Schema description coverage is 100%, with the 'wallet' parameter already well-described in the schema. The tool description reaffirms the parameter's purpose but does not add new semantic details beyond the tool's overall function. Slight extra value in contextualizing the parameter within the broader task.

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 token holdings for a Solana wallet address'). It lists the return fields (mint address, symbol, name, balance, USD value) and distinguishes itself from siblings like get_sol_balance (SOL only) and get_token_price (specific token price).

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

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

The description explicitly says 'Use this when the user asks what tokens a wallet holds or wants a general overview of wallet contents.' This provides clear usage context and implicitly excludes siblings (e.g., get_sol_balance for SOL, analyze_wallet_defi_positions for DeFi positions).

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

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

With no annotations, the description carries full burden. It discloses that it returns USD price with confidence score, but lacks detail on error handling, rate limits, or data source. For a simple price query, this is adequate but not thorough.

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

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

Two sentences, no unnecessary words. The action is front-loaded and every sentence adds value.

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

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

For a simple tool with one parameter and no output schema, the description covers inputs, action, and return value. It could explicitly mention that output is a mapping from token to price/confidence, but the description is sufficient for an agent to understand the tool's purpose and 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%, so baseline is 3. The description largely repeats the schema's parameter description ('Accepts token symbols or mint addresses'), adding minimal new meaning.

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 current prices'), the resource ('Solana tokens'), and the output ('price in USD with confidence score'). It distinguishes from siblings like 'get_token_balances' which focuses on balances rather than prices.

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

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

The description explicitly states 'Use this for spot price checks', providing direct usage guidance. It does not explicitly list when not to use, but the sibling context makes alternatives clear. Minor improvement would be to mention that for historical prices a different tool is needed.

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

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

No annotations provided, but description is transparent about return data and purpose. For a read-only tool, no further behavioral details are necessary.

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 no redundancy. Each sentence adds value: first defines the tool, second gives usage guidance.

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?

No output schema, but description enumerates returned fields. Tool is simple and well-documented for its purpose.

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 covers both parameters with descriptions. The description adds context by stating the ranking basis (TVL) and output fields, which complements the schema.

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

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

The description clearly states the tool retrieves top Solana DeFi protocols ranked by TVL, specifies the returned fields (name, TVL, category, percentage changes), and distinguishes from siblings like get_protocol_tvl by focusing on overall landscape comparison.

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

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

Explicitly says to use when user asks about overall Solana DeFi landscape or wants to compare protocols. Does not explicitly state when not to use it, but siblings are listed for inference.

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

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

With no annotations, the description must cover behavior. It mentions Markdown support and severity emoji prefix, but omits details like whether the call is synchronous, rate limits, or if the action is idempotent. It adequately indicates this is a write operation but lacks depth.

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

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

Two sentences, front-loaded with the core purpose, no filler. Every sentence adds distinct value: action, usage guidance, prerequisite.

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

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

For a simple 3-param tool with no output schema, the description covers purpose, usage, parameter details, and basic behavior. Missing return value or error info, but that is acceptable given the tool's simplicity.

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

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

Schema coverage is 100%, but the description adds valuable context: chat_id format ('numeric ID or @username') and severity's effect ('affects emoji prefix'). This provides meaning beyond the schema's enum descriptions.

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

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

The description clearly states the action ('Send a formatted message to a Telegram chat') and the resource ('Telegram'). It distinguishes itself from siblings, which are all data retrieval tools, by being a write/notification tool.

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

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

The description explicitly tells when to use the tool ('when the user explicitly asks to send... get an alert, or be notified') and includes a prerequisite ('Requires the user's Telegram chat ID'). It does not list alternatives, but the sibling context makes the usage scope clear.

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