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

With no annotations provided, the description carries full burden. It discloses the tool's comprehensive nature and returns a 'go/no-go recommendation', but lacks details on permissions, rate limits, or potential side effects. It adequately describes the core behavior but misses deeper 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 front-loaded with the core purpose in the first sentence, uses two efficient sentences total with zero wasted words, and clearly communicates the tool's value proposition and recommendation status 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 complex 7-parameter tool with no annotations and no output schema, the description is reasonably complete. It explains the tool's integrative nature, when to use it, and the output type ('go/no-go recommendation'), though it could elaborate more on behavioral risks or error handling.

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 baseline is 3. The description adds no specific parameter details beyond what the schema provides, but it contextualizes the inputs as part of a 'comprehensive risk assessment' for DeFi safety checks, which slightly enhances understanding.

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

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

The description clearly states the tool's purpose with specific verbs ('combining contract scanning, transaction simulation, and token checks') and resources ('DeFi interaction'), and distinguishes it from sibling tools by positioning it as the 'recommended all-in-one safety check' that integrates their 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 explicitly states when to use this tool ('before any DeFi interaction') and implies alternatives by naming sibling tools (check_token, scan_contract, simulate_transaction) as components it combines, making it the comprehensive choice over piecemeal approaches.

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 describes what the tool does (detects scam indicators) and its intended use case, but lacks details on behavioral traits such as rate limits, authentication needs, response format, or error handling. The description is informative but incomplete for operational transparency.

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

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

The description is front-loaded with the core purpose in the first sentence and follows with specific use guidance. Both sentences are essential, with no wasted words, making it highly efficient and well-structured for quick understanding.

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 (assessing token safety with scam detection) and lack of annotations and output schema, the description is moderately complete. It covers the purpose and usage well but lacks details on behavioral aspects and output, which are critical for an AI agent to invoke it correctly. It meets minimum viability but has clear gaps in operational 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 (tokenAddress, chainId, holderAddress) with descriptions. The description does not add any parameter-specific semantics beyond what the schema provides, such as explaining the significance of holderAddress in scam detection. Baseline score of 3 is appropriate as the schema handles parameter documentation.

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 ('check', 'detects') and resources ('token'), identifying scam indicators like honeypot mechanics, concentrated holdings, and fake ownership renouncement. It distinguishes from siblings by focusing on token safety assessment rather than general risk assessment, contract scanning, or transaction simulation.

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 when to use this tool: 'before swapping into any unfamiliar token.' This provides clear context for usage and implies alternatives (e.g., not using it for familiar tokens or after swapping). While it doesn't name specific sibling tools, the guidance is direct and actionable.

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 behaviors: it analyzes for specific exploit patterns, returns a risk score and findings, and has a precautionary use case. However, it lacks details on rate limits, authentication needs, or error handling.

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

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

The description is front-loaded with the core purpose, followed by usage guidance, all in two efficient sentences with zero wasted words, 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 tool's complexity (security analysis with 4 parameters) and no output schema, the description is mostly complete, covering purpose, usage, and output types. However, it could benefit from more details on behavioral aspects like performance or limitations to fully compensate for the lack of annotations and output schema.

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

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

Schema description coverage is 100%, so the schema already documents all parameters well. The description adds no additional parameter semantics beyond implying analysis can be done on source, bytecode, or via address, which is already covered in the schema. Baseline 3 is appropriate.

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

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

The description clearly states the tool's purpose with specific verbs ('analyze', 'returns') and resources ('smart contract's source code or bytecode'), distinguishing it from siblings like 'assess_risk' or 'check_token' by focusing on contract analysis for security patterns.

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?

It explicitly states when to use this tool ('BEFORE interacting with any unfamiliar contract'), providing clear context and distinguishing it from alternatives like 'simulate_transaction' by focusing on pre-interaction analysis rather than simulation.

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 does well by disclosing key behavioral traits: it's a simulation (non-destructive), detects specific issues (reverts, abnormal gas usage, red flags), and operates on a forked chain. It doesn't mention rate limits, authentication needs, or detailed output format, but covers essential safety and scope.

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: first defines the tool's purpose and key features, second provides usage guidance. Every phrase adds value, and it's front-loaded with the core functionality.

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 does well by explaining the tool's behavior, safety profile (non-execution), and use case. It could improve by hinting at return values (e.g., simulation results), but for a 5-parameter tool with good schema coverage, it's largely complete.

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

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

Schema description coverage is 100%, so the schema already documents all parameters thoroughly. The description adds no additional parameter semantics beyond implying the simulation context, which aligns with 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 clearly states the specific action ('simulate a transaction'), the resource ('on a forked chain'), and the key distinction from actual execution ('WITHOUT actually executing it'). It differentiates from siblings like 'assess_risk' or 'scan_contract' by focusing on transaction simulation rather than general risk assessment or contract scanning.

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: 'to preview what will happen before sending a real transaction.' This provides clear context for usage versus alternatives, indicating it's for pre-execution testing rather than live operations.

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