PreApe

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

With no annotations provided, the description carries the full burden, and it does well: it states the output verdict, the key analysis components, the v1 null fields, and the RadarDEX-only coverage. It does not address potential side effects or permissions, but as a read-only analysis tool the disclosed limitations are meaningful and useful.

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: the first sentence states the purpose and return verdict, followed by efficient notes on scope and limitations. Every sentence earns its place with no redundant or filler content.

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

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

Given the schema covers all parameters and this is a simple analysis tool with no output schema, the description is largely complete: it explains return value, key fields, limitations, and scope. The main gap is not addressing the relationship to preape_check, but that is a usage-guidance nuance rather than a blocking completeness issue.

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 some context by mentioning analysis components like top-holder concentration and liquidity, which loosely connect to includeHolders, but it does not add substantial meaning beyond the schema.

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

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

The description states a specific verb and resource: it performs 'Full pre-trade analysis for an Arc / RadarDEX token before buying' and returns a clear verdict (GO / CAUTION / AVOID). It does not explicitly differentiate from the sibling tool preape_check, so it falls short of a 5, but the purpose is 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 clearly indicates when to use it ('before buying') and notes RadarDEX-only coverage as a scope limitation. However, it never mentions the sibling tool preape_check or explains when to choose this tool over that alternative, leaving the usage guidance incomplete.

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

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

With no annotations, the description carries the full burden and it succeeds: it discloses the output format, the covered checks (creator history, LP lock), and a notable limitation (does not scan full holders). It also implies a read-only nature through 'risk check' and 'before buying.' This is strong transparency despite lacking explicit safety semantics.

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?

Five short, front-loaded sentences, each carrying distinct information: purpose, output, coverage, limitation, and usage. No filler.

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

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

For a single-parameter, no-output-schema tool, the description tells the agent what it returns, what it checks, what it ignores, and when to invoke it. The absence of an output schema is mitigated by the explicit return description.

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

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

Schema coverage is 100%, so the schema already documents the token address. The description repeats the Arc context and adds RadarDEX as a domain reference, but doesn't provide additional parameter-specific details like format or validation rules. 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 states a specific action ('pre-trade risk check'), a target resource ('token on Arc / RadarDEX'), and a concrete output ('GO, CAUTION, AVOID'). It is clear and distinct in scope, but it doesn't explicitly name the sibling preape_analyze, so differentiation relies on the 'Quick' and 'Use this first' cues rather than an explicit contrast.

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 gives clear context: use it before buying and use it first. However, it doesn't explicitly state when to switch to preape_analyze or exclude it, so the alternative is implicit rather than named.

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