scam-detection

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 explicitly states a key behavioral trait: 'Free — consumes no credits,' which tells the agent this tool has no cost side-effect. It also implies read-only status through 'Check,' which covers the main transparency concern for a usage 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 extremely concise: one sentence plus a short clause. It front-loads the purpose ('Check') and lists the key output dimensions without any filler. Every word contributes 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 zero-parameter, no-output-schema tool, the description is fully complete. It tells the agent exactly what data can be obtained (prepaid credits, monthly usage, expiry), confirms there is no cost, and requires no additional information for correct invocation.

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

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

The tool has zero parameters and an empty input schema, so parameter semantics have no ambiguity. Per the baseline for 0-parameter tools, a score of 4 is appropriate; the description need not add anything 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 uses a specific verb ('Check') and names a precise resource: the API key's remaining prepaid scan credits, monthly plan usage, and credit expiry. This clearly distinguishes get_usage from siblings scan_message and scan_url, which perform scans rather than report usage.

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 implies when to use this tool: when an agent needs to check credit/usage status. It also states it is free and consumes no credits, which is useful guidance for selecting it safely over operations that would consume credits. It does not explicitly name alternatives or exclusions, but the context is sufficient.

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 behavioral burden. It clearly discloses the output shape (verdict, risk score, summary, findings) and an important operational trait: 'Costs 1 scan credit.' It implies a non-mutating analysis action, though it doesn't explicitly state side-effect safety.

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 carry the purpose, usage timing, output contract, and cost with no filler. The primary action and indicators are front-loaded, and every clause 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?

For a one-parameter tool with no output schema and no annotations, the description explains what it does, when to use it, what it returns, and its cost. It is slightly incomplete in not addressing the relationship to scan_url, but the naming and content-type distinction make the gap minor.

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%, and the schema already documents 'message' as the full message text with a character limit. The description adds the type of content ('message, email, or text') and context for what gets analyzed, but does not substantially go beyond the schema's 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?

States a specific verb ('Analyze') and a precise resource ('a message, email, or text') with a clear goal: detecting scam indicators. The listed indicators and returned verdict/risk score make the tool's purpose concrete and distinguishable from scan_url by content type.

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?

Provides a clear usage window: 'before acting on it,' with concrete examples of when to use it (payment requests, verification codes, urgency pressure, impersonation). It does not explicitly contrast with scan_url or state when not to use it, so it stops short of a full 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 expected outputs (verdict, 0-100 risk score, plain-English summary, and specific findings) and a side-effect cost ('Costs 1 scan credit'). It does not mention rate limits or auth, but for a simple scan tool this is solid behavioral disclosure.

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

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

Two sentences: the first states the purpose and returns, the second adds the cost. Every sentence earns its place, with the core purpose front-loaded and no redundant 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 tool with no output schema, the description compensates by enumerating all return fields and the credit cost. An agent can call it correctly and interpret its result without missing critical 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?

The input schema already covers the single 'url' parameter with 100% description coverage and an example format. The description adds no additional parameter semantics, so the baseline 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 opens with a specific verb and resource: 'Check a URL or domain for phishing and scam risk before visiting, clicking, or transacting with it.' It clearly distinguishes this tool from siblings (get_usage, scan_message) by focusing on URL/domain scanning, leaving no ambiguity about the target.

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 usage context: use before visiting, clicking, or transacting. It does not explicitly name alternatives or exclusion conditions, but the trigger scenarios are specific enough to guide an agent's decision without needing comparison to siblings.

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