gateplex

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

No annotations provided, so description carries full burden. It describes a read-only operation but does not explicitly state it is safe or without side effects. Additional disclosure of behavioral traits like auth scope is present (tied to API key) but not comprehensive.

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?

Single sentence, front-loaded with key action and resource, no superfluous words. Efficient 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 low complexity (no parameters, no output schema, no annotations), the description is sufficient. It explains purpose and use case but could hint at return format. Still largely complete for 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?

Input schema has 0 parameters with 100% description coverage. Description adds no parameter info, which is acceptable given no parameters exist. Baseline for 0 parameters is 4.

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 lists active guardrail rules for the Gateplex project tied to the API key, specifying verb 'list', resource 'guardrail rules', and scope. It distinguishes from sibling tools get_feed and log_intercept, which have different 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 implies usage is for self-checking before action, providing clear context. However, it does not explicitly mention when not to use or alternatives, though siblings are distinct enough.

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 disclose behavior. It implies a read operation but does not explicitly state if it's safe or describe side effects, rate limits, or pagination. Only mentions default limit.

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 sentence with no extra words. It efficiently conveys the core action and default, though it could include usage context for 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?

For a simple retrieval tool with one optional parameter and no output schema, the description covers the basic purpose but lacks usage guidance and return format details. It is minimally 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 0%, so the description must compensate. It provides the default value for 'limit' (10) which adds meaning beyond the schema, but does not explain the parameter's role as a maximum count or the range 1-50.

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 'Retrieve' and the resource 'latest intercepts' for the 'Gateplex project', distinguishing it from sibling tools like check_guardrails and log_intercept which serve different purposes.

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 vs alternatives (check_guardrails, log_intercept). The description gives no context for preferred usage 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. The description only states the action ('send an intercept event') and general purpose ('logging, governing, auditing'). It does not disclose behavioral traits such as whether the operation is destructive, authentication requirements, error handling, or side effects. The description is too vague for an agent to understand the full implications of invoking this 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 with two sentences. The first sentence clearly states the core action, and the second sentence immediately provides usage guidance. No unnecessary words or irrelevant details.

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 8 parameters, no output schema, and no annotations, the description is too brief. It does not explain what the tool returns (e.g., success/failure, the created event ID), how to use optional parameters, or provide any examples. The description is insufficient for an agent to understand the full context of this logging tool.

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 63% parameter description coverage, meaning several parameters are already documented in the schema. The tool description does not add any additional information about the parameters; it only provides a high-level purpose. Given the moderate schema coverage, the description should have supplemented parameters with usage context, but it does not.

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 action ('Send an intercept event to the Gateplex API') and specifies the target resource ('intercept event'). It also provides context for when to use it - 'every time an AI agent performs an action that should be logged, governed, or audited' - which differentiates it from sibling tools like check_guardrails and get_feed.

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 explicit positive guidance: 'Use this every time an AI agent performs an action that should be logged, governed, or audited.' It lacks explicit when-not-to-use instructions or alternative tool mentions, but the provided context is clear enough for an AI agent to know when to invoke it.

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