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 mentions what is checked ('credential and agent counts') but lacks details on permissions, rate limits, response format, or whether this is a read-only operation. For a health check tool with zero annotation coverage, this leaves significant gaps in understanding how it behaves.

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, efficient sentence that front-loads the core purpose ('Check the health status of Aegis') and adds specific details ('including credential and agent counts') without waste. Every word earns its place, making it highly concise and well-structured.

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 (0 parameters, no output schema) and lack of annotations, the description is adequate but has clear gaps. It covers the purpose and scope but misses behavioral aspects like response format or usage context. Without annotations or output schema, more detail on what the health check returns would improve completeness.

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 0 parameters, and schema description coverage is 100%, so there are no parameters to document. The description doesn't need to add parameter semantics beyond what the schema provides. A baseline of 4 is appropriate as it avoids redundancy while being complete for a parameterless tool.

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 a specific verb ('Check') and resource ('health status of Aegis'), including what aspects are covered ('credential and agent counts'). It distinguishes itself from siblings like 'aegis_list_services' and 'aegis_proxy_request' by focusing on health monitoring rather than listing or proxying. However, it doesn't explicitly contrast with siblings beyond the implied scope difference.

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 no guidance on when to use this tool versus alternatives. It doesn't mention prerequisites, frequency, or scenarios where health checks are appropriate compared to 'aegis_list_services' (which might list services without health details) or 'aegis_proxy_request' (which might involve active requests). Usage is implied by the purpose but not explicitly stated.

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 of behavioral disclosure. It effectively describes the tool's behavior: it's a read-only operation (implied by 'List'), returns specific non-sensitive data, and explicitly states what is never returned (secrets). It could improve by mentioning potential limitations like rate limits or authentication requirements.

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 perfectly concise with two clear sentences: one stating the action and resource, another detailing the return values and important exclusion. Every word earns its place with zero wasted text.

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 read tool with no output schema, the description provides good context about what data is returned and what isn't. It could be more complete by describing the return format (e.g., list structure) or any behavioral constraints, but it adequately covers the essential information 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?

The tool has 0 parameters with 100% schema description coverage, so the schema already fully documents the lack of inputs. The description appropriately doesn't add parameter information, maintaining focus on the tool's purpose and output behavior.

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 ('List all available services') and resource ('services registered in Aegis'), distinguishing it from siblings like health checks or proxy requests. It specifies what information is returned (service names, auth types, allowed domains) and explicitly excludes secrets.

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 context by stating it returns service metadata, suggesting it's for discovery or auditing purposes. However, it doesn't explicitly state when to use this tool versus alternatives or provide any exclusion criteria, leaving some guidance gaps.

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 of behavioral disclosure. It adds useful context: authentication is handled automatically, credentials are not visible, and it specifies the required inputs (service name and API path). However, it lacks details on error handling, rate limits, response formats, or other behavioral traits like whether it's idempotent or has side effects.

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, with two sentences that directly state the tool's function and key behavior. Every sentence adds value: the first defines the purpose, and the second clarifies authentication handling. There is no wasted text, though it could be slightly more structured for clarity.

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 complexity (6 parameters, no annotations, no output schema), the description is moderately complete. It covers the core purpose and authentication mechanism but lacks details on response handling, error scenarios, or advanced usage. Without annotations or output schema, the agent must rely on the schema for parameter details, leaving gaps in behavioral understanding.

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 minimal semantic value beyond the schema, only mentioning that credentials are injected and specifying the required inputs. It does not elaborate on parameter interactions or usage nuances, meeting the baseline for high schema coverage.

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: 'Make an authenticated API call through Aegis.' It specifies the verb ('Make'), resource ('API call'), and mechanism ('through Aegis'), but does not explicitly differentiate it from its siblings (aegis_health and aegis_list_services), which likely serve different purposes like health checks or listing services.

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 context by mentioning 'authenticated API call' and 'credentials are injected automatically,' suggesting it's for making requests to services registered with Aegis. However, it does not provide explicit guidance on when to use this tool versus its siblings or other alternatives, leaving the agent to infer based on the tool names and descriptions.

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