UsageMax public observability

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

Annotations already cover read-only and non-destructive behavior. The description adds that the response includes citations and that questions are 'bounded', which provides useful context beyond annotations. It doesn't specify what happens if the query exceeds bounds, but that's a minor gap given the simple 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 a single, well-structured sentence that front-loads the action and purpose without redundancy. Every word adds 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 tool with one parameter and no output schema, the description is mostly adequate, but it leaves 'bounded' undefined and does not describe the expected response format beyond 'cited public resources'. An agent may not know how to phrase questions or what 'bounded' means in practice, so completeness is partial.

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 schema has zero description coverage for the only parameter 'query', and the tool description never mentions the parameter. The agent only knows it's a string with length constraints; the description doesn't clarify that the parameter is the natural-language question or how to phrase it. This is a significant omission for a tool with a single parameter.

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 clear verb ('Ask'), a specific resource ('UsageMax documentation'), and the outcome ('receive cited public resources'). It naturally distinguishes from siblings like leaderboard, network_stats, and public_profile, which are data-retrieval tools rather than Q&A over docs.

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 word 'bounded' implies limits but does not explicitly state when to use this tool over siblings or what falls outside scope. No alternatives are named, so the agent must infer that documentation questions go here while numeric data comes from the sibling tools.

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?

Annotations already indicate readOnlyHint and non-destructive behavior. The description adds useful context: the data is public and capped at 100 rows. It does not describe ordering or pagination, but these are minor for a simple read-only 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?

A single sentence with no filler, front-loaded with the action and resource. Every word 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?

The tool is simple, but the description omits any explanation of the two parameters and the response format. Since there is no output schema and no parameter descriptions, an agent must infer meaning from enum names alone, which is adequate but leaves clear gaps.

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% and the description does not mention metric or period at all. The schema's enum values and defaults are partially self-explanatory, but the description adds no meaning beyond the raw 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 ('Read') and a clear resource ('public UsageMax leaderboard') and adds a concrete bound ('maximum 100 rows'). This clearly distinguishes it from sibling tools like ask_site, network_stats, and public_profile.

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 establishes this tool is for reading the leaderboard, which is the relevant context. It does not explicitly mention alternatives or exclusions, but no close sibling competes with this function, so the guidance is adequate.

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?

Annotations already establish read-only and non-destructive behavior. The description adds value by specifying the data scope ('aggregate public') and the output behavior ('render the optional inline observability view'), going beyond the annotations without contradicting them.

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?

One tight sentence that front-loads the primary action and resource, then adds the output behavior. No filler or redundant restatement of the tool name.

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 no-parameter read-only tool, the description conveys the data scope and output view sufficiently. It could be more complete by clarifying what the observability view contains or how 'optional' is controlled, but these are minor given the simple signature.

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 zero parameters, so schema coverage is vacuously complete and no parameter documentation is needed. The description correctly focuses on behavior rather than inputs, matching the baseline for a no-parameter 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 states a specific action ('Read') and resource ('aggregate public UsageMax network statistics'), making the tool's core function clear. It also mentions rendering an observability view, but it does not explicitly differentiate this from the sibling leaderboard tool.

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?

'Aggregate public' implies this is the tool for high-level network statistics rather than user-specific data, giving some context. However, it never states when to prefer network_stats over siblings like leaderboard or public_profile, so routing guidance is only implicit.

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?

Annotations already cover readOnlyHint and destructiveHint. The description adds useful context by noting the profile must be opt-in public and that aggregate statistics are included. However, it does not disclose return format, error cases, or rate limits, and the annotations carry most of the safety burden.

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?

One short, front-loaded sentence with no filler. It states the action and key scoping constraint efficiently, earning 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?

With no output schema, the description should clarify what the returned 'aggregate statistics' are and how the handle parameter works. The phrase 'profile and aggregate statistics' is ambiguous about whether statistics are global or profile-specific, leaving an agent without enough detail for confident 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?

Schema description coverage is 0%, so the description must compensate for the undocumented 'handle' parameter. It does not: the description never mentions the handle or explains that it identifies the profile. The agent must infer meaning from the parameter name alone.

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 ('Read') and resource ('one opt-in public UsageMax profile and aggregate statistics'), clearly identifying what the tool does. It does not explicitly differentiate from sibling tools like leaderboard or network_stats, so it stops short of a 5.

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 no explicit when-to-use guidance or alternatives. 'Opt-in public' hints at a prerequisite for data availability, but there is no direction on choosing this tool over ask_site, leaderboard, or network_stats.

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