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

The annotations already establish this as a safe, read-only, idempotent query. The description adds useful behavioral context by specifying that it evaluates the current situation and compares against the posted limit, rather than raw speed alone. Nothing in the description contradicts the annotations.

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 communicates the core purpose and key qualifiers (right now, posted limit) without redundancy. It is front-loaded and free of unnecessary detail.

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-only tool with an output schema and strong safety annotations, the description covers everything needed to invoke it appropriately. The combination of annotations, output schema, and succinct description leaves no significant contextual gap.

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 the schema covers 100% of the parameter surface, so there is little parameter information to add. The description's mention of 'posted limit' gives helpful semantic framing even though no parameters exist.

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 identifies the tool's function: determining whether the subject is currently speeding and by how much over the posted limit. While phrased as a question rather than an imperative-style description, it is specific and distinguishable from sibling tools like get_truck_state or get_raw_telemetry.

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 the tool should be used when the current speeding status relative to the posted limit is needed. However, it does not explicitly explain when to prefer this tool over alternatives or mention any exclusions, leaving comparison with sibling tools to inference.

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 declare readOnlyHint=true, openWorldHint=true, idempotentHint=true, and destructiveHint=false, covering safety and idempotency. The description adds no additional behavioral context (e.g., latency, freshness, or what happens if no active job exists). Since annotations carry the burden, a 3 is appropriate; the description does not contradict 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?

The description is a single, information-dense sentence. It front-loads the core content (current delivery job) and lists the returned fields without any filler. Every word earns its place, making it exceptionally 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?

For a zero-parameter, read-only tool with an output schema available and annotations covering behavioral safety, the description is complete. It specifies the key content returned, and the output schema handles the exact structure. Nothing an agent needs to decide whether to call this tool is missing.

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, so schema description coverage is trivially 100%. The description does not need to explain any parameters. Per the rubric, 0 params yields a baseline of 4, and the description adds no unnecessary detail.

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 resource (current delivery job) and the specific attributes it returns (cargo, route, pay, deadline, on-time status). It unambiguously identifies the tool's function and differentiates it from sibling getters like get_truck_state or get_fuel_status by focusing on the job itself.

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 the tool is for retrieving current job details, but it does not explicitly state when to use it versus alternatives. There is no context about prerequisites or exclusions, but given the simplicity of a zero-parameter getter, the usage is reasonably inferable from the name and description. It meets the 'implied usage' bar.

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?

The annotations already declare readOnly, idempotent, and openWorld hints, so the safety profile is covered. The description adds useful semantic context (score range and contributing factors) beyond the annotations, but it does not disclose any additional behavioral traits such as data staleness or calculation basis. Given the annotations carry the main burden, a 3 is appropriate.

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, dense sentence that front-loads the key output (0-100 score) and immediately notes the inclusion of affecting factors. There is no filler or repetition; every word contributes to understanding.

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 read-only tool with no parameters and an output schema present, the description sufficiently explains what the score represents and its range. It could benefit from a note on when to use it over sibling tools, but that falls under usage guidelines. Overall, the tool is adequately specified for 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?

There are zero parameters, so the schema is fully self-explanatory. The description adds no parameter information, but none is needed. The baseline of 4 applies due to the absence of 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 clearly states the tool returns a 0-100 driving score for the current session, and mentions that it includes the factors that lower it. This is a specific resource ('driving score') with a precise range and context, distinguishing it from sibling tools like get_trip_summary or get_raw_telemetry.

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 given on when to use this tool versus alternatives such as get_trip_summary or check_speeding. The description only states what it does, not when it is appropriate or when another tool should be preferred. This leaves the agent to infer usage context from the name and siblings.

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 declare readOnlyHint, idempotentHint, and destructiveHint=false, covering the safety profile. The description adds the specific data fields returned but does not reveal any additional behavioral traits (e.g., data freshness, side effects, or error conditions). With annotations covering the core behavior, a score of 3 is appropriate.

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, compact sentence lists all four data points without any filler. It is front-loaded with the most important information (fuel level) and efficiently covers the rest.

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 there are no parameters and an output schema exists, the description fully communicates the tool's purpose and return value. An agent can confidently call this tool without additional context.

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, so no parameter-specific documentation is needed. The description's mention of the routed destination implies that navigation context is automatically used, but since no parameters exist, the baseline of 4 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 states precisely what the tool returns: fuel level, consumption, estimated range, and a binary judgment about reaching the routed destination. This is specific, names the resource (fuel status), and clearly distinguishes it from siblings like get_navigation or get_truck_state.

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 the tool is for fuel-related queries, but it does not explicitly state when to use it over alternatives or any exclusions. Given its narrow scope, the intended use is fairly obvious, but the lack of explicit routing guidance leaves room for ambiguity.

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 declare readOnlyHint, openWorldHint, idempotentHint, and non-destructive behavior. The description adds value by specifying the exact content returned (distance, ETA, posted limit, speeding). It does not cover edge cases (e.g., no active route), but given the annotations and the simplicity of the tool, the added context is sufficient.

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, front-loaded sentence that begins with the core resource ('Routing status') and lists the returned fields immediately. Every word is informative with no redundancy.

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 has no parameters, an output schema exists, and annotations cover safety, the description fully explains the tool's purpose and scope. Nothing needed for correct invocation or understanding is missing.

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, so the schema is empty and the description carries no parameter-specific burden. The description conveys the semantic output meaning, which fully compensates for the lack of parameters. Baseline of 4 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 clearly states a specific resource ('Routing status') and the precise data returned (distance, ETA, posted limit, speeding status). It is distinct from siblings like get_truck_state or get_fuel_status, which deal with other domains.

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 for retrieving routing information but does not explicitly contrast with alternatives such as check_speeding (which focuses solely on speeding) or get_trip_summary. No when-not-to-use or alternative routing is provided, so the agent must infer from context.

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 declare readOnlyHint=true, idempotentHint=true, and destructiveHint=false, so the safety profile is covered. The description adds value by explaining the output is a 'full normalized telemetry snapshot', indicating the data is normalized and complete, which is behavioral context not present in the annotations. This enhances understanding without contradicting any annotation.

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, front-loaded sentence that immediately states the core purpose ('full normalized telemetry snapshot as JSON') and then adds a clarifying audience note. Every word earns its place, with no filler or redundancy. It is 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?

For a zero-parameter tool with an output schema already defined, the description is sufficient. It states what the tool returns and who it is intended for. It does not explicitly mention when to prefer siblings, but the 'full' vs specific distinction is implied, and the presence of an output schema means return format is already documented. Overall, it covers what an agent needs to invoke it correctly.

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 schema description coverage is trivially 100% because there are no properties to document. The baseline for 0 parameters is 4, and the description does not need to explain parameters. It adds no parameter-specific information, but none is required.

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 the tool returns 'the full normalized telemetry snapshot as JSON', which clearly identifies the resource and the format. The qualifiers 'full' and 'normalized' help distinguish it from siblings like get_truck_state or get_fuel_status, though it does not explicitly name a sibling or contrast itself. This is clear and specific enough to avoid confusion.

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 says it is 'for power users / debugging', which implies the intended use case: when a user needs the complete raw snapshot for debugging rather than a focused subset. It does not explicitly state when not to use it or name alternative tools, but the user audience hint provides clear context about when this tool is appropriate.

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 convey read-only, idempotent, and non-destructive behavior, so the description need not repeat these. It does add the context of EU hours-of-service style, which hints at the regulatory framework behind the guidance. However, it does not disclose any edge cases, data availability limits, or the nature of the output beyond 'guidance.' Given the low complexity and strong annotations, this is adequate but not exceptional.

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, front-loaded sentence with no filler. It states the core purpose ('Fatigue guidance') first, then clarifies the basis ('continuous driving time') and adds a contextual qualifier ('EU hours-of-service style'). Every word earns its place, and it is appropriately sized for a zero-parameter tool.

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 has no parameters and an output schema exists (which we don't see but is present), the description sufficiently conveys what the tool does. It could be enhanced by explicitly stating when to call it (e.g., 'Use when the driver has been driving for a sustained period'), but it is currently adequate for an agent to understand its role among the sibling tools. The lack of any handling instructions for missing or invalid data is a minor gap.

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?

With zero parameters, the baseline is 4 per the rubric. The description's mention of 'continuous driving time' clarifies the conceptual input even though no explicit parameter exists, helping the agent understand what data drives the guidance. This adds value beyond the empty 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 clearly states a specific verb ('get') and resource ('rest advisor') with a precise function: providing fatigue guidance based on continuous driving time. It is distinct from sibling tools such as get_truck_state, get_navigation, and get_eco_score, which cover unrelated domains. The EU hours-of-service mention adds domain context without ambiguity.

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 the tool is relevant when continuous driving time is a factor, but it does not explicitly state when to use it versus alternatives, nor does it mention exclusion criteria. Since no sibling tool provides fatigue guidance, the lack of explicit alternatives is acceptable, but it still lacks a clear 'use when' statement. The phrase 'based on continuous driving time' gives an implicit trigger, but more explicit guidance would improve clarity.

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 declare readOnlyHint=true, idempotentHint=true, and destructiveHint=false, covering the safety profile. The description adds the temporal context ('since the server started'), which is valuable behavioral information beyond the annotations. It does not elaborate on return structure, but that is covered by the output schema.

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, front-loaded sentence with no wasted words. Every element ('rolling totals', 'since server started', the list of data types) earns its place, making it instantly scannable.

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 that the tool takes no parameters and an output schema exists, the description is sufficiently complete. It defines the time window and the content of the summary, leaving the return format to the schema. An agent can call it without ambiguity.

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?

There are zero parameters, so the baseline for this dimension is 4. The description correctly avoids mentioning any parameters, and the schema is empty, so there is nothing to add.

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 ('get'), a resource (trip summary), and the scope ('rolling totals since the server started'), while enumerating the data categories (distance, time, speeds, fuel, events). This clearly distinguishes it from siblings like get_fuel_status or get_truck_state, which focus on narrower aspects.

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 conveys the use case (retrieving overall trip aggregates) but provides no explicit guidance on when to choose this over alternatives. It does not mention exclusions or contrast with sibling tools, leaving the selection to inference.

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 declare readOnlyHint, idempotentHint, and non-destructive, so the safety profile is covered. The description adds useful context by noting it works with any configured source (mock/http/mmap), indicating backend-agnostic behavior and the snapshot nature, which goes 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?

The description is two concise sentences. The first lists the included state aspects, and the second frames the tool's primary use case and backend flexibility. Every sentence carries meaning and the most important information is front-loaded.

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 has no parameters, is read-only with comprehensive annotations, and has an output schema, the description fully covers the essential context. It explains what the tool does, what data is returned, and that it works across sources, so no critical information is missing.

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?

There are zero parameters, so the schema description coverage is 100% by vacuity. Per the baseline rule for 0-parameter tools, a score of 4 is appropriate; the description does not need to compensate for missing 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?

The description clearly states the tool fetches the 'current truck state' and enumerates the specific data aspects it covers (speed vs limit, engine, gear, cruise, fuel, damage, lights). It also brands itself as a 'one-call snapshot', which effectively differentiates it from more specialized sibling tools like get_fuel_status or get_navigation.

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?

It frames the tool as the go-to for a comprehensive 'what's happening right now' overview, which implicitly advises using it when a broad state is needed rather than a single metric. However, it does not explicitly name alternative tools or exclusion criteria, so the guidance is clear but not fully explicit.

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 declare readOnlyHint, openWorldHint, idempotentHint, destructiveHint=false, so the safety and idempotency profile is covered. The description adds the behavioral traits of ordering (newest first) and scope (driving events including specific categories). It doesn't mention pagination or default limit behavior, but that is partially covered by the schema default. Given the annotations provide a strong baseline, the description adds useful context beyond 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?

A single sentence that is concise and front-loads the core purpose (recent driving events) before enumerating event types and ordering. No filler words.

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 has an output schema (though not shown here, it's indicated as present), and the description doesn't need to explain return format. Combined with annotations and schema, the description is sufficient for an agent to know what it returns and when to call it. Minor gap: no mention of how events are categorized or whether filters exist beyond limit, but that may be beyond scope for a simple list 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?

Schema coverage is 100% (the only parameter `limit` has a description). The description does not add additional parameter semantics beyond what's in the schema, but the parameter itself is simple and well-covered. Baseline 3 is appropriate when the schema already documents the parameter effectively.

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 resource (recent driving events) and the specific event types (speeding, hard braking, collisions, refuels), and notes the ordering (newest first). This distinguishes it from sibling tools like get_raw_telemetry or get_trip_summary, which are either more raw or aggregate differently. The verb 'list' is explicit.

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 a general-purpose listing use case but does not explicitly state when to use this vs. alternatives. Sibling tools like check_speeding or get_trip_summary might cover similar ground, but no exclusion or preference guidance is given. The ordering and event type filtering are clear, but no scenarios are provided.

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