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

Beyond the readOnlyHint/openWorldHint annotations, the description adds meaningful behavior: the value is measured live, includes source and last update, and pendingAmpLimit appears only when a change is recorded but unconfirmed by the car. This helps the agent interpret freshness and pending state correctly.

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 dense, information-rich sentences with no filler. The core semantics are front-loaded, and the endpoint/scope parenthetical is compact and useful for authorization context.

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-required-parameter read with an output schema, the description covers the core result, live behavior, pending state, endpoint, and authorization scope. Nothing critical for correct invocation or interpretation 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 input schema already documents all three parameters with 100% coverage, including the VIN optionality and the raw flag's warning about carrying the VIN despite redaction. The description itself adds no parameter-level meaning, so the baseline 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 identifies exactly what is returned: the configured maximum AC charging current in amps, its source, last update, and pendingAmpLimit when the car has not yet confirmed a change. This clearly distinguishes it from sibling tools like get_target_soc and get_charging_estimate.

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 context: it is the configured amp limit, measured live, so the agent understands when to use it for live charging-current-limit reads. It does not explicitly name alternatives or exclusions, but the stated purpose makes the usage straightforward.

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 signal readOnlyHint and openWorldHint, so the safety profile is known. The description adds useful behavioral context beyond the annotations: it is an M2M endpoint, requires the 'pdp-telemetry/availability' scope, and exposes the raw flag behavior (even carrying VIN when redaction is on, though that detail lives in the schema rather than the description itself).

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, front-loaded with the core meaning, then the endpoint and scope. Every clause adds information; there is no filler or repetition.

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 a rich output schema present, complete parameter descriptions in the input schema, and annotations covering read-only/open-world behavior, the description only needed to supply the operational essentials (endpoint, scope, and meaning of the fields it returns), all of which are present.

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 baseline is 3 even without parameter details in the description. The description adds field semantics (availabilityStatus, usageMode) and the endpoint template, but does not need to compensate for parameter docs since the schema already documents raw, vin, and delegated_account_id fully.

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 and resource: it retrieves 'Vehicle availability' with the concrete fields 'availabilityStatus and usageMode (whether the car is currently reachable/awake)'. It does not explicitly differentiate from sibling tools like get_car_status or polestar_status, but the parenthetical makes the availability semantics unmistakable.

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 context: this checks whether a car is reachable/awake, and it identifies the exact M2M endpoint and required OAuth scope. However, it provides no explicit when-to-use versus alternatives among the many sibling get_* tools, nor any 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?

Annotations already declare readOnlyHint=true and openWorldHint=true, but the description adds valuable behavioral nuance beyond these: it explains that optional fields appear only when reported by the car, and that a missing field means unreported rather than zero. This prevents misinterpretation of sparse data. It also includes a concrete reference-vehicle example (14 fields, none optional) and exposes the raw parameter's side effect (VIN leak) via the schema but also reinforces the behavior. No contradiction with 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 information-dense but efficiently organized: it front-loads the core battery fields, then discusses optional fields and the missing-field semantics, and ends with endpoint/scope details. Every sentence contributes useful context, and the structure (main fields, caveat, endpoint) is logical. It is slightly longer than strictly necessary but avoids redundancy, earning a 4 rather than 5.

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 an output schema exists (not shown but indicated) and the description thoroughly explains the data contract (including optional-field behavior and a concrete example), the tool is fully specified for an agent to invoke correctly. The endpoint and OAuth scope are provided, and the raw parameter's behavior is covered in the schema. No critical operational detail is missing for a read-only telemetry query.

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% and each parameter (raw, vin, delegated_account_id) already has a clear description. The tool description adds no additional parameter-level semantics beyond what the schema provides, but it does reference the endpoint and scope which indirectly clarifies the vin usage. Since the schema carries the full explanatory burden, a baseline of 3 is appropriate; the description does not need to compensate.

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 clear and specific verb-resource pairing: 'Battery state' followed by an enumerated list of the exact metrics returned (charge level, charging status, distance to empty, time to full, consumption). This unambiguously differentiates it from sibling tools like get_odometer or get_location. It names the resource (battery) and gives a concrete inventory of output fields, making the tool's purpose unmistakable.

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 does not explicitly name alternative tools or state when NOT to use it, but it clearly implies its scope: any query about battery state or charging metrics. The field list and endpoint make the usage context obvious, and it notes the data contract for optional fields. While it lacks an explicit exclusion (e.g., 'for charging estimates use get_charging_estimate'), the purpose is unambiguous enough for an agent to select it appropriately.

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 and openWorldHint, and the description adds useful behavioral context: it discloses 'Costs several domain reads (cached)' and notes 'data age for each,' giving agents insight into performance and data freshness without contradicting 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 two sentences: the first front-loads the purpose and enumerates the contents, the second gives cost and the alternative. There is no wasted wording, and the key information is presented early.

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 presence of an output schema (which explains return values) and annotations (readOnlyHint, openWorldHint), the description adequately covers the tool's aggregate nature, cost, and usage. It doesn't describe the output structure, but that is handled by the schema. The minor gap is missing explicit when-not-to-use guidance, but that's a usage-guideline issue more than a completeness issue.

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 single parameter (vin) is fully described in the schema with 100% coverage, including optionality and default behavior when omitted. The description adds no additional parameter information, so the baseline of 3 is appropriate since the schema handles the semantics.

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: 'One-call status of the car' and enumerates the specific data fields (charge level, range, lock/doors, etc.). It distinguishes itself from sibling get_* tools by explicitly saying 'use instead of calling five get_* tools,' making the unique role obvious.

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 a clear use case ('use instead of calling five get_* tools') and implies when to use this aggregated tool versus the individual getters. However, it doesn't explicitly state when NOT to use it (e.g., if only one field is needed), though that is strongly implied by the alternative wording.

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 and openWorldHint, so the description only needed to add value beyond those. It does: it explains that over M2M the response is a settings record with typically just an id and utc0 flag, that missing coordinates are expected rather than a failure, and it lists the exact endpoint and OAuth scope.

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 compact and front-loaded with the key caveat about settings-record behavior, then packs the endpoint and scope into a parenthetical. Every sentence earns its place, and there is 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 read-only tool with zero required parameters, 100% schema coverage, and a provided output schema, the description adds the one crucial non-obvious fact: the response shape over M2M differs from what the name suggests. The endpoint and scope complete the operational picture.

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%, so the three parameters are already fully documented in the input schema. The description doesn't add parameter-level semantics beyond referencing the VIN in the endpoint path, which is acceptable given the schema carries the burden.

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 identifies a specific resource ('configured charge locations') and the endpoint path, and clarifies that it is not a list of addresses. It doesn't use an explicit verb like 'retrieves', but the tool name and endpoint make the action clear, and it distinguishes itself from a coordinate-lookup expectation.

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 when to use it by explaining that finding no coordinates is normal, and it gives the M2M endpoint and scope. However, it doesn't explicitly state when to prefer this tool over a sibling like get_is_at_charge_location or plan_cheapest_charge, nor does it provide any when-not-to-use guidance.

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 mark the operation read-only and open-world. The description adds valuable non-obvious behavior: the M2M response typically carries only the last sync timestamp rather than an active/inactive boolean, plus the exact endpoint and required scope. This goes beyond what annotations alone provide.

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 dense sentences with no filler. The core state is stated first, followed by the key behavioral caveat, then endpoint and scope in a compact parenthetical. Every element 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 read-only getter with optional parameters, the schema covers all inputs and an output schema exists. The description supplies the endpoint, auth scope, and the unusual timestamp-only payload behavior. The only slight gap is the absence of explicit guidance on when an active/inactive boolean might be present, but this is 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?

The input schema has 100% parameter coverage, so the baseline is 3. The description does not add parameter-specific meaning beyond referencing the vehicle in the endpoint path, but the schema already documents raw, vin, and delegated_account_id adequately.

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 names the resource precisely: "Charge-now override state," with the M2M endpoint spelled out. It clearly distinguishes this from siblings like get_global_charge_timer and get_target_soc by focusing on the charge-now override, though it does not explicitly mention those siblings.

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 endpoint and scope hint at direct M2M use, and the description implies when the tool is relevant by naming the exact override state, but it gives no explicit when-to-use guidance or alternative tool comparisons. Usage context is present but mostly implied.

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 only say read-only and open-world, so the description adds meaningful behavior: it explains the estimation inputs (energyAvailable, configured amp limit, and the car's own time-to-full) and conditional logic ('when available', 'when charging'). This does not contradict the readOnlyHint.

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 with the core purpose front-loaded and supporting estimation logic packed efficiently afterward. It is compact but slightly dense; the parenthetical field reference could be trimmed without losing much 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?

With an output schema present and fully documented optional parameters, the description covers the key inputs and calculation sources an agent needs. It falls short only in not orienting the agent toward sibling alternatives or clarifying where the target charge level originates.

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% for both parameters, so the description need not re-document vin/phases. It adds algorithmic context about amp limit and energy sources, but no additional parameter syntax or constraints beyond the 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 opens with a specific verb and resource: it estimates energy and time needed to reach a target charge level from current SoC. This distinguishes it from siblings like get_target_soc and get_battery without needing to name them.

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 plan_cheapest_charge or get_charge_now; it also states no prerequisites or exclusions. The context is inferable but not 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 carry readOnlyHint=true and openWorldHint=true, so the safety profile is disclosed and the description does not contradict them. The description adds the M2M endpoint and telemetry scope as data-source context but reveals little else about behavior (staleness, failure modes, unknown-state handling), so it lands at baseline.

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 compact sentence with the component list front-loaded, followed by a parenthetical endpoint note. Every token carries information; there is no filler or restatement of the title.

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?

An output schema exists so return shape is documented externally, annotations cover read-only and open-world behavior, and the schema fully documents all three optional parameters. The only real gap is usage routing versus the sibling set, which leaves a minor rather than critical hole.

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 each parameter already has rich semantics: raw explains its VIN-redaction bypass, vin explains single-vehicle optionality, and delegated_account_id explains the third-party constraint. The description adds no parameter-level meaning beyond the endpoint context, so the high-coverage 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 identifies a precise resource — exterior state — and itemizes exactly what it covers (doors, windows, hood, tailgate, tank lid, central lock, tailgate lock, alarm). It reads as a noun phrase without an explicit retrieval verb, and it does not explicitly differentiate from overlapping siblings like is_car_secure, but the component enumeration makes the tool's scope unambiguous.

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?

There is no when-to-use guidance or alternative routing. The description does not say when to prefer this over is_car_secure (which plausibly overlaps on lock/alarm state) or the other get_* telemetry tools. The M2M endpoint and scope note is technical context, not situational guidance.

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 description adds genuinely useful behavioral context beyond the readOnlyHint/openWorldHint annotations: pending changes appear only when an edit has not yet reached the car, and an empty pending block means nothing is queued. This clarifies the sync/pending semantics without contradicting 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 three compact sentences with no filler: payload definition, the key pending-changes nuance, and endpoint/scope context. Every sentence earns its place, and the most non-obvious behavior is called out explicitly.

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 read-only getter with a full output schema and fully documented optional parameters, the description provides the non-obvious semantics needed to understand the result (pending behavior, activation, sync status). It is slightly incomplete about selection criteria among sibling charging/timer tools, but nothing required to invoke it correctly 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?

Schema description coverage is 100%, so the schema already documents vin, raw, and delegated_account_id. The tool description adds no parameter-level semantics, which keeps this at the baseline rather than elevating it.

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 identifies the exact resource (global-charge-timer) and its payload concepts (start/stop hour, timezone offset, activation flag, sync status), making it easy to distinguish from sibling charging/vehicle getters. The action 'get' is clear from the tool name and title, and the endpoint path leaves no ambiguity about scope.

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 the many sibling get_* endpoints, nor when not to use it. The word 'Recurring' implies the intended domain, but the agent is left to infer the decision boundary between this and related charging/timer 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 declare readOnlyHint and openWorldHint, so the safety profile is covered. The description adds the M2M endpoint and required scope, which is useful operational context, but it does not disclose additional behavioral traits such as response shape, rate limits, or the raw payload behavior described in the 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 compact and information-dense: it front-loads the core purpose, lists the specific health categories, and adds the endpoint and scope in a short parenthetical. Every segment earns its place with 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?

Given the rich schema, output schema, and annotations, the description is sufficient for an agent to understand what this tool returns and how to invoke it. It could be slightly more explicit about when to choose this over siblings, but that gap is minor for a read-only, parameter-light 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 description coverage is 100%, so the baseline is 3. The description itself does not explain the parameters, but the schema already provides detailed descriptions for raw, vin, and delegated_account_id, so no further compensation is needed.

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 resource as service health and enumerates the specific data returned: days/distance/engine-hours to service, service warning, and fluid/light/12V warnings. This level of detail distinguishes it from sibling tools like get_battery or get_car_status, even though the description uses a noun phrase rather than an explicit verb.

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 when to use this tool—when service intervals or vehicle warnings are needed—but it does not explicitly state when to prefer it over alternatives or mention any exclusions. The endpoint and scope details are helpful context but do not provide direct tool-selection guidance.

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 and openWorldHint=true, but the description adds valuable behavioral context by noting the tool often returns DATA_NOT_AVAILABLE on unsupported vehicles. It also provides the endpoint and scope, which helps with debugging and authorization.

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, clear sentence with a parenthetical technical note. It is front-loaded and contains no fluff, making it easy for an agent to parse quickly.

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 getter with all-optional parameters, an output schema, and annotations covering read-only and open-world behavior, the description covers the key edge case (DATA_NOT_AVAILABLE) and provides the endpoint. Nothing essential is missing 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?

Schema description coverage is 100%, so the parameters are fully documented in the schema. The description adds no additional parameter-level meaning, so it meets the baseline for high coverage without extra value.

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 checks whether the vehicle is currently at a saved charge location, using a specific verb and resource. It also distinguishes itself from sibling tools like get_charge_locations (which lists saved locations) by focusing on the current 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 purpose is clear enough that an agent can infer when to use it (checking current location vs. listing saved locations). However, it does not explicitly name alternatives or provide conditions, leaving slight room for ambiguity in tool selection.

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 and openWorldHint, so the safety profile is covered. The description adds the upstream M2M endpoint and required OAuth scope, which is useful operational context, but does not disclose data freshness, rate limits, or other behavioral caveats.

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 front-loads the core result fields and places the endpoint/scope in a compact parenthetical. Every word earns its place; there is no redundancy or 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 zero-required-parameter read tool with rich schema documentation and an output schema, the description plus annotations are almost fully sufficient. The only meaningful gap is the absence of any guidance about when this tool should be preferred over sibling getters.

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 describes all three parameters fully, including the VIN optionality rule and the raw payload redaction caveat. The description adds no parameter-level meaning beyond the schema, so the baseline score of 3 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 names a precise resource ('last known position') and enumerates the exact payload fields: latitude, longitude, altitude, heading, speed, and timestamp. This clearly distinguishes get_location from the other telemetry getters in the sibling list.

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 does not explain when to use this tool versus alternatives, nor does it give any exclusions, prerequisites, or conditional guidance. The endpoint and scope are informative context, but not usage direction.

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 and openWorldHint=true, covering the safety profile, so the description carries a lighter burden. It adds genuine value beyond annotations by specifying the selection boundary (health-domain warnings only), the extra inclusion of the service countdown, and how to interpret an empty result. Nothing here 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?

Two terse sentences with zero filler. The scoping statement is front-loaded, the categories are compactly packed in parentheses, and the empty-result semantics closes the definition. 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?

For a low-complexity read tool with one optional parameter, full schema coverage, and an existing output schema, the description covers all essential non-structural semantics: what subset is returned and what an empty response means. The only gap is an explicit pointer to get_health for the broader health picture, which is more a usage-routing concern than an invocation-completeness one.

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 single optional vin parameter is fully documented in the schema, including its optionality and the single-vehicle default behavior. The description contributes no parameter-specific detail, but the baseline of 3 applies because the schema carries the entire burden.

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 identifies a specific resource – active warnings from the health domain – and enumerates the exact categories (fluids, lights, 12V, service) plus the service countdown, with clear empty-result semantics. The 'Only' scoping implicitly separates it from the sibling get_health, which likely returns the full health dataset, though the sibling is not named explicitly.

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 'Only...plus...' phrasing and the 'empty means nothing needs attention' line imply this is the curated, decision-ready subset of the health domain, giving a sense of when it fits. However, there is no explicit when-to-use statement, no named alternative, and no exclusion such as 'for the full health status use get_health instead.'

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 and openWorldHint, so the description carries no safety burden. It adds useful context by naming the M2M endpoint and OAuth scope, and it clarifies units (km, km/h), but it does not describe response shape, latency, staleness, or other runtime behavior.

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 compact, front-loads the data content, and appends the endpoint/scope in a parenthetical. It is slightly awkward phrasing ('Odometer meters') but every element 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 simple read-only telemetry getter with zero required parameters, an output schema, and complete parameter documentation, the description provides enough context: data fields, units, endpoint, and auth scope. Nothing critical is missing 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?

Schema description coverage is 100%, so the schema already documents all three parameters thoroughly. The description adds no parameter-level detail beyond that, which meets the baseline but does not exceed it.

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 title supplies the verb ('Get') and the description clearly identifies the resource: odometer, trip meters, and average speeds. It does not explicitly contrast itself with sibling tools, but the telemetry domain is distinct enough that an agent can tell it apart from get_battery or get_health.

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 guidance on when to choose this tool over alternatives, nor does it state any exclusions or prerequisites. The endpoint and scope are useful context but do not help an agent decide between this and sibling getters.

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 and openWorldHint, so the safety profile is covered. The description adds meaningful context by naming the exact M2M endpoint and required OAuth scope, which helps the agent understand the access context. It adds no contradictory behavior claims.

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 compact sentences with the core purpose first and the endpoint/scope appended without fluff. Each sentence 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 read-only, zero-required-parameter fetch with a full output schema and complete parameter schema, the description is largely sufficient. It adds the endpoint and scope while annotations cover safety. The only mild gap is the lack of an explicit sibling pointer, already accounted for under usage guidance.

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 covers 100% of the parameters with detailed descriptions, so the description is not required to add parameter-level meaning. The tool description itself adds no extra detail about raw, vin, or delegated_account_id.

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 identifies the resource ('scheduled parking-climate timers') and enumerates the returned dimensions (ready-at hour, weekdays, repeat flag, activation), so an agent knows what data it will get. It is clear enough but does not explicitly separate this from the similarly named sibling get_parking_climatization.

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 use case (reading scheduled parking-climate timer configuration) and includes the endpoint and scope, but it never states when to prefer this over get_parking_climatization or other timer tools. No alternatives or exclusions are given, so guidance is mostly inferred.

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 and openWorldHint=true, so the safety profile is covered. The description adds useful context about the endpoint and the returned data fields, but does not disclose additional behavioral traits such as caching, staleness, or vehicle-state prerequisites. With annotations present, this is adequate but not rich.

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 focused sentence followed by a parenthetical endpoint/scope reference. It is front-loaded with the core semantics and contains 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?

The combination of a clear description, 100% schema coverage, readOnly/openWorld annotations, and an output schema covers invocation needs well. The only notable gap is the absence of explicit sibling routing guidance, but that is a usage-guideline concern rather than a completeness gap for calling the 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 description coverage is 100%, so every parameter (raw, vin, delegated_account_id) is already fully documented in the schema. The description adds no extra parameter-level meaning, 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 identifies a specific resource (parking climatization) and enumerates the exact data it exposes: running status, runtime left, seat/steering-wheel heating intensities, and ventilation. This clearly distinguishes it from siblings like get_parking_climate_timer or get_pre_cleaning, whose resources are different.

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 when to use the tool: whenever current parking-climate/preconditioning status is needed. However, it does not explicitly state when not to use it or point to alternatives such as get_parking_climate_timer or get_pre_cleaning, leaving usage routing 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 and openWorldHint, covering the safety profile. The description adds useful context by naming the M2M endpoint/scope and the specific telemetry data returned. It does not add depth on edge cases or response behavior, but given the annotations and output schema, the baseline burden is lower.

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 compact single sentence plus parenthetical endpoint/scope. It front-loads the key semantic data points and includes no filler, repetition, or extraneous 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 read-only telemetry getter with an output schema, no required parameters, and fully documented params, the description is nearly complete. The only noticeable gap is the absence of any guidance about when to select this tool over climate/air-quality siblings, which keeps it from a 5.

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 descriptions cover 100% of the three parameters with clear explanations, so the baseline is 3. The description adds only the {vin} route hint and does not otherwise supplement parameter meaning, which is acceptable since the schema already carries that load.

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 names a specific resource (cabin air pre-cleaning) and enumerates exactly what the tool provides: running status, PM2.5/air quality index, last cycle validity and completion time. This is distinct from any sibling getter and leaves no ambiguity about the tool's role.

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?

There is no guidance on when to use this tool versus the many related siblings (e.g., get_parking_climatization, get_car_status, get_needs_attention). No context, exclusions, or alternative routing is provided, so an agent must infer applicability solely from the name.

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 and openWorldHint=true, so the safety profile is covered. The description adds value with the M2M endpoint and the OAuth scope pdp-charging/targetSoc, which clarifies access requirements and the data source without contradicting 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 short, front-loaded summary that states the resource, key output fields, endpoint, and scope in two concise sentences. Every clause carries useful information with no 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?

The description, combined with a fully documented parameter schema, an output schema, and read-only annotations, gives an agent everything needed to invoke a simple read-only retrieval tool correctly. The endpoint and scope add important operational context, and nothing critical 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?

Schema description coverage is 100%, so the schema fully documents raw, vin, and delegated_account_id. The description does not add parameter-level details, which is acceptable given the high schema coverage, but it also does not enhance understanding of any parameter beyond what the schema already provides.

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 resource: target battery state of charge, including the setting type and last-update context, so an agent can tell what data the tool returns. It is not fully differentiated from siblings like get_battery or get_charging_estimate, but the word 'target' and the endpoint make its purpose distinct enough.

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 when target state of charge or its setting type is needed, but it does not explicitly state when to prefer this tool over related siblings such as get_battery or get_charging_estimate. No exclusions or alternative routing are provided.

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 description adds meaningful behavioral detail beyond the readOnlyHint and openWorldHint annotations by clarifying it returns true/false and names any open item. It accurately reflects the read-only nature of the check without contradicting 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, front-loaded sentence that states the core behavior first and then specifies exactly what is checked. Every phrase adds useful information with no 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 simple read-only check with one optional parameter, an output schema, and full parameter documentation, the description is complete. It tells the agent what the tool returns and what security aspects it covers.

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 sole parameter, vin, is fully documented in the input schema with an explanation of its optionality. The description adds no parameter-specific detail, but with 100% schema coverage this is acceptable.

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 performs a true/false security check covering doors, windows, hood, tailgate, central lock, and alarm. It is specific about the resource and behavior, though it does not explicitly distinguish itself from siblings like get_car_status or polestar_status.

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 usage context is implied: use this when you need to know whether the car is physically secure and what may be open. However, there is no explicit guidance about when to use this instead of sibling status or health 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 mark this as read-only and not open-world, and the description reinforces that by saying 'Every domain this server reads.' It adds valuable behavioral context about the 404 error semantics and the distinction from missing vehicle data, 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?

Two dense, purposeful sentences. The first states exactly what is returned, and the second gives actionable guidance. No filler or 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?

For a parameterless, read-only listing tool with an output schema present, the description fully covers what the tool does, what it returns, and when to use it. The error-semantics note adds important operational context that the schema and annotations alone would not provide.

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 description-level parameter semantics are largely irrelevant. The baseline of 4 applies because there is nothing for the description to clarify about inputs.

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 lists every domain the server reads, with endpoint, OAuth scope, and tool name. This distinguishes it from siblings like list_vehicles and the get_* tools, which retrieve vehicle-specific data rather than a catalog of 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 explicitly tells the agent to consult this tool rather than guessing a domain name. It also clarifies the difference between an unknown domain returning a 404 VALIDATION_RESOURCE_NOT_FOUND and a vehicle reporting no data, helping the agent diagnose errors correctly.

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 and openWorldHint, so the safety profile is covered. The description adds useful context that the result is scoped to VINs authorized for this credential, but it does not disclose anything further such as pagination, ordering, or behavior when no vehicles are available.

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, tightly scoped sentence that communicates the action, the resource, and the authorization constraint. Every word earns its place, with no filler or repetition.

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 there are no parameters, an output schema exists, and annotations cover read-only and open-world behavior, the description is complete for an agent to select and invoke the tool correctly. It clearly states what is returned (VINs) and the authorization boundary, which is all the agent needs.

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, and schema description coverage is 100%, so there is no parameter ambiguity to resolve. The baseline for a parameterless tool is 4, and the description appropriately focuses on output instead of inputs.

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 and resource: it lists the VINs authorized for the credential, which clearly distinguishes this from the many get_* siblings that return details about individual vehicles. It is explicit about the scope of the result set, not just a restatement of the title.

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 that this tool is for discovering which vehicles the current credential can access, but it does not explicitly state when to use it versus alternatives such as list_domains or the get_* tools. No exclusionary guidance is provided, though the simple no-parameter design makes the intended role fairly clear.

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 mark this read-only, and the description reinforces that by saying it 'computes' a plan rather than executing a charge. It adds non-obvious context about depending on the global-charge-timer window and ensuring enough energy to hit the target level. It does not disclose failure behavior when the window cannot satisfy the target, but the output schema and open-world hint mitigate that gap.

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 sentence with no filler. It front-loads the input ('Given hourly electricity prices'), states the core computation, and names both dependencies. Every word contributes.

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 description, combined with the fully covered input schema, the output schema, and the readOnly/openWorld annotations, gives an agent everything needed to invoke the tool correctly. It explains the tool's inputs, dependencies, and output intent without over-explaining return values.

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 all four parameters are already documented. The description adds conceptual context by linking prices, the charge window, and the target level, but it does not add parameter-level detail beyond what the schema provides. Baseline 3 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 uses a specific verb ('computes') with a clear resource ('cheapest hours inside the car's charge window') and a measurable goal ('deliver enough energy to reach the target charge level'). It is immediately distinct from the sibling getter tools, which retrieve state rather than produce a plan.

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 states the input condition ('Given hourly electricity prices') and the constraints it uses ('charge window', 'target charge level'), so an agent knows when this tool is relevant. It does not explicitly name alternative tools or exclusion cases, but the context is strong enough to route appropriate requests.

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, and the description adds meaningful behavioral context: it is a self-report that exposes budget consumption, limits, rate ceilings, cache performance, and token expiry. There is no contradiction and no hidden side effects implied.

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 tight sentences with the metric list front-loaded and the usage trigger in the second sentence. 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?

For a zero-parameter, read-only status tool with an output schema, the description fully explains what the tool reports and when to invoke it. Nothing needed for correct selection or invocation 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 description carries no parameter burden. Baseline 4 applies because no parameter documentation is needed.

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 distinct purpose: a server self-report covering API budget, rate ceiling, cache hit rate, token expiry, and mode. This clearly separates it from the sibling vehicle-data getters, all of which report car state rather than server/API status.

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 gives an explicit trigger condition: 'Call this if you suspect you are burning through the daily API budget.' It does not name alternatives or exclusions, but given the unique server-level scope, no sibling is a genuine alternative.

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