mileage-logbook

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

Annotations already indicate this is not read-only and not destructive, and the description adds useful behavioral detail: existing data under the token stays, and a wrong or expired key changes nothing. This goes beyond the annotation hints by explaining failure semantics and safety of the operation.

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 with no filler. It front-loads the core action, then gives the key format and safety guarantees, and closes with the verification tool. Every sentence contributes essential information.

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 single-parameter activation tool with annotations covering the safety profile, the description is complete: it states what the tool does, what input is needed, what happens on failure, and how to confirm success. There is no missing critical information for an agent to call 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 schema already documents the key parameter and its format with 100% coverage. The description adds meaning by specifying that the key must be issued at checkout for this server or the bundle, which clarifies validity requirements not present in 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 uses a specific verb and resource: it 'turns Pro on' for the connection using a license key. It also distinguishes itself from the sibling license_status tool by saying license_status confirms the activation. This leaves no ambiguity about what the tool accomplishes.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description provides clear context for use: the key must be an MCPL1.<payload>.<signature> issued at checkout for this server or the bundle. It does not explicitly list exclusions or alternative tools, but it does reference license_status as the confirmation path, giving the agent a sense of the workflow.

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. The description adds useful context beyond annotations by specifying the JSON response contents and stating 'nothing changes,' reinforcing the read-only nature of the call.

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 cover output, purpose, usage context, and side-effect guarantee. Every sentence earns its place 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?

With no output schema, the description sufficiently describes the return value. With no parameters, annotations covering safety, and a clear use case, nothing essential is missing for an agent to invoke this tool 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?

There are zero parameters and the schema already fully documents that fact. The description explicitly says 'No arguments,' which is accurate and reinforces the schema without needing further elaboration.

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 begins with a specific verb ('Report') and a precise resource ('this endpoint's licence state for your token'), and enumerates the exact output fields: product, tier, reason, and checkout URL. This clearly distinguishes it from sibling tools like license_activate.

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 states when to call it: 'Call it to explain a free-tier refusal.' This is clear contextual guidance, though it does not name alternatives or explicitly state when not to use it.

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 idempotent, so the description adds value by disclosing specific behavior: refusal when any non-personal trip is unpriced, oldest-first ordering, and the bare-number amount format for spreadsheet compatibility. These traits go well beyond the annotation hints and shape caller expectations.

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 dense but efficient. Every clause contributes meaning: column list, ordering, rate context, amount formatting, and refusal condition. It is front-loaded with the core purpose and contains 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 read-only export with no output schema, the description covers output format, ordering, column semantics, and failure mode. It leaves minor gaps such as whether a header row is included or what happens when the date range has no trips, but these are not critical 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 coverage is 100%, with both parameters already described with format and defaults. The description adds the concept of a 'window' but no parameter-specific detail beyond what the schema already provides, 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 precise verb+resource: exporting the mileage log as CSV. It enumerates every column and explicitly orders rows oldest first, distinguishing it from sibling tools like mileage_summary and trip_list by the one-row-per-trip CSV format.

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?

'Export the log as CSV for an accountant' establishes a clear use case. The description implies when to use it, but it does not explicitly state when not to use it or name alternatives such as mileage_summary for aggregated totals.

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

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

Annotations already establish the read-only, idempotent, non-destructive profile. The description adds meaningful behavior beyond that: per-day rate selection, listing no-rate trips with reasons instead of dropping them, and the 'Never metered' operational note. This exceeds the lower bar set by the annotations, though 'Never metered' is slightly ambiguous.

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 core summary output, then adds edge-case behavior and defaults. Every sentence earns its place, but 'Never metered' is cryptic and could be clearer or removed.

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 is no output schema, the description does a good job enumerating output contents, grouping, rate behavior, and no-rate handling. It is slightly incomplete regarding the exact structure of the response and leaves 'distance kept per unit' unclear, but overall it is sufficient 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?

The schema already provides 100% parameter documentation, including defaults and the category enum values. The description reinforces date-range and category concepts but does not add significant semantic detail 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 clearly identifies a mileage summary over a date range, including trips, per-day rates, deductible amounts, and per-currency totals. It is specific enough to distinguish from most siblings, though it never explicitly differentiates itself from mileage_export or trip_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 implies usage for aggregate deductible-mileage reporting and states the current-calendar-year default. However, it gives no explicit guidance about when to choose this tool over mileage_export or trip_list, leaving the 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, idempotentHint, and destructiveHint=false. The description adds valuable context beyond annotations: grouping by jurisdiction and category, ordering by effective-from dates, and the purpose ('the series each trip is priced from'). No contradiction.

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 tight sentences with the main behavior front-loaded: the verb-and-resource clause leads, followed by grouping/ordering detail and a concise safety note. 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?

With no output schema, the description carries the return-shape burden and does it well by describing grouping and ordering. It doesn't cover empty-list or error behavior, but for a simple read-only list tool this 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?

The tool has zero parameters, so schema coverage is vacuously 100%. Baseline for 0 params is 4; the description appropriately focuses on behavior and return shape rather than 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?

States a specific verb and resource: 'List every mileage rate on file,' with concrete details about grouping and ordering. Clearly distinguishes from siblings like rate_set (write) and trip_list (different resource).

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?

Provides clear context for when to use the tool (to view all mileage rates) and explicitly notes 'Reads only.' It does not name alternative tools or exclusion conditions, but the context is strong enough for an agent to route 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?

With all annotations false, the description carries the behavioral burden. It discloses non-obvious behavior: rates form series, trips use the rate in force on the drive date, no rates are preloaded, and the free tier is limited. It does not mention duplicate/replacement behavior, but the disclosed semantics are substantial.

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?

Four focused sentences with no filler: a front-loaded definition, rate-series semantics, a verification warning, and a plan limitation. Every 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 six-parameter tool with no annotations and no output schema, the description gives a coherent picture of how rates apply over time and notes the plan restriction. It is slightly incomplete on conflict behavior such as duplicate effective dates or replacement, but the agent has enough to choose and call the tool 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?

Schema description coverage is 100%, so the baseline is 3. The description paraphrases the six parameters and ties them to the effective-date series model, but it does not add factual detail beyond what the input schema already documents.

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?

States a specific action (set), a specific resource (mileage rate), and the precise scope (per category, jurisdiction, unit, and effective date). The first sentence alone clearly differentiates it from read-only siblings like rate_list and mileage_summary.

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 makes the tool's setting role clear and explains the rate-series context, so usage is implied rather than explicit. It does not name alternatives or state when not to use this tool, so it stops at a 3.

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

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

Annotations already indicate this is not read-only, but the description adds concrete behavior beyond them: it returns a TR-YYYY-NNNN identifier and counts against a 20-trip monthly quota based on trip date. No annotation contradiction is present.

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?

Three short sentences front-load the core action and fields, followed by return value and quota constraint. No filler or repetition of schema details.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a 9-parameter create tool with a detailed schema, the description covers the essential return value and quota behavior. Optional parameters like note and jurisdiction are left to the schema, which is acceptable; it could only add marginal clarity about what happens when the free tier is exceeded.

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 high (89%), so the schema carries parameter documentation. The description names the main captured fields and the allowed categories, but adds little beyond the schema's own descriptions.

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 — "Log one drive in the mileage log" — and enumerates exactly which fields are captured (date, from/to, distance, purpose, category). This clearly separates it from sibling list/remove/export/rate tools.

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 intended use is explicit: record a new trip when the user supplies trip details. It doesn't explicitly name sibling alternatives or exclusions, but as the only create-style trip tool among read/delete/export siblings, the context is clear; the free-tier note adds a practical condition.

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. The description goes beyond them by disclosing the ordering ('oldest first'), the exact output fields, and the non-obvious pricing behavior: each trip earns an amount under the day's rate, or shows a plain reason when unpriced. This is substantial behavioral context not available from annotations or 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 two sentences with no filler. Action, resource, ordering, output fields, and filtering capability are all front-loaded. 'Reads only' is a short reinforcement of annotations and does not bloat the text. Every 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 3-parameter, read-only list operation with fully documented schema and strong annotations, the description covers everything needed to call it correctly: what is returned, in what order, how pricing is calculated, and what happens for unpriced trips. No output schema exists, but the field list in the description compensates adequately.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The schema describes all three parameters at 100% coverage with formats and inclusive date semantics. The description merely restates that filtering by date range and category is possible, adding no new format, enum, or default information. This meets the baseline for full schema coverage without adding parameter-specific 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 states a specific verb ('List'), a specific resource ('trips in the mileage log'), and enumerates the exact fields returned with ordering ('oldest first'). This clearly distinguishes it from sibling tools like mileage_summary or mileage_export, which serve different aggregation/export purposes, even without naming them 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 description implies usage context via 'List trips...' and 'Filter by date range and category,' but it does not explicitly say when to prefer this tool over alternatives such as mileage_summary, mileage_export, or trip_add. There is no when-not-to-use guidance, so an agent must infer the appropriate choice from the resource type alone.

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 as destructive, so the description correctly moves beyond that by disclosing a non-obvious consequence: the id is not reissued and the gap in the TR series is a record of removal. This adds meaningful behavioral context 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?

Two sentences carry a complete message with no filler. The action and required identifier are front-loaded, and the important consequence about id reissuing is stated briefly and clearly.

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?

This is a simple single-parameter destructive operation with annotations covering the safety profile, so the description does not need to explain return values or auth. It covers the input format, purpose, and an important behavioral consequence, leaving no critical gaps 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?

The schema already documents the single parameter with an exact description and example, and schema coverage is 100%. The description reinforces the exact-match requirement and format, but does not add substantial semantic detail beyond what the schema 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 states a specific verb ('Remove'), a precise resource ('one trip from the mileage log'), and a required identifier format ('exact TR-YYYY-NNNN id'). It also gives the intended purpose ('for entries made by mistake'), making it clearly distinguishable from siblings like trip_add and trip_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 phrase 'for entries made by mistake' provides clear context for when this tool is appropriate. It does not explicitly name alternatives or exclusions, but the single-purpose nature of the tool and the exact-id requirement make the usage context reasonably clear.

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