BusCalc — Business & Trade Calculations

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

Beyond the read-only, idempotent, and non-destructive annotations, the description discloses that prices and omitted costs are not looked up and that private projects or purchases are not accessed. It also usefully lists the returned results, formula, assumptions, method version, and source-page URL, though it does not describe error behavior or infeasible break-even inputs.

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 purpose is front-loaded, and the four short sentences are easy to scan. The generic "tested BusCalc worksheet" wording adds little, but the remaining output and data-access disclosures earn their 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?

Together with the detailed nested input schema and annotations, the description is sufficient for an ordinary break-even calculation, and its return-value list partly offsets the absence of an output schema. Remaining gaps include the unexplained optional units object and behavior when price does not exceed variable cost, but these do not prevent normal 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?

With schema description coverage at 33%, the description needs to compensate, but it only mentions fixed costs and does not identify the required price and variable-cost inputs or explain the optional top-level units object. The nested schema documents fixed, price, and variable well, so parameter meaning is not wholly absent, but the description itself adds little.

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 opening sentence gives a specific operation and outputs: finding the units and revenue needed to cover fixed costs. This clearly identifies break-even sales and distinguishes it by subject matter from the sibling calculators, though it does not explicitly contrast it with nearby tools such as buscalc_decision_feasibility.

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?

"Use this tested BusCalc worksheet when the task matches its inputs and scope" provides a basic when-to-use cue. However, it is largely circular and gives no concrete prerequisites, exclusions, or alternative sibling tool for related but different tasks.

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 readOnly, idempotent, closed-world and non-destructive, so safety is covered. The description adds real value beyond that: it states the verdict is favorable/unfavorable, that breaking points, permitted repairs and verification priorities are returned, and that a zero limit acts as a hard lock. It does not describe failure behavior for mismatched modes or malformed inputs, keeping it below a 5.

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 sentences, front-loaded with the purpose and the covered scenarios before the return summary and the scope disclaimer. Every sentence carries information; the only mildly expendable element is the phrasing about 'original bounded workflow models,' which is promotional rather than operational.

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

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

For a tool with five mutually exclusive mode branches and roughly twenty parameters per branch, the description gives an accurate high-level orientation, plus return contents and lock semantics, leaving field-level detail to a very thorough schema. The gap is that terms like 'permitted repairs' and 'verification priorities' are undefined and there is no output schema, so the agent cannot anticipate the result shape precisely.

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?

Reported coverage is 0% only at the top level; the nested per-mode properties in fact carry very detailed descriptions, so the schema does most of the semantic work. The description contributes by naming the five workflows, which helps the agent pick the correct oneOf branch, but it adds no units, defaults or format guidance beyond what the schema already supplies.

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 plus resource and enumerates the five decision types it covers (job, restaurant run, delivery route, equipment purchase, staffing plan), which maps directly onto the schema's five mode branches. It does not explicitly distinguish itself from siblings such as buscalc_break_even_sales or buscalc_markup_vs_margin; the contrast (multi-constraint feasibility vs. single-formula calculation) must be inferred.

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?

Usage is implied by the scenario list and by 'Zero permitted change locks an item,' which tells the agent that a zero input means 'not permitted to change.' The closing clause ('no world-first, forecast or obtainable-saving guarantee') functions as a scope boundary telling the agent not to use this for forecasting, but no alternative sibling is ever named when a single calculation suffices.

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 readOnly, idempotent, non-destructive, and closed-world, so the bar is lower, and the description still adds real value: it discloses the return payload (named results, units, formula, assumptions, method version, source-page URL) and states that no prices or private projects are accessed. It does not cover rate conventions, rounding, or failure behavior, which keeps it short of a 5.

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 purpose is front-loaded and the return-value sentence earns its place, but 'Use this tested BusCalc worksheet when the task matches its inputs and scope' is filler that conveys nothing and could be cut without loss.

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 calculator with no output schema, the description does explain what comes back and what is out of scope, which is the important part. However it leaves the empty 'units' parameter and the single-value modelVersion rejection behavior unexplained, so an agent still needs to open the schema to call it safely.

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 33%, and the description contributes no parameter-level meaning at all beyond a passing mention of 'units' as a return value. The nested 'units' object is empty and entirely undocumented, so an agent cannot tell from the description whether it overrides or merely labels output units.

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: 'Build a fixed-rate equipment loan amortization schedule.' The 'fixed-rate' qualifier and 'amortization schedule' distinguish it reasonably well from sibling calculators such as buscalc_equipment_ownership_cost_per_hour or buscalc_fleet_cost_per_mile, though it never names a sibling 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 usage instruction is 'Use this tested BusCalc worksheet when the task matches its inputs and scope,' which is circular and gives no when-to-use condition, no exclusions against alternatives, and no prerequisites. The negative scope ('no prices... looked up') describes behavior, not selection criteria.

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 readOnly, idempotent, non-destructive, and closed-world behavior, so the safety profile is covered. The description adds genuinely new context beyond that: the return payload (named results, units, formula, assumptions, method version, source-page URL) and the fact that no external price lookups or private data access occur. It still does not explain the costing method or how utilization affects the result.

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 output/scope sentences earn their place, but 'Use this tested BusCalc worksheet when the task matches its inputs and scope' is filler that consumes prime front-loaded space without informing the agent. The whole definition is short enough that nothing is badly bloated, but the ordering puts boilerplate before substance.

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 no output schema, the description usefully sketches the return shape, and the closed-world statement clarifies data boundaries. However, for a multi-input financial calculation with a nested inputs object, it omits the method (how ownership cost per hour is derived, how salvage and life are amortized, how hours enters) and gives no guidance on assumptions or validation failures such as a rejected modelVersion.

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 description mentions no parameters at all - not purchase, salvage, life, fixed, hours, or variable - so it adds zero meaning beyond the schema. With reported coverage at 33%, the description should be compensating for the undocumented top-level fields (units, modelVersion) and does not.

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 says it recovers 'economic ownership and running cost at realistic utilization,' which conveys the general resource, but the verb is vague and the key per-hour output unit appears only in the title. It never contrasts itself with close siblings such as buscalc_fleet_cost_per_mile or buscalc_equipment_loan_payment, so an agent cannot easily tell which cost tool applies.

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 usage instruction is 'Use this tested BusCalc worksheet when the task matches its inputs and scope,' which is circular and gives no conditions for selection. The negative scoping sentence ('No prices or omitted costs are looked up; no private projects or purchases are accessed') hints at limits but names no alternatives or prerequisites.

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, destructiveHint=false, and openWorldHint=false, so the safety profile is covered. The description adds useful behavioral context: it returns named results, units, formula, assumptions, method version, and a source-page URL, and it does not look up prices or access private projects. There is no annotation 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?

The first sentence is well front-loaded and informative, and the return/boundary sentences add value. The second sentence, 'Use this tested BusCalc worksheet when the task matches its inputs and scope,' is vague boilerplate that does not earn its place. Overall it is acceptable but contains 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 usefully states what is returned: named results, units, formula, assumptions, method version, and source-page URL. Annotations cover the read-only safety profile, and the nested conditional schema carries input requirements. The remaining gap is that usage alternatives and some nested parameter meanings are not explained in the description.

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 only 33%, so the description must add meaning, and it does explain operation semantics plus fractional-inch and decimal-inch entry. However, it does not clarify the relationship between feetA/feetB and subtractFeet/subtractInches, the empty units object, or modelVersion beyond what the schema already says. It partially compensates, but not 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 specific operations and resource: add or subtract two measurements, or multiply a length by a count, in feet and inches. This distinguishes it from money/time BusCalc siblings by domain and arithmetic. It does not explicitly name sibling tools or contrast with them, so it stops short of a 5.

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

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

The only guidance is the generic instruction to use the worksheet 'when the task matches its inputs and scope.' No explicit when-not conditions or alternatives among the BusCalc siblings are given. The first sentence implies arithmetic-measurement use, but an agent must infer selection criteria.

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

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

Annotations already establish read-only, idempotent, non-destructive and closed-world behavior, so the bar is lower. The description nevertheless adds real value: it lists what is returned (named results, units, formula, assumptions, method version, source-page URL) and explicitly states that no prices or omitted costs are looked up and no private projects or purchases are accessed, reinforcing the closed-world hint with concrete 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 formula is front-loaded in the first sentence and the returns/scope sentence is substantive. The middle sentence ('Use this tested BusCalc worksheet when the task matches its inputs and scope') is filler that could be cut or replaced with actual guidance.

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 covers the computation, the return payload, and the no-lookup scope, which is reasonable for a read-only calculator with no output schema. However, for a nested-input tool with only 33% schema coverage it does not explain how to handle the reportingPeriod alignment or mixed-period costs beyond a passing mention, and it offers no routing against the similar per-hour sibling.

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 33%, so the description must carry some load, and it does clarify that costs and distance must be measured for the same period (reinforcing the reportingPeriod semantics). It adds nothing about units or modelVersion beyond what the nested schema descriptions already say. Partial compensation, 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 first sentence states a concrete verb chain and resource: sum vehicle operating, ownership and driver costs, then divide by productive miles. That makes the computed metric unambiguous. It does not, however, point at the closest sibling (buscalc_equipment_ownership_cost_per_hour) to say how the per-mile metric differs from the per-hour one, so differentiation is left implicit.

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?

Usage guidance is limited to the circular instruction 'use this tested BusCalc worksheet when the task matches its inputs and scope,' which gives no decision criteria. The one real boundary is the warning not to mistake this for cost per all odometer miles, which does help scope the metric. No alternative tool or when-not condition is named.

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, non-destructive and closed-world, so the safety profile is covered. The description adds genuinely new context: the return payload (named results, units, formula, assumptions, method version, source URL) and explicit negative scope ('no prices or omitted costs are looked up; no private projects or purchases are accessed'). It stops short of stating validation failure behavior or error modes, which matters given the version-mismatch rejection.

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 lead sentence is well front-loaded and does real work. But 'Use this tested BusCalc worksheet when the task matches its inputs and scope' is boilerplate that consumes a sentence without informing, and the closing scope sentence packs three distinct claims into one clause.

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 compensates by enumerating the return fields, and the closed-world/read-only boundary is clearly set, which suits a deterministic single-formula calculator. The remaining gap is the version-mismatch rejection path and the unexplained units parameter.

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 33%, so the description must compensate, and it largely does not. The cost and margin semantics live entirely in the schema, and the 'units' object parameter — an empty-properties object the agent might reasonably try to populate — is never explained anywhere in the definition.

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 transformation: 'Convert cost and desired gross margin into price without confusing markup.' The verb (convert), the two inputs, and the output (price) are all named, and the markup-vs-margin distinction separates it from siblings like buscalc_service_business_hourly_rate that also touch pricing.

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?

'Use this tested BusCalc worksheet when the task matches its inputs and scope' is circular — it tells the agent to use it when it applies, without saying what that looks like. No sibling tool is named as an alternative, and there is no explicit when-not condition, even though nine related calculators exist.

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

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

Annotations already cover the safety profile (readOnly, idempotent, non-destructive, closed-world), so the bar is lower. The description still adds real value by declaring the return payload — named results, units, formula, assumptions, method version and a source-page URL — and by stating that no prices are looked up and omitted costs are not inferred, which sets expectations about assumptions baked into the result. It does not mention error behavior on version mismatch, but overall it goes meaningfully beyond 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?

Four short sentences, front-loaded with the computation, then the usage caveat, then the return shape, then the scope exclusions. No restatement of the title and no filler beyond the arguably weak "matches its inputs and scope" clause.

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

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

For a tool with no output schema, the description supplies a solid account of what comes back (named results, units, formula, assumptions, method version, source URL), which is the main completeness risk. The gap is the conditional input model, which the description never explains despite the nested object and if/then branching. Otherwise adequate for a three-parameter worksheet 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 only 33%, and the description never explains the key input decision: recipeEntry selects between supplying an ingredient list versus a known batch cost, with different required fields in each branch. It also never clarifies the portions denominator or the units object. The phrase "package prices and quantities used" gestures at the ingredients path but leaves the conditional input structure entirely to 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?

States a specific verb and resource — ingredient cost of a batch and cost per sellable portion — derived from package prices and quantities used. That computation is distinct from every sibling (break-even, loan payment, fleet cost per mile), so an agent can identify it without opening the schema. It stops short of explicitly contrasting with alternatives, which keeps it out of the top band.

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 routing guidance is "Use this tested BusCalc worksheet when the task matches its inputs and scope," which is close to circular and names no alternatives. The negative scope clause (no prices or omitted costs looked up, no private projects or purchases accessed) does usefully tell the agent this is not a data-retrieval tool, which lifts it above no guidance at all. An agent still has to infer when to prefer this over sibling cost 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?

Beyond the read-only and idempotent annotations, the description usefully lists returned metadata and rules out price or omitted-cost lookups and private-data access. These disclosures clarify operational boundaries, though 'tested' adds little and no error behavior is described.

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-loads the calculation's purpose before covering outputs and access limitations. The generic worksheet recommendation and unverifiable 'tested' wording are mild boilerplate that keep it from being fully economical.

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 detailed nested input schema and safety annotations make the tool broadly callable, while the return-content summary partly offsets the absence of an output schema. Important gaps remain: the actual equation is unstated, profit is absent from the described scope, and the promised named results are not identified.

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 opening sentence relates overhead, compensation, and hours to the calculation, but largely repeats information already present in the nested field descriptions. It does not state the rate equation or explain how the required profit input contributes, so it only partially compensates for the low reported schema-description coverage.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The opening sentence clearly describes allocating annual overhead and owner compensation across billable hours, which conveys the hourly-rate calculation's purpose. It does not explicitly distinguish the tool from related costing siblings, and its scope statement omits the required additional-profit input.

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 cost-recovery scenario gives an implied use case, but 'when the task matches its inputs and scope' is generic rather than actionable selection guidance. There are no concrete prerequisites, exclusions, or alternatives among the sibling tools.

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

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

Annotations already cover the safety profile (readOnly, idempotent, non-destructive, closed world), and the description adds genuine value beyond them: it enumerates the return payload (named results, units, formula, assumptions, method version, source-page URL) despite there being no output schema. It also states that no prices or private records are looked up, reinforcing the closed-world guarantee. Minor gap: nothing about the units object being effectively empty.

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 opening computation sentence is well front-loaded, but the second sentence ("Use this tested BusCalc worksheet when the task matches its inputs and scope") is pure filler that earns no place. The output-contract sentence is dense and useful; trimming the boilerplate would tighten the whole thing.

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 calculator with no output schema, the description supplies the missing return-shape information and the computation's scope. The remaining gap is that a nested-object input with an empty units sub-schema is left unexplained, so an agent cannot be sure whether units is required or what to put in it.

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 only 33%, so the description should carry more weight; it does clarify that endDays is a day offset for the end reading and that excluded is a minutes quantity, which disambiguates the two most confusing inputs. However, the nested units object (empty properties) and the interaction between excluded minutes and a multi-day offset are never explained.

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?

"Find time between two clock readings" names a specific verb and resource, and the qualifiers "explicit end-day offset and optional excluded minutes" pin down the exact computation. The subject matter makes it unmistakable against siblings like buscalc_markup_vs_margin or buscalc_fleet_cost_per_mile.

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?

"Use this tested BusCalc worksheet when the task matches its inputs and scope" is circular and gives no real selection criteria. There is no statement of when NOT to use it or which sibling to prefer for adjacent tasks; the trailing sentence about prices and private projects describes data access, not usage routing.

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