Torgix Free Equipment Tools

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

Annotations already declare readOnlyHint, idempotentHint, openWorldHint, and destructiveHint=false, so the safety profile is covered. The description adds genuinely new context: the external dependency on NHTSA's vPIC service and the vehicle-scope restriction. It stops short of noting failure behavior for malformed VINs or any rate/availability limits of the external API.

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, front-loaded with the core action and data source, then the scope caveat. Every clause carries information and nothing is repeated.

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 and a single parameter, the description compensates by listing the return fields an agent can expect (year, make, model, body class, GVWR class, engine). Together with the annotations and the scope note, an agent has everything needed to decide and call 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 coverage is 100% and the single parameter is fully documented in the schema as 'The 17-character VIN.' The description repeats the 17-character constraint without adding format, checksum, or validation detail beyond what the schema provides, so it sits at the baseline for a fully-documented parameter.

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

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

States a specific verb and resource ('Decodes a 17-character VIN') and names the upstream data source (NHTSA's free vPIC database), then enumerates the returned attributes (year, make, model, body class, GVWR class, engine). It also scopes the tool to on-road vehicles, distinguishing it from any sibling that might handle off-highway equipment.

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?

Gives an explicit when-not rule: 'On-road vehicles only; off-highway equipment uses serial numbers instead,' which tells an agent to avoid this tool for off-highway assets. It does not name a specific sibling to route to (e.g., find_equipment_manual or equipment_cost_per_hour), so the alternative path is implied rather than linked.

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

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

Annotations already declare readOnlyHint, idempotentHint and non-destructive, so the safety profile is covered. The description adds genuinely new behavioral context: that omitted parameters silently fall back to defaults, that those defaults are echoed in the response, and that the math mirrors a named external calculator (torgix.ai/learn), which helps an agent trust and explain the output. It stops short of describing the response shape beyond 'lists the defaults'.

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, zero filler. The cost-component list comes first to establish what is computed, followed by the input contract in the same breath. Every clause 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 13-parameter, all-optional-but-two calculation tool with no output schema, the description covers the two things an agent cannot get from structured fields: the defaulting contract and where the defaults come from. A brief note on what the result object contains (per-hour total plus breakdown) would close the last 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?

Schema description coverage is 100%, so every one of the 13 parameters already has a documented meaning and default in the schema. The description only restates the required/optional split and the defaulting behavior, adding no per-parameter meaning the schema lacks. Baseline 3 applies when the schema carries the weight.

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 ('Calculates') and a precisely scoped resource ('what a machine really costs per hour to own and operate'), then enumerates the cost components covered (depreciation, cost of capital, insurance/taxes/storage, fuel, lubricants, repairs, wear parts). No sibling tool touches cost math, so the agent can route here without ambiguity.

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

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

Explicitly names the two required inputs ('Purchase price and hours per year are required') and states what happens to everything else ('anything else left out uses the calculator's defaults, which the answer lists'). This is clear operational guidance for how to call it, though it offers no when-to-use versus alternatives guidance for the broader fleet decision family (e.g., repair_rebuild_or_replace).

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 readOnly, idempotent, non-destructive, and open-world behavior, so the bar is lower; the description nonetheless adds real value by disclosing the response shape (title + link) and the negative-result behavior. The 'that library only' scope note sits slightly in tension with openWorldHint=true, but it describes corpus scope rather than world-openness, so this is a clarification rather than a 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 sentences with no filler. The resource scope and return shape come first, and the miss-handling caveat follows naturally.

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 two-parameter read-only lookup with no output schema, the description supplies what an agent needs: what corpus is searched, what comes back (title and link), and what happens on a miss. Nothing material 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 coverage is 100% and both parameters already carry examples (Bobcat, T590), so the schema does the heavy lifting. The description's phrase 'for a make and model' maps to the params but adds nothing about the fact that make is required while model is optional, leaving that 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 (finds), a precisely scoped resource (operator/service/parts manual or spec sheet for a make and model in the Discount Equipment library), and the return payload (title and link). No sibling tool does manual lookup, so the tool is easily distinguished from decode_vin, recall_lookup, and the cost/health calculators.

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?

Clearly frames the context of use: this searches the Discount Equipment library only, and the caller should expect an explicit 'nothing found' answer when the machine is absent. It does not name alternatives or prerequisites, but no sibling tool overlaps functionally, so the routing gap is small.

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 readOnly, idempotent, non-destructive and closed-world. The description adds genuinely new behavior: 'Plain rules, nothing stored' tells the agent the assessment is deterministic and retains no data, and it enumerates exactly what gets flagged (old, high hours, underused, missing info, duplicate IDs) plus a summary. It does not say how results are formatted or ordered, 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?

One dense sentence with the purpose front-loaded and no filler; the parenthetical input spec earns its space. It is slightly overloaded, packing input format, row limit, and five flag categories into a single clause chain, but nothing is redundant.

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-value burden, and it does list the flag categories and the fleet summary. The one gap is the shape of the response (structured report vs. prose), which an agent may need to know before rendering results to a user.

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 baseline is 3, but the description goes well beyond the schema: field order (make, model, year, hours), optional header row, CSV or tab-separated formats, and a 200-row ceiling that the schema's maxLength does not express. This materially reduces malformed-input failures.

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: 'Reviews a pasted fleet list ... and flags old machines, high hours ... with a fleet summary.' The scope (plain rule-based review of pasted text) is unmistakable. It never names a sibling, but the siblings (decode_vin, recall_lookup, equipment_cost_per_hour) are functionally distant enough that confusion is unlikely.

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 rather than stated: the description tells you the tool needs a pasted, line-per-machine list, which effectively defines the trigger condition. There is no explicit 'use when' framing and no mention of alternatives such as decode_vin for identifying a single machine, so the agent must infer routing.

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

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

Annotations already declare readOnlyHint=true, idempotentHint=true, openWorldHint=false and destructiveHint=false, so the safety profile is covered. The description adds that output is a consumable checklist rather than raw data, but says nothing about behavior for unrecognized equipment strings or the checklist's shape/length.

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 in the first clause, but the long run-on enumeration of ~20 equipment types followed by 'and more' is bloated and self-undermining. A tighter list or a stated coverage rule would carry the same information with less noise.

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 lookup with no output schema, the definition is adequate but thin: it never states the return format (sections, markdown, item counts) or what happens when the equipment string is not recognized. Those are the two things an agent would still need to guess.

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 a 3 is the baseline, but the description effectively supplies an accepted-value vocabulary for `equipment` (telehandler, skid steer, aerial lift, etc.) that goes beyond the schema's two examples. The `when` parameter (daily, pre-trip, annual) is echoed in the description but its interaction with equipment type is not clarified.

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: returns a ready-to-use inspection checklist for a given equipment or inspection type. The scope is concrete and easily separable from siblings like find_equipment_manual or state_compliance_requirements, though the description never explicitly contrasts itself with 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?

Usage is implied by 'for a type of equipment or inspection' and the examples (daily pre-use, DOT pre-trip, annual), which hints at the checklist-vs-requirements distinction. However, there is no explicit when-to-use/when-not or naming of the alternative tool (state_compliance_requirements) for regulatory questions.

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 safety (readOnly, idempotent, non-destructive, openWorld), so the description's job is to add context — and it does: it discloses that a VIN is decoded internally first (a hidden chained call) and that per-vehicle open-recall status is out of scope. It does not mention rate limits, result caps, or failure behavior for an invalid VIN.

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 tight sentences: capability and output fields first, scope limitation and fallback last. No filler, and the most decision-relevant constraint is not buried.

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?

There is no output schema, so it is valuable that the description names the returned fields and the internal VIN-decoding step. It remains slightly incomplete on result volume/ordering and on what happens when a VIN cannot be decoded or no recalls match.

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 the schema already documents that vin is 'used instead of year, make and model'. The description restates the either/or input modes without adding syntax or validation detail (e.g. VIN length checks, model-year formatting) beyond the schema, 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?

States a specific verb and resource ('Lists the safety recalls NHTSA has issued') and enumerates both accepted input modes — year/make/model or VIN — plus the fields returned ('campaign number, component, summary and remedy'). An agent can tell this apart from decode_vin, which is implicitly referenced by '(decoded first)'.

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?

Explicitly states a negative scope: 'It cannot say whether a recall is still open on one specific vehicle', and redirects to nhtsa.gov/recalls or the dealer. That is genuine when-not guidance, but it doesn't say when to reach for the sibling decode_vin versus passing year/make/model directly, so it stops short of full alternative routing.

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, so safety needs no restating. The description adds real behavioral context the annotations cannot: the repair is priced by the hours it buys before the next major event, and the method is documented at a specific URL. It stops short of saying what the returned decision or numbers look like, which matters somewhat since no output schema exists.

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 sentences that are front-loaded with the decision, then the pricing logic, then the two input patterns. Every sentence carries information; the URL reference is the only slightly self-serving element but it substantiates the method.

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 13-parameter analytical tool the description covers the two things an agent could plausibly get wrong: which replacement figure to supply and how rebuild differs from repair. The remaining gap is that with no output schema, the shape of the returned verdict and figures is never described.

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 13 parameters are already documented and baseline would be 3. The description goes beyond the schema by explaining the relationship between replacement_cost_per_hour and replacement_price (give either) and the rebuild input pattern, which the schema lists as independent fields without stating they are mutually exclusive routes.

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 decision ('decides whether to repair (or rebuild) a machine or replace it') plus the criterion ('by comparing cost per hour'), so the agent knows exactly what it gets. It doesn't explicitly differentiate itself from the similar-sounding sibling equipment_cost_per_hour, which is the one confusion risk.

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?

Gives concrete usage conditions: supply the replacement 'either as a cost per hour or as a purchase price', and for a rebuild 'enter the rebuild cost and the much larger hours it buys'. That resolves the main input-selection ambiguity, though it never names an alternative tool or a case where you should not 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 declare read-only, idempotent, non-destructive and closed-world, so the safety profile is covered. The description adds genuinely useful context the annotations cannot: every item carries an official source link and a checked date, the corpus is 355 cited items, and the 'not legal advice' disclaimer. It doesn't say anything about result size or pagination, keeping it at 4.

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 tightly packed sentences: what it returns, what unlocks extra checks, and provenance plus a disclaimer. The scope statement is front-loaded and no sentence is 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?

No output schema exists, and the description compensates by describing what each returned item includes (source link and checked date) and by flagging the answer is not legal advice. For a five-parameter, one-required read tool this covers everything an agent needs to invoke it correctly.

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

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

Schema coverage is 100%, so the baseline is 3, but the description goes beyond the schema by explaining the causal relationship — that providing gvwr_lbs, axles and interstate is what activates the threshold checks. It omits the category enum, which is the one parameter an agent might overlook, so it does not quite reach 5.

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 ('Lists') plus an enumerated set of resource types (registration, IFTA, IRP, DOT inspection, emissions, permits, highway-use tax) scoped to a US state/DC plus federal items. This is clearly distinguishable from siblings like inspection_checklist or recall_lookup, which cover narrower single-purpose lookups.

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?

Explicitly tells the agent to supply GVWR, axles and interstate status in order to unlock the CDL/USDOT/IFTA/IRP/Form 2290 threshold checks, which is real conditional guidance. It stops short of naming when-not to use it or a competing tool, so it lands at 4 rather than 5.

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