Moonshot Lab (demo)

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

With no annotations, the description carries the full burden well: it discloses the state coverage limit (8 states), that unknowns are returned as ranges rather than point values, that each line carries a source and confidence level, and that inputs are not stored. It stops short of stating auth requirements, side effects, or what happens for a state outside the supported 8, so it is not exhaustive.

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 dense paragraph that front-loads what the tool produces and follows with boundaries and disclaimers; nothing is redundant beyond the deliberately emphatic 'not an offer, not a quote' sequence, which is short enough to justify itself.

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 does useful work describing the return shape (itemized lines with source/confidence, ranges for unknowns, a trade-in block with allowance, payoff, equity, tax credit). However, for a 13-parameter tool at 0% schema coverage with no annotations, the input side is essentially undocumented, leaving a real 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 0% across 13 parameters, and the description explains almost none of them. The trade-in clause loosely implies meaning for trade_value/payoff, but buyer_zip/city/county/state, registration_state, plate_transfer, vehicle_weight_lbs, financed, lender_name and eligible_incentive_labels are all left entirely undefined in both the schema and the prose.

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 gives a specific verb+resource ('Itemized out-the-door DEMO ESTIMATE') and scopes it precisely to real public tax and fee rules for 8 states, with an itemized structure (source, confidence, ranges, trade-in block). It does not name any sibling, so the agent must infer the boundary against get_price_breakdown or get_trade_in_scenarios rather than being told it.

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 or when-not-to-use guidance and no alternatives named, despite close siblings (get_price_breakdown, get_trade_in_scenarios) that overlap with the trade-in and tax content described here. The only usage-adjacent statements are disclaimers ('not an offer, not a quote, no payments') and a privacy note, which don't tell the agent when this tool is the right pick.

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?

No annotations are provided, so the description carries the full behavioral burden. It discloses the response's top-level contents, which is some useful context, but says nothing about read-only nature, permissions, rate limits, or pagination semantics despite exposing inventory_limit/inventory_offset.

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 dense fragment that front-loads the resource and enumerates contents without filler. The modifier 'Fictional' is unexplained but does not cost much space.

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, no annotations, and 0% parameter coverage, the description should compensate more. It hints at the return structure but omits parameter meaning and pagination behavior, which an agent needs to call this 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 0% and the description never mentions dealer_key, inventory_limit, or inventory_offset by name. The phrase 'a page of inventory' only loosely gestures at the pagination parameters, leaving the required key undocumented.

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 enumerates what a dealer profile contains (registry entity, stores, group, state rules, inventory page), which makes the resource specific and lets an agent distinguish it from list_dealers. It lacks an explicit verb and never names a sibling, so it falls 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?

There is no guidance on when to call this versus list_dealers or search_inventory, and no stated prerequisites. The only hint is that inventory is paginated, which is implied rather than explained.

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 no annotations, the description carries the full behavioral burden. It usefully discloses that the data is 'synthetic' with per-value provenance, which matters for how an agent should treat the values, but it says nothing about missing-listing behavior, permissions, or failure modes.

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 no filler; the output nature is front-loaded and the ID format follows immediately. Nothing needs trimming.

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 read tool with no output schema, the description adequately characterizes both the input form and the returned record's nature, saving the need for an output schema. It omits error/not-found behavior, which is the only notable 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 coverage is 0%, so the definition must compensate, and it does by specifying that listing_id is either 'dealer_key:VIN' or 'the urn' — concrete format information absent from the schema. It stops short of examples or validation rules, but this is meaningful added semantics for a single required param.

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 the specific resource returned ('Full synthetic listing record with per-value provenance') for the get_listing operation, so the agent knows this is a record-fetch by ID. It does not explicitly contrast itself with siblings like search_inventory or get_dealer, but the resource is 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 guidance on when to use this tool versus alternatives such as search_inventory (to find listings) or get_dealer (dealer data). The only usage-adjacent information is the accepted ID form, which is parameter detail rather than routing 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?

With no annotations and no output schema, the description carries the full burden. It does usefully disclose that the URLs are 'self-generated placeholder' images (i.e., synthetic, not real assets) and that rights notes accompany them, which is genuine behavioral context. However, it says nothing about auth needs, pagination, or whether the placeholder URLs are actually consumable.

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 efficient sentence that front-loads the resource and content. It earns its words, though its terseness is partly under-specification rather than tight writing.

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 tool with 0% schema coverage, no annotations, and no output schema, the description is thin: limit behavior, what 'types' accepts, and the shape of the returned block are all unaddressed. The rights-notes mention is a start but the definition is not complete enough for confident 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 0%, so the description must compensate. It partially does by naming media kinds (photo, video poster, spin) that plausibly map to the 'types' parameter, but it never mentions the 'types' filter itself, nor the 'limit' parameter (default 50) or the listing_id requirement.

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?

It identifies the resource (a media block tied to a listing) and enumerates the content (photo, video poster, spin, rights notes), but it is written as a noun-phrase fragment with no verb, so the action (retrieve media for a listing) is only implied. There is no media sibling to distinguish from, so the lack of differentiation is not a major issue.

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 when-to-use guidance, no prerequisites, and never names an alternative tool. 'For a listing' weakly implies listing_id must be supplied, but nothing tells an agent when this is the right call versus get_listing or search_inventory.

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 no annotations, the description carries the full behavioral burden. It discloses the categories of content returned (schema links, vocabularies, states, value-wrapper format), which is useful, but says nothing about whether this is a safe read, whether it is cached/static, cost, or permissions. The 'get_' prefix implies read-only but that is inference, not disclosure.

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?

It is a single short fragment with no wasted words, but it is not even a sentence and lacks any front-loaded framing of what the tool does. Brevity here comes from omission rather than disciplined structure.

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 and no annotations, so the description must fully define the return contract, and it only lists content categories without explaining their shape, what a 'value-wrapper format' means in practice, or how an agent should apply the result. For a zero-argument, annotation-free tool it leaves the agent without enough to use the output confidently.

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 takes zero parameters, so the baseline of 4 applies. There is no parameter surface the description needs to compensate for, and the description does not confuse the reader with nonexistent arguments.

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 (the ontology) and enumerates its contents — schema links, vocabularies, states, value-wrapper format — so an agent can infer it returns schema/metadata for the domain. But it is a noun phrase with no verb and no framing of what 'the ontology' governs or relates to, unlike concrete siblings such as get_dealer or get_listing. Purpose is inferable but not stated.

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, when-not-to-use, or alternative guidance at all. An agent could guess it is a reference/schema lookup useful before interpreting other responses, but nothing in the text says so, and no sibling is referenced. Usage is only implied, not directed.

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 no annotations provided, the description carries the full behavioral burden; the 'get_' prefix implies read-only but this is never stated. It says nothing about whether data-flag checks may cause fields to be missing or flagged, nor about freshness, required listing state, or error 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?

It is a single compact sentence with no filler, but it is a noun-phrase inventory rather than a front-loaded statement of what the tool does. The trailing 'with data-flag checks' is tacked on without explaining what that means for the caller.

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 and no annotations, so the description must cover both behavior and returns. It partially compensates by enumerating output components, but omits usage conditions, permissions, and required listing state, leaving gaps for an agent deciding whether to call 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?

Only one parameter (listing_id) and schema description coverage is 0%, so the description adds no semantics for it. However, a single self-evident identifier is a low-burden case, so this sits at the minimum-viable baseline rather than being penalized further.

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 enumerates the data categories the tool covers (price components, dealer fees, incentives, tax rules), which implies a retrieval of a price breakdown, but it never states a verb or resource ('Returns the itemized price breakdown for a listing'). It also gives no signal distinguishing it from the sibling estimate_out_the_door, which plausibly overlaps on 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?

There is no when-to-use guidance, no mention of prerequisites (does the listing need to be priced/configured first?), and no reference to alternatives such as estimate_out_the_door despite the obvious overlap. The agent must infer the usage context entirely.

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?

No annotations exist, so the description carries the full burden. It does disclose useful behavioral facts - the data is static/demo, one scenario per state, and meant to feed another tool - but says nothing about whether it is read-only, whether results change, or what a scenario record contains.

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 16-word sentence with no filler, front-loading what the tool yields and ending with the routing hint. Nothing could be removed without losing 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?

With no output schema and no annotations, the description should describe the shape of a returned scenario (fields, how many states, format), but it only gives the count-per-state and the consumer. Adequate for a simple no-arg getter, but incomplete on return structure.

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 takes zero parameters, so per the baseline a 4 applies. The description appropriately makes no parameter claims and instead explains the output payload, which is the only variable an agent needs to reason about.

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 resource - 'ready-made demo trade-in scenarios (one per state)' - and its intended downstream use, so an agent can distinguish it from inventory/listing getters. It never uses an explicit verb ('returns', 'retrieves'), but the cardinality and content are 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?

It names the consumer tool ('can be passed to estimate_out_the_door'), which implies the when-to-use context, but there is no explicit trigger condition or statement that this is only for demo/testing rather than real trade-in data. Usage is strongly implied rather than stated.

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 no annotations, the description carries the behavioral burden, and it does disclose the dataset bounds (20 dealers, 4 groups) and that the data is fictional demo content. It does not state that the call is read-only or side-effect free, though a zero-parameter list tool makes that implication strong.

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 front-loaded sentence with no filler. Every clause (count, contents, groups) conveys information an agent cannot get from the empty schema.

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 characterizes the return payload (dealers plus group and store counts, and the four groups). This is close to sufficient for a parameterless list tool, with only the read-only confirmation missing.

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

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

The tool takes no parameters, which is the baseline-4 case; there is nothing to describe. The schema is empty so the description cannot conflict with 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?

States a specific resource and enumerates what it returns (dealers with group and store counts, plus dealer groups). It is clear what the tool does, but it never contrasts itself with the singular sibling get_dealer, leaving the list-vs-single distinction to inference.

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 explicit when-to-use guidance and no mention of alternative tools. An agent must infer that this is the bulk-retrieval option versus get_dealer for one record; the description supplies no routing rule.

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 no annotations, the description carries the full burden and does disclose useful traits: the data is synthetic/fictional, the corpus is ~860 vehicles at 20 dealers, distance filtering is straight-line to the selling store, and limit is capped at 50. However, for a 20-parameter tool it says nothing about how filters combine, how offset/pagination behaves, or what the response contains, leaving significant behavioral gaps.

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?

Dense and front-loaded: purpose first, then filter semantics, then the limit cap. Nearly every clause earns its place; the parenthetical state list is slightly verbose but justifies the geographic scope, and the sentence fragments keep it short.

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 20-parameter, zero-schema-description tool with no annotations and no output schema, the description is far too thin. It omits pagination via offset, how multiple filters combine, accepted value formats for make/model/trim/body_style/drivetrain, and any indication of what results look like, leaving an agent to guess on most of the surface area.

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 0%, so the description must compensate, and it only covers about four of twenty parameters. It does add genuinely useful enum values the schema lacks (condition: new/used/cpo; sort: price_asc/price_desc/year_desc/mileage_asc/distance_asc) and explains the zip+radius_miles relationship and the limit cap, but make, model, trim, year range, price range, body_style, drivetrain, fuel_type, dealer_key and offset are entirely undocumented.

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 (search) and resource (inventory), and scopes it precisely with dataset size, dealer count and the eight states covered. It does not explicitly contrast itself with siblings like list_dealers, but the verb+resource pairing is unambiguous and no other search tool exists.

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 tool is obviously the search entry point, and the description enumerates condition and sort values, plus the zip+radius_miles pairing. There is no explicit when-to-use, when-not-to-use, or named alternative (e.g., list_dealers vs search_inventory), so the guidance stays at the minimum-viable level.

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