LasVegasTonight.com — Nightlife, Shows, Sportsbooks & VIP Math

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 describes browsing active threads and gives price/audience context, but it does not clarify whether the operation is read-only, what 'join' would do, whether authentication or prerequisites are required, or what happens after joining.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is a single front-loaded sentence with no obvious filler. It is information-dense, but the long parenthetical list of thread types makes it slightly harder to scan than a more structured breakdown would be.

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 two-parameter browse tool, the description covers the thread categories and audience well. However, with no annotations and no output schema, it should do more to explain the 'join' action, prerequisites, and what browsing returns, and it omits the live_checkin mode.

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 schema already documents both optional filters. The description still adds meaning by mapping three mode values to human concepts: '8-way VIP booth seat splits,' '1:1 even-ratio guestlist squads,' and 'Sphere-to-club crawl crews,' though it does not mention venueSlug or the live_checkin mode.

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 and resource: 'browse active Vegas Weekend Roll Call community threads,' and it names distinct thread types. It implicitly differentiates itself from venue-search and event-list siblings by focusing on community table-share threads, though the 'join' half of the tool name is not explained.

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 audience and outcome are clear: solo travelers, couples, and small groups browsing to split tables at a stated price range. However, there is no explicit when-to-use guidance, no when-not-to-use guidance, and no mention of alternatives such as submit_vip_table_or_guestlist_hold for actually securing a spot.

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 behavioral burden. It usefully discloses the exact tax and gratuity rates applied and that LET is conditional, but never states that this is a pure side-effect-free computation, that 'venue fee' is an unspecified/assumed input, or how the total is presented (per person vs. table total).

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 that front-loads the outcome and then lists the cost components; there is no filler or restatement of the tool name.

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

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

With no annotations and no output schema, the description should clarify the return shape (per-guest vs. total spend) and how the unspecified venue fee is determined. The rate breakdown is helpful but leaves those gaps for a calculation tool whose output consumers must interpret.

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

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

Schema description coverage is 100%, so all three parameters are already documented, including the LET boolean and its club-vs-dining semantics. The description's mention of the 9.0% LET and 20% gratuity reinforces the parameters but adds no new syntax or constraints beyond the schema.

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

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

States a specific verb (calculate) and a precisely-scoped resource (out-the-door Las Vegas VIP table cost), and enumerates exactly which cost components are included. It is unmistakably distinct from the venue-search and venue-detail siblings.

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

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

The intent to convert a quoted pre-tax minimum into a true total is implied by 'true out-the-door' cost, but there is no explicit statement of when to call this rather than get_venue_details, and no stated prerequisites or exclusions. Usage is inferable but not guided.

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; 'Retrieve' and 'verified' signal a read-only, authoritative lookup and the scope (25 clubs, licensed venues) is disclosed. However, it says nothing about data freshness, whether rules vary by night, geographic/licensing caveats, or result shape — real gaps for a rules-reference tool.

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 the verb first and zero filler. It is dense — stacked marketing-style tokens ('$0', 'M/F ratio', '$0-cover bypass') make it slightly harder to parse — but every clause carries scope 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 annotations and no output schema, the description must cover behavior on its own and it only partially does. It conveys what is covered but not how results are organized (per-venue rule sets? aggregated?) or how to interpret 'verified' rules, leaving the agent under-informed about the returned data.

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

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

Schema description coverage is 100% and both parameters (mode, venueSlug) are already documented with their allowed values in the schema, so the baseline is 3. The description does not add any semantics beyond the schema, such as what a venueSlug lookup returns versus a full dump.

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 ('Retrieve') and a precisely scoped resource: guestlist M/F ratio and cutoff rules across 25 Las Vegas clubs plus complimentary house limo bypass rules at licensed gentlemen's clubs. It is unmistakable what data comes back, though it never names or distinguishes itself from siblings like get_venue_details or calculate_nevada_table_split that could plausibly overlap.

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 content scope implies when the tool applies (you want ratio/cutoff or free-limo rules), but there is no explicit when-to-use/when-not guidance and no routing to alternatives such as get_venue_details for general venue info. The agent must infer selection criteria from the resource description 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?

With no annotations, the description carries the full burden and does substantial work: it discloses the 38.875% NRS 368A.200 tax/LET/grat/fee waterfall, the 8-person split basis, the 0-100 scale, and the five sub-score inputs, plus that pricing is real-time. It omits auth requirements, refresh/caching behavior, and error cases for a missing slug.

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 front-loaded sentence with no filler, but the nested parentheticals stack the tax-waterfall and sub-score detail, making it denser to parse than necessary for the small surface area.

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 defines what each returned metric means and how it is computed, which is the critical missing piece. It could go further on result shape (e.g., whether both metrics return together) and on behavior when neither parameter is supplied.

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 already 100%, so the baseline is 3; the description adds mode-level meaning by pairing venueSlug with single-venue retrieval and vertical with top-leaderboard listing, which the schema fields alone only partially convey.

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?

Uses a specific verb ('Retrieve') and names two uniquely-defined resources (TableEstimate™ and VibeCred™) with explicit composition for each, so an agent can tell this apart from get_venue_details or calculate_nevada_table_split without opening either schema.

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 any venue or top leaderboard' signals the two operating modes (single venue vs. leaderboard listing), and the parameter names reinforce that split. It stops short of naming alternatives or stating when not to use it, so it is clear context rather than full 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?

No annotations are provided, so the description carries the full burden. It does disclose the content of the payload (skybridges, walkable dinner-to-show-to-club chains, split math) and 'Retrieve' signals a read-only operation, but it says nothing about invalid-slug behavior, result size, or how hub data relates to the per-venue tools in the same server.

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 sentence, but a badly overloaded one: a 20-item resort enumeration dominates the text while the operational guidance is buried at the end. The list is largely recoverable from the slug schema and costs the reader more than it earns.

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, no-output-schema lookup tool this covers the essentials, but it leaves unclear what a returned 'hub' actually contains field-wise and how it composes with sibling tools like get_venue_details. The cryptic 'child venue Nevada split math' clause adds confusion rather than completeness.

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 adds real semantics the schema lacks: it states that omitting the optional slug enumerates all 20 hubs and implies the slug space is the resort list. The schema only says 'Optional resort hub slug' without explaining the omission behavior, so this is a genuine addition.

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 ('Retrieve') and a well-scoped resource ('20 Las Vegas Casino-Resort After-Dark Campuses'), and the enumerated resort list makes the coverage concrete. It is not explicitly differentiated from siblings like get_venue_details or search_las_vegas_venues, and the phrase 'child venue Nevada split math' is opaque jargon that blurs rather than clarifies what is returned.

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?

'or omit slug to list all 20 hubs' gives a clear usage rule for the two modes of calling the tool. However, there is no guidance on when to reach for this hub-level tool versus get_venue_details, search_las_vegas_venues, or calculate_nevada_table_split, despite those siblings being obvious alternatives.

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 does real work by enumerating the payload (tax multiplier, table sections, door telemetry, neighbor resorts), which is the only place that return content is disclosed. It still omits error/not-found behavior, whether data is cached or date-scoped, and says nothing about auth or freshness.

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 front-loaded sentence with no filler and the action stated first. The trailing field list is long and includes opaque jargon ("2026 door telemetry"), but each clause does convey what the call returns.

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?

Adequate for a simple slug-keyed lookup, and the field enumeration compensates for the absent output schema. It leaves unresolved where slugs originate and how this tool relates to get_resort_nightlife_hub, which explicitly covers the "parent resort nightlife hub" content this one also claims to return.

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?

Single parameter at 100% schema description coverage with concrete slug examples, so the schema already carries the semantics. The description only restates "for a venue slug" without adding format, sourcing, or validation guidance.

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?

Specific verb ("Retrieve") plus resource ("full venue specifications" keyed by venue slug), which is clearly a detail-lookup distinct from search_las_vegas_venues. It stops short of explicitly naming the sibling it is not, and the long field enumeration muddies the core statement.

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

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

No statement of when to call this versus search_las_vegas_venues or get_resort_nightlife_hub, and no hint that the slug must first come from a search. The agent must infer the entry path and the boundary with the overlapping resort-hub sibling entirely on its own.

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 bears the full burden; 'List all' implies a safe read-only enumeration and it does disclose the payload contents (table multipliers and indoor bridge traffic rules). However, it does not state that the result set is static/fixed, how many events are returned, or any format details, leaving real behavioral gaps for a zero-annotation tool.

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 that opens with the verb and resource before the parenthetical detail. The long enumeration of twelve event names is bulky but earns its place by telling the agent the exact coverage of the result set.

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 annotations and no output schema, the description must carry everything, and it does define the scope of data (events plus multipliers and bridge traffic rules). It still omits return shape, ordering, and whether multipliers are per-event or per-venue, which an agent would need to plan a follow-up call.

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, so the baseline for this dimension is 4. The description correctly implies no input is needed by framing it as a full enumeration of all surge weekends.

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 ('List') and a specific resource ('major Las Vegas surge weekends'), then enumerates the event categories covered (F1, NYE, Super Bowl, CES, etc.) so the agent knows exactly what data is returned. None of the sibling tools (venue search, table split calculation, guestlist rules) overlap with this read-only event calendar, so it is clearly distinguishable.

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 only implied: an agent can infer this should be consulted when pricing or planning around a surge weekend, but the description never says when to call it versus calculate_nevada_table_split or get_venue_details, nor does it state prerequisites or exclusions. It is a plausible no-parameter lookup, but the routing guidance is left 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?

No annotations are provided, so the description carries the full load; it implies a read-only lookup and advertises a curated '119 verified' dataset with Nevada table split pricing in results, which is useful context. However, it says nothing about result ordering, pagination behavior, or what a result record contains, which matters for a zero-annotation tool.

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?

There is only one sentence, and it is front-loaded with the verb and resource, which is good. But the eight-category enumeration plus the marketing phrase 'out-the-door Nevada table split pricing' are redundant with the vertical enum and add length without disambiguating behavior.

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 three-optional-parameter search with no output schema and no annotations, the description covers scope and content but omits result shape, sorting, and how the returned pricing relates to calculate_nevada_table_split. Adequate but with clear 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?

Schema description coverage is 100%, so limit, query, and vertical are already documented with defaults and enumerated category values. The description adds no syntax, matching behavior, or filter-combination guidance beyond the schema, 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?

Specific verb (Search) plus a concrete resource (119 verified Las Vegas venues) with the covered categories enumerated, which maps cleanly onto the 'vertical' filter. It is distinguishable from get_venue_details, but the description never explicitly contrasts itself with siblings such as get_resort_nightlife_hub.

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 categories listed implicitly signal that this is the discovery/listing entry point and that no filters are required (all params optional), but nothing states when to prefer it over siblings or whether to follow up with get_venue_details. Usage is inferable 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?

No annotations exist, so the description carries the full behavioral burden, and it mostly markets data fields (DropScore™, TableEstimate™ splits, guestlist cutoff probability, Apple Music previews). It never states result ordering, whether search is case-insensitive or fuzzy, or what happens when query and artistSlug conflict — behavior an agent needs before calling.

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 front-loaded sentence with the verb and scope first, which is good structure, but it is padded with trademarked marketing terms (DropScore™, TableEstimate™) that add little selection value compared to the plain category list.

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

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

For a low-complexity search tool with three optional parameters and no output schema, the description usefully enumerates the per-entertainer data a caller can expect (ratings, stage times, splits, previews). It stops short of describing result shape or ordering, but the core is covered.

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 limit, query, and artistSlug already documented with defaults and examples, so the baseline of 3 applies. The description adds no parameter-level meaning such as how query interacts with artistSlug or how the 12/40 limit interacts with paging.

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: 'Search all 109 Las Vegas DJs, Sphere visual residencies, Strip theater concert headliners, hip-hop performers, comedians, and magicians.' The entertainer focus implicitly separates it from siblings like search_las_vegas_venues and get_venue_details, though no sibling is named explicitly.

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

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

There is no when-to-use or when-not-to-use guidance and no named alternative. An agent must infer that this is the browsing/search path for performers rather than venues, tables, or guestlist holds from the enumerated categories 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?

No annotations are provided, so the description carries the full burden of behavioral disclosure. It states that a request is sent to the VIP Desk and that a confirmation code and split sheet are returned, but it omits whether the hold is binding, what payment or commitment is implied by '$0-due-online', whether SMS or email side effects occur, and how failures are handled. For a submission tool with no annotation coverage, these are significant 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?

The description is a single long, run-on sentence with marketing phrasing such as 'real $0-due-online' and 'out-the-door Nevada split sheet'. It does front-load the core action, but the dense list of service types and promotional adjectives makes it less scannable than it could be. It is not wasteful enough to score below 3.

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 an 11-parameter submission tool with no annotations and no output schema. The description mentions the general outcome and confirmation code, but it does not provide enough behavioral or usage context for an agent to invoke it confidently in a complex VIP booking workflow. The schema covers parameters, but annotations and output structure are absent, leaving the description incomplete for a mutation-style tool.

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

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

Schema description coverage is 100%, so the schema already documents all 11 parameters. The description adds no parameter-level semantics beyond naming the request categories and outcomes; it does not clarify the roles of venueSlug, contactInput, partySize, or the optional fields. A baseline of 3 is appropriate when the schema does the heavy lifting.

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, 'Submit', and enumerates the resources: VIP table hold, guestlist entry, limo pickup, and corporate buyout. It clearly identifies the destination as the LasVegasTonight.com VIP Desk and the outcome as a confirmation code and split sheet. It does not explicitly differentiate itself from siblings such as calculate_nevada_table_split or get_free_limo_and_guestlist_rules, but the action is still clear.

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 or when-not-to-use guidance. It never says whether an agent should call this only after checking venue details or rules, nor does it mention alternatives like calculate_nevada_table_split for cost estimates or get_free_limo_and_guestlist_rules for eligibility. Usage is only implied by the verb 'Submit'.

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