FrontRowTickets.com MCP Server

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

Annotations already cover the safety profile (readOnly, idempotent, openWorld, non-destructive), and the description adds real behavior beyond them: data is refreshed from the live source at call time, max_price acts as a hard gate, quantity does not reserve anything, and a gated miss returns availability:null with a note. The closing caveat that section-level price bands are unavailable sets return expectations.

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

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

Front-loaded with the core question and answer, then constraints, then alternatives, then the API limitation. It is dense but every sentence carries information; the middle clause mildly duplicates the schema's max_price and quantity descriptions, which keeps it from a 5.

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 readOnly annotations, the description carries the return-value burden itself: it names the fields returned (current availability and starting price), the gated null case, and the catalog limitation on band-level pricing. Nothing needed to call this correctly 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%, so the field meanings are already documented and the description largely restates the max_price gate and quantity-is-informational semantics. It does add one thing the schema lacks: the concrete failure shape (availability:null with a note) when the gate excludes the event, which is useful invocation context.

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 the exact question the tool answers ('can I get tickets for this event?') and scopes it to one event, with a specific verb and resource. It explicitly distinguishes itself from siblings by naming get_event (full record) and get_deals (browse by budget), so an agent can select it without inspecting other schemas.

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 gives explicit routing rules: use get_event for the full record, get_deals to browse by budget. It also states the condition under which max_price suppresses the result, so the agent knows when a null response is expected rather than an error.

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?

Goes well beyond the readOnly/idempotent/openWorld annotations by disclosing result ordering (cheapest first), a result ceiling (up to 25), the exclusion rule (events without pricing data are dropped), and the precise scope of the cap (applied per event to its starting price). These are exactly the behaviors that change how an agent interprets an empty or short result set.

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, front-loaded with the usage trigger and the cap semantics before the optional filters and the routing pointer. No redundant restatement of the tool name or title.

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 filter-driven read tool with no output schema, the description covers the input contract, ordering, result cap, and exclusion behavior. What is returned per event is not described, but that is a minor gap given the absence of an output schema and the low risk of misuse.

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 interpretive value: it clarifies that max_price is a per-event cap on starting price rather than a total-budget figure, and that city/date range act only as narrowing filters on the deal search. It does not add format detail for the date parameters, which the schema already covers.

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 the cheapest available events') plus the governing constraint (required max_price cap). It also explicitly distinguishes itself from search_events, so an agent can pick between the two without opening a 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?

Opens with the selection condition ('Use when budget is the primary filter') and names the alternative tool and its role ('Use search_events for text- or category-driven discovery instead'). Both the when and the when-not are explicit.

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, openWorldHint, and destructiveHint=false, so safety is covered. The description adds useful behavioral context beyond that: the record is 'live-refreshed from the catalog when called (cached copy otherwise),' which tells the agent about freshness and caching. It does not discuss auth, rate limits, or return shape, but the added freshness detail is meaningful.

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 purpose, then behavioral freshness detail, then routing guidance. Every sentence earns its place and the most important information comes first.

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, but the description enumerates the returned fields (venue, date, ticket count, price range, sections), covers freshness behavior, and routes to the correct alternative. Combined with rich annotations, nothing needed to call this read-only tool correctly 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 description coverage is 100%, with event_id fully documented as 'Event ID from search_events.' The description does not add syntax or format details beyond the schema, so the baseline of 3 is appropriate when structured data carries the parameter semantics.

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: 'Full details for one event,' then enumerates exactly what is returned (venue, date, ticket count, price range, sections). It explicitly distinguishes itself from the sibling get_availability, so an agent can route correctly 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?

It gives an explicit alternative and the condition that selects it: 'Prefer get_availability when the only question is can I get N tickets at or under $X.' This is a clear when-not-to-use rule plus a named sibling, leaving no ambiguity about selection.

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 readOnly/idempotent annotations, it discloses the default ordering (cheapest all-in first), that max_price is computed on all-in price including fees, and that notes pass through verbatim and must be relayed. The non-transacting nature and the filter-not-reservation caveat are exactly the behavioral facts annotations cannot convey.

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?

Purpose and ordering come first, followed by parameter clarifications, then the notes/purchase caveat — well front-loaded. It is dense, and the IMPORTANT block is long, but each sentence carries distinct guidance rather than repetition.

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, yet the description enumerates the returned fields (section, row, quantity, seat range, base and all-in price, notes, fee detail) and explains the notes field's criticality. Nothing material an agent needs to call or interpret this tool 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%, so the baseline is 3, but the description adds real meaning: max_price caps the ALL-IN price with fees, min_quantity means 'tickets together in one listing,' and quantity is emphasized as a filter, not a hold. These clarifications go beyond the schema's phrasing.

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 ('Return actual seat listings for one event') and enumerates the returned fields. It explicitly distinguishes itself from search_events, which only gives a starting price, so an agent can route between the two 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?

Gives an explicit trigger ('Use after search_events when the user wants seat options to choose from') and names the sibling it follows. It also sets boundaries — quantity is a filter not a hold, and purchasing happens via the event page url, not this tool.

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?

Goes well beyond the readOnly/idempotent annotations by disclosing result ordering (soonest first), the pagination ceiling (default 10, max 50, no further pages), and what each result carries (ticket counts and starting prices). The 'filters combine freely' note tells the agent the query model is conjunctive, which the annotations do not cover.

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, all front-loaded: what it searches, how filters and results behave, then sibling routing. No filler and no 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 output schema, the description carries the return-shape burden itself and does so — result count, ordering, and fields returned are all stated. Together with the sibling routing, an agent has everything needed to call it correctly on the first attempt.

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, and the description earns an extra point by explaining that all filters are optional and combine freely and by restating the limit's no-pagination implication. It does not add format detail for city or date fields 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?

States a specific verb and resource (search FrontRowTickets.com ticket inventory) and enumerates the filter dimensions (free text, city, date range, category). It also positions itself as the entry point ('Start here for discovery'), which distinguishes it from the more targeted 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?

Explicitly gives the default entry point plus two routing rules: use get_event for one event's full record, and get_deals when the user has a hard budget cap. That is real when-to-use guidance with named alternatives, not an implied preference.

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