event-synoptic

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 mentions included info (ratings, hours, happy hour details, links) but does not disclose any side effects, limitations, or error behavior. It gives adequate but not deep transparency.

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 two sentences long, front-loaded with the verb 'Find', and conveys all key capabilities without unnecessary words.

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

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

Given 6 parameters, no output schema, and no annotations, the description covers the main use cases and return info. It lacks details on parameter constraints and error handling but is overall sufficient.

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

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

Schema description coverage is 33% (only 2 out of 6 parameters have descriptions). The description adds context for vibe and happy_hour_now but does not fully compensate for the missing parameter documentation.

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 clearly states the tool finds bars and nightclubs in Los Angeles with specific filters like vibe, location, and happy hour. It distinguishes itself from sibling tools that focus on events or tickets.

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 provides clear context for when to use the tool (finding bars with various criteria). It does not explicitly state when not to use it or offer alternatives, but the purpose is well-defined.

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 of behavioral disclosure. It explains inner workings such as the `free.today`, `free.label`, `free.next`, and `free.rules` fields, notes that free rules depend on the 'current LA date' (time-zone relevant), and lists additional return data (hours, open-now, visit length, quietest time, prices, links). This goes well beyond the schema and gives a detailed picture of 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?

The description is somewhat lengthy but is well-structured: it opens with the core purpose, then highlights two key differentiators with examples, and ends with a list of additional data points. Every sentence adds value, though it could be tightened without losing meaning. The front-loading is effective.

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

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

For a tool with no output schema, the description does a good job of enumerating return fields and filtering semantics. It covers free admission details, exhibitions, hours, open-now status, visit duration, quietest time, prices, and links. Missing details like pagination or error handling are non-critical for a finder tool, and the explanation of free rules is particularly thorough.

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 50% (type, limit, free_today have descriptions; lat, lon, open_now do not). The description adds meaningful context by enumerating museum types (matching the enum) and elaborating on the free-today concept. However, it does not explain lat/lon or open_now, nor does it fully compensate for the missing schema descriptions on those parameters. It provides partial value but leaves gaps.

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 begins with a specific verb and resource: 'Find Los Angeles museums and galleries'. It then lists concrete categories (art, history, science, film, kids, cars, gardens, photography) and highlights unique capabilities (free admission rules, exhibition schedules) that clearly distinguish it from sibling tools like find_bars or get_best_ticket_prices.

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 provides strong context for when to use this tool: 'Answers the two questions ticketing APIs cannot' (free admission and current exhibitions). This implies a contrast with ticketing-related tools such as get_best_ticket_prices, though it does not explicitly name alternatives or state when NOT to use it. The guidance is clear but not fully 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?

No annotations are provided, so the description carries the full burden. It discloses that Gametime prices are fetched LIVE and results are sorted, but fails to mention error handling, authentication needs, or the read-only nature. Adequate but not comprehensive.

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 two sentences with no redundancy, front-loading the core purpose and adding key details about live pricing and sorting. Every word 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?

Given the simple nature of the tool (1 param, no output schema), the description covers the main purpose and key behaviors. However, it lacks explanation of the parameter semantics and return format (what the buy links contain). Adequate but with clear gaps.

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% for the single parameter event_id. The description does not explain what event_id is, its format, or how to obtain it (e.g., from get_event). This is a critical gap as the agent has no guidance on providing a valid input.

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 clearly states the tool compares ticket prices across multiple named marketplaces and returns buy links sorted cheapest first. This specific verb+resource combination distinguishes it from siblings like get_event (event details) or search_events (event discovery).

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 implies the tool is for comparing ticket prices across marketplaces but does not explicitly state when to use it versus alternatives, nor does it mention when not to use it or any prerequisites. Usage is clear from context but lacks explicit 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, and the description only says 'full details' without specifying what those details are. It lacks information about permissions, rate limits, error behavior, or response structure, which is critical for a tool with no output schema.

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 sentence with no wasted words. It is front-loaded with the action and identifies the parameter source efficiently.

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?

Despite being a simple tool with one parameter, there is no output schema and the description does not clarify what 'full details' includes. The tool would benefit from describing the return format or common fields. Siblings provide context but the description is incomplete.

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 schema has one parameter 'id' with type string, and description coverage is 0%. The description adds no extra meaning beyond 'by its id', such as format, source, or constraints. It does not compensate for the lack of schema descriptions.

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 clearly states the verb ('get'), resource ('event'), and method ('by its id'). It distinguishes from sibling tools like search_events (which returns multiple events) and other tools.

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 explicitly says 'from search_events results', indicating a workflow where search_events is used first to obtain IDs. This provides clear when-to-use guidance, though it doesn't mention when not to use it or 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, the description carries the burden. 'List all' clearly conveys a read-only, non-destructive operation. It enriches context by explaining that the output represents the controlled vocabulary shared across sibling tools, which is useful behavioral context.

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, well-structured sentence that immediately states the action (List), the object (all taxonomy tags), and the purpose (used by other tools). No filler or redundancy.

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 parameterless list tool, the description covers the essential scope (types of categories) and the relationship to sibling tools. It could mention the output format (e.g., grouped list or labels), but that is not critical given the low complexity.

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 has zero parameters, so the baseline is 4. There is no schema information to clarify, and the description appropriately does not attempt to invent parameter details.

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 'List' and identifies the exact resource: all event category tags, bar/club vibe tags, kid-place categories, and museum types. It clearly distinguishes from sibling tools by positioning it as the shared taxonomy reference for the other tools.

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 states the taxonomy is 'used by the other tools', implying it is a reference for obtaining valid tag values before using find_bars, find_museums, or search_events. This gives clear context, though it does not explicitly name alternatives or provide exclusion criteria.

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

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

With no annotations, the description fully carries the burden. It details the returned JSON fields (venue, date, price-from, artists, tickets link), explains the meaning of rating and popularity scales, clarifies badge semantics with an explicit exclusion ('not a nightclub's free-before-11pm promo'), and documents the market block for #markets events. This goes well beyond a simple 'search' declaration.

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 ~250 words, which is long but front-loaded and well-structured: purpose -> return format -> rating/popularity -> filters -> badge -> #markets. Every section adds distinct information, though the 'Filter by...' sentence is somewhat redundant with the schema, making it slightly less concise than ideal.

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?

Despite no output schema, the description covers the key return fields, the rating/popularity semantics, and the special market block. It clearly articulates unique capabilities (badge, #markets) and when they matter. For a search tool with 12 optional parameters and no annotations, this is comprehensive.

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 83%, so baseline is 3, but the description adds meaningful value: it explains the #markets tag in depth (flea/vintage/night markets, market block contents), clarifies badge values with examples and exclusions, and summarizes the filter parameters. This compensates for the two undocumented parameters (free_only, max_price_usd) and exceeds baseline.

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 'Search upcoming Los Angeles events' — a specific verb and resource. It enumerates event categories, states the return format, and the unique badge/#markets features distinguish it from siblings like whats_on_tonight, get_event, find_bars, and find_museums.

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 clear context for when to use this tool: it calls out badge filters as covering 'audiences no other catalogue indexes' and #markets as 'a category absent from every ticketing feed'. It doesn't explicitly name alternative tools or provide 'when not to use' guidance, but the uniqueness signals are strong.

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 provided, so the description must carry the burden. It discloses time filters (events until ~6am, bars with happy hour now) but fails to mention output behavior, location dependence, or lack of results handling.

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 efficient sentence with no fluff, but its brevity sacrifices completeness, particularly regarding parameters.

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

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

For a tool with 2 unannotated parameters and no output schema, the description lacks essential details about inputs, output format, and edge cases, making it insufficient for reliable agent 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 description coverage is 0% and the description does not mention the lat/lon parameters at all, leaving their meaning and usage completely unspecified.

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 clearly states the tool returns a combined list of top events and bars for tonight in LA, distinguishing it from sibling tools like find_bars or search_events.

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 implies usage for tonight's combined events and bars, but does not explicitly state when to avoid this tool or mention alternatives beyond the implicit sibling distinction.

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