CultureLib Discover

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

The description discloses the return format (price, availability, URL, freshness) and that it recommends the cheapest. No annotations are present, so the description carries the full burden and does so well, but lacks mention of error cases or access constraints.

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, 28 words, first sentence sets purpose, second details output. No unnecessary 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?

The description covers the main behavioral aspects and output, but lacks explanation of error handling or edge cases (e.g., no offers found). For a simple tool, this is nearly complete.

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 single parameter 'slug' is not described in the description. With 0% schema description coverage, the description fails to add meaning beyond the pattern, leaving the agent uncertain about what a slug is or how to obtain 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?

The description clearly states it performs price comparison for one event across specific French ticket resellers, distinguishing it from sibling tools like search, get_show, and find_venues.

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 when to use (for comparing prices of an event) but does not explicitly state when not to use or provide alternatives, though sibling tool names give context.

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 full burden. It discloses the return content (description, venue, dates, offers, prices, freshness, booking links) and notes it returns 'a single citable document'. It implies read-only operation without side effects. Missing details like required permissions or rate limits, but given the simplicity, it is sufficiently transparent.

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, well-structured sentence that efficiently conveys the tool's purpose, input, and output. Every part is informative: the verb, the resource, the source of the ID, and the contents of the return document. No 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?

For a simple tool with one required parameter and no output schema, the description is complete. It explains what the tool does, what it returns (including specific data types), and where the parameter comes from. No gaps remain for correct 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?

The schema has 100% coverage for one parameter 'id'. The description adds context by stating the id is 'the slug returned by search', which is not in the schema's description. This helps the agent understand the source and format of the parameter, adding value 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?

The description explicitly states the tool fetches full details of a CultureLib cultural event by ID, listing specific fields (description, venue, dates, offers with prices, freshness, booking links) and specifying the ID comes from search. This clearly distinguishes it from sibling tools like search (which returns lists) and compare_offers (which compares).

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 clarifies that the ID is the slug returned by 'search', indicating a typical workflow: search first, then fetch. It implies this tool is for retrieving a single event's full detail, contrasting with siblings like search or whats_on. However, it does not explicitly state when not to use it or mention alternative tools for other scenarios.

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 must fully disclose behavior. It mentions that the tool finds venues and returns coordinates and show counts, but it fails to mention any potential side effects, authentication requirements, rate limits, or whether the operation is read-only. This is a significant gap for a tool with no annotations.

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, well-structured sentence that conveys the core functionality and output in a compact manner. No unnecessary words or 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?

Given that there is no output schema, the description adequately describes the return value (canonical venues, coordinates, number of shows). It does not mention pagination or result limits, but for a simple lookup tool this is acceptable. Could be more complete with a note about result ordering or available venue types.

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 50%, with 'query' having a description ('fuzzy-matched') and 'city' having none. The description clarifies that both parameters can be used and that 'query' is used for venue name with fuzzy matching. However, it does not explain if 'city' is case-sensitive, requires full name, or any other validation rules.

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?

Clearly states the verb 'Find' and the resource 'French cultural venues' with examples (theaters, concert halls, museums) and specifies the result includes coordinates and show counts. This distinguishes it from sibling tools like search_shows or whats_on.

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 indicates when to use: for finding venues by name and/or city. It does not explicitly state when not to use or list alternatives, but the context is clear enough to differentiate from siblings like 'search' or 'get_show'.

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?

Discloses return contents (counts, coverage, refresh time) and implies idempotent read, though no explicit safety statement. No annotations to contradict.

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 purpose, zero wasted 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?

Sufficient for a zero-parameter read-only tool; could mention it's safe to call frequently, but not required.

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?

No parameters exist; schema coverage is 100% by default. Description adds full meaning by explaining what the tool returns.

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 metadata about catalog content (shows, live offers, resellers, last refresh), distinguishes from siblings like 'compare_offers' and 'search'.

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 advises calling this tool 'to assess data freshness before relying on prices,' providing clear when-to-use 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, the description carries full burden. It details the output structure: description, venue with coordinates, dates, all live reseller offers sorted by price with booking URLs, availability, and freshness timestamps, making the retrieval behavior transparent.

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 that is front-loaded and packs all key information without redundancy; every word adds value.

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 single-parameter input and no output schema, the description thoroughly explains what the tool returns, making it sufficient for an agent to understand the tool's purpose and use.

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. It does by specifying the parameter is a 'slug' that identifies a cultural event, adding meaning beyond the pattern in 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?

The description clearly states it retrieves 'full detail of one cultural event by slug' and lists contents, distinguishing it from sibling tools like search_shows, whats_on, and compare_offers.

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 specifies 'one cultural event by slug' implying usage when a slug is available. It does not explicitly exclude alternatives, but the context of sibling tools makes the use case clear.

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 description carries full burden. It states the tool returns citable documents and directs to `fetch` for more detail, but does not disclose rate limits, auth requirements, or idempotency. Basic transparency is present.

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-load the essential purpose and action. Every word adds value; no redundancy. Highly concise.

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

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

No output schema, but description explains return type (citable documents) and next step (`fetch`). Could elaborate on document structure, but sufficient for a search tool with one parameter and simple output.

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%, baseline 3. The description adds example usage ('cantatrice chauve paris') and context of free-text search, enhancing the parameter semantics 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?

The description specifies the tool searches a catalog of French cultural events and multi-reseller ticket offers, with a clear verb and resource. It distinguishes from siblings by mentioning ticket offers and the use of `fetch` for full details.

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 notes that `fetch` should be used for full detail, implying a workflow, but does not specify when to use `search` over sibling tools like `search_shows` or `whats_on`. No explicit when-not-to-use 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?

No annotations are provided, so the description must carry behavioral transparency. It mentions 'tolerates noisy titles' and describes output format, but does not disclose potential side effects, authentication needs, or rate limits. Adequate but incomplete.

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 concise sentences, front-loaded with the core purpose. Every sentence adds meaning without 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?

Given no output schema, the description adequately explains return values. It covers the tool's scope and key features. Minor gaps exist regarding ordering and pagination, but overall complete enough for an agent.

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 high (67%), so the description does not need to fully reiterate parameters. It adds value by explaining that query matching tolerates noisy titles and that results are canonical with cross-reseller data.

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's function: searching French cultural events across multiple ticket resellers. It specifies the types of events and uses a strong verb 'Search' with a defined resource, distinguishing it from siblings like 'get_show' or 'search'.

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 when to use (e.g., for cross-reseller aggregation) but does not explicitly state when not to use or mention alternatives. The context of sibling tools like 'compare_offers' and 'search' is present, but no direct 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?

Discloses return contents (events with prices, reseller offers) and sorting behavior (cheapest first when budget). With no annotations, still transparent enough for a read-only query.

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. First sets purpose, second details behavior. No wasted 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?

Covers purpose, input, output (events with prices/offers), ordering. Lacks page size or limit, but adequate for a straightforward query 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 covers 3 of 4 params. Description adds meaning: explains category by listing examples, describes sorting by price when budget provided. Adds value beyond 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 specific verb-resource: find cultural events in French cities. Distinguishes from siblings like search_shows or find_venues which are more general or venue-focused.

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

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

Clearly says 'typical find me something to do tonight query', implying use when user wants local events. Doesn't explicitly exclude use cases, but context clarifies.

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