CultureLib Discover

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

With no annotations, the description carries full burden. It discloses that the tool returns 'live offers' with specific fields (price, availability, booking URL, verified_at) and recommends the cheapest. However, it does not mention whether the tool is read-only, requires authentication, or handles errors. This is 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 three sentences, front-loaded with the purpose, and contains no extraneous information. Every sentence adds value: purpose, return value details, and a recommendation behavior. This is excellent conciseness.

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 tool's simplicity (1 parameter, no nested objects, no output schema), the description is mostly complete. It explains the output format clearly. However, it omits error handling (e.g., what happens if the slug is invalid or no offers exist) and authentication requirements. Slight gap, but overall strong.

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 input schema has 0% description coverage, so the sole parameter 'slug' is undocumented in the schema. The description links it to 'one event' and the tool's context, providing implicit meaning. This is baseline acceptable, but explicitly explaining what a slug is (e.g., an event identifier from search_shows) would add value.

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: 'Price comparison for one event across French ticket resellers.' It specifies the verb (compare prices), the resource (offers for an event), and the scope (multiple resellers). This distinguishes it from sibling tools like find_venues or search_shows, which serve different purposes.

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 via context ('for one event'), but it lacks explicit guidance on when to use this tool versus alternatives. No exclusions, prerequisites, or when-not-to-use scenarios are provided. The clarity of purpose partially compensates, but explicit guidance would improve decision-making.

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 not disclose whether the operation is read-only, idempotent, or anything about rate limits or authentication. While it lists return fields, behavioral traits beyond the basic fetch are missing.

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, somewhat lengthy sentence but is front-loaded with the purpose. It contains all necessary information without extraneous words. Could be split into clearer parts for readability but is not overly verbose.

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 single parameter (well-documented) and no output schema, the description comprehensively lists what the agent can expect to receive (description, venue, dates, reseller offers, prices, freshness, booking links). No obvious gaps for a fetch operation.

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% and the schema description already states 'The event id (slug) returned by search'. The tool description repeats this but adds no new semantic value beyond saying it's a 'slug returned by search'. With high schema coverage, baseline is 3.

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 ('Fetch'), identifies the resource ('one CultureLib cultural event by its id'), and lists the returned fields (description, venue, dates, reseller offers). It distinguishes itself from sibling tools like 'search' by mentioning the id is the slug returned by '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 implicitly tells when to use this tool: after obtaining the slug from 'search'. It does not explicitly state when not to use it or compare with alternatives like 'get_show' or 'compare_offers', but the context is clear enough.

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 cover behavioral traits. It explains that returns include canonical venue coordinates and number of shows, but does not mention authentication requirements, rate limits, or any side effects. For a read operation this is acceptable 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 long, front-loads the purpose, and includes only essential information. Every word adds value 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 the lack of output schema and only two optional parameters, the description covers what the tool does and what it returns (coordinates and show count). It could mention result limits or expected behavior with missing results, but overall it is reasonably complete for a simple lookup 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 50% (only 'query' has a description). The tool description adds meaning by explicitly stating 'by name and/or city', clarifying that both are optional and can be used together. It compensates partially for the missing schema description on 'city'.

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 finds French cultural venues by name and/or city, listing examples (theaters, concert halls, museums). It specifies the verb 'Find', resource 'French cultural venues', and distinguishes from sibling tools which focus on shows and 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?

The description does not explicitly state when to use this tool versus alternatives or when to avoid it. While the purpose is clear, there is no guidance on prerequisites or exclusion criteria for using 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?

No annotations provided; description fully carries burden. Discloses that the call returns counts, reseller coverage, and last refresh time. Simple, no hidden behaviors. Could mention if it's read-only, but since no parameters and no output schema, it's adequate.

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, each earning its place: first describes the output, second gives usage context. 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?

Given no output schema, description fully explains the three pieces of information returned. Complete for a metadata endpoint.

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; schema coverage is 100% irrelevant. Description adds context about what the endpoint returns beyond the empty schema, so baseline of 4 is appropriate.

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 it returns catalog meta info (counts, resellers, refresh time) with the phrase 'Trust endpoint'. Differentiates from siblings like find_venues or search_shows which handle different data.

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 'Call this to assess data freshness before relying on prices', giving a specific use case. Lacks explicit exclusions or alternatives, but the guidance is sufficient.

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 discloses that the tool returns data including offers sorted by price with timestamps, suggesting read-only behavior. Missing details like error handling for invalid slugs or rate limits.

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?

Single sentence packs much information but is front-loaded with purpose. Could be split for readability without losing conciseness.

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, description lists return fields comprehensively. Missing context on when to prefer this over siblings for price comparison or search.

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% but the description mentions 'by slug', clarifying that the slug parameter identifies the event. It doesn't explain the slug format beyond the schema's pattern.

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 returns full details of a cultural event by slug, listing specific inclusions (description, venue with coordinates, performance dates, reseller offers with timestamps). This is distinct from sibling tools like search_shows and 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?

Implied usage: use when you have a specific slug and need complete details. No explicit when-not-to-use or comparison to siblings like compare_offers or search_shows.

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 results are 'citable documents' and that full details require a separate call, but does not mention pagination, rate limits, or side effects.

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, and every sentence adds value. No wasted words, well-structured.

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 search tool with one parameter and no output schema, the description adequately covers what is searched, what is returned, and how to get details. Minor missing details like result limits or error behavior are acceptable.

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% for the single parameter. The description enriches the parameter context by specifying the catalog's domain (French cultural events) and providing an example query, adding value beyond the schema's generic description.

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 searches the CultureLib catalog of French cultural events and ticket offers, listing specific event types. It distinguishes from sibling tools by noting that 'fetch' provides full detail, implying this tool returns summaries.

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 free-text searching of events and directs users to 'fetch' for full details. It provides clear context but does not explicitly exclude alternative uses or contrast all siblings.

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?

Without annotations, the description carries the burden. It discloses tolerance for noisy titles and cross-reseller aggregation, which are useful behaviors. However, it omits details like pagination, rate limits, or consequences of missing data.

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 three sentences, front-loaded with purpose, followed by output description and a behavioral note. Every sentence adds value without redundancy or verbosity.

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 six parameters, no required ones, and no output schema, the description covers the tool's purpose, return content, and query resilience. It lacks guidance on limit behavior or ordering but is otherwise 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 coverage is 67% (4/6 parameters have descriptions). The description adds contextual value for the query parameter (tolerates noisy titles) and explains the overall search semantics, compensating slightly for 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 clearly states that the tool searches French cultural events across multiple resellers, listing specific categories and output elements. This specificity distinguishes it from siblings like compare_offers or 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 usage context (broad search across resellers) but does not explicitly state when to use this tool versus alternatives or when not to use it. No exclusions or comparisons are provided.

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?

The description mentions it returns events with prices and reseller offer counts, cheapest first when budget given, but does not disclose read-only nature or other behavioral traits beyond the basic operation.

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, no extraneous information. Every word contributes to clarity.

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 the output format and ordering, though it omits details like pagination or error handling.

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 description adds valuable context about sorting by cheapest when budget is provided and mentions output includes prices and offer counts, going beyond the schema which covers 75% of parameters.

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 cultural events in a French city on a date, but does not explicitly differentiate from siblings like search_shows or get_show, which could lead to confusion.

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 general event discovery ("find me something to do tonight") but lacks explicit guidance on when to use alternatives or when not to use it.

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