audioknihy.cz Catalog

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

Annotations already declare readOnlyHint=true, idempotentHint=true, destructiveHint=false. The description adds specific details: it lists exactly 35 genres and includes audiobook counts, which enriches the behavioral context beyond 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?

Two concise sentences, front-loaded with the most important information ('List all 35 Czech audiobook genres with audiobook counts'). Every sentence is meaningful and efficient.

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 zero parameters and the presence of an output schema, the description adequately explains what the tool returns (genres with counts) and its role as an entry point. No 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?

The input schema has zero parameters, so schema coverage is 100%. Description adds no parameter information, but none is needed. Baseline score 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?

The description clearly states the tool lists all 35 Czech audiobook genres with counts, and positions it as a discovery entry point before drilling into a specific genre. This distinguishes it from sibling tools like search_audiobooks or get_audiobook.

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 'Discovery entry point — agents enumerate genres before drilling into a specific one,' providing clear guidance on when to use it. It does not explicitly state when not to use it, but the context 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?

Annotations already indicate read-only and idempotent behavior. The description adds context by specifying the return structure (price, format, last-seen timestamp per partner), which helps the agent understand the output without contradicting 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 two sentences, front-loading the purpose and then detailing the return fields. Every sentence is informative with no 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 tool's simplicity (2 parameters, output schema present), the description sufficiently covers purpose, parameters, and return structure. It is complete for the agent to correctly select and invoke the 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 coverage is 100%, so the schema defines parameters well. The description adds value by tying the two slugs together to identify 'one audiobook', clarifying the relationship between parameters beyond individual 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 'compare' and resource 'price comparison table across every active retail partner for one audiobook', and specifies what is returned. It distinguishes from sibling tools like find_cheapest_offer or get_price_index by emphasizing a full comparison.

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 obtaining a comprehensive price comparison, and suggests agents can then rank or filter. However, it does not explicitly state when not to use this tool or mention alternative tools like find_cheapest_offer for a single lowest price.

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 indicate read-only and idempotent. Description adds that it returns only the lowest-price active offer and compares across all partners, providing useful context beyond 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?

Two concise sentences with no wasted words. The first sentence delivers the core purpose; the second adds a distinguishing USP.

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?

Complete for a simple lookup tool with full annotations and output schema. Description clearly explains scope and uniqueness.

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 parameter descriptions. Description does not add semantic details beyond the schema, meeting the 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?

Clearly states it finds the lowest-price active offer for an audiobook across all affiliate partners. The USP differentiates it from siblings like compare_all_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?

Implies use when cheapest offer is desired, but does not explicitly mention when to use alternatives like compare_all_offers for all offers.

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=true, idempotentHint=true, destructiveHint=false, so description adds value by specifying the returned fields and mentioning 'active offers across retail partners', which provides behavioral context beyond what annotations convey. No contradictions.

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 with the purpose and efficiently lists the returned fields 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?

For a tool with 2 required parameters, high schema coverage, and an existing output schema, the description completely covers what the tool returns. It lists all key fields and mentions offers, which is sufficient for an agent to understand the 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 description coverage is 100%, with both work_slug and author_slug already having detailed descriptions and examples. The description's mention of 'by author + work slug' adds no new meaning, so a baseline of 3 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?

The description uses a specific verb ('get') and resource ('audiobook detail'), and clearly lists the returned fields (title, description, cover, runtime, ISBN, genres, narrator, publisher, offers). It distinguishes from sibling tools like search_audiobooks and compare_all_offers by focusing on retrieving full detail for a specific audiobook via slugs.

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 when you have the author and work slugs, but does not explicitly state when to use this tool over alternatives like search_audiobooks or when not to use it. No exclusions or comparisons to siblings 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?

Annotations already declare readOnlyHint=true and idempotentHint=true, so the safety profile is covered. The description adds value by specifying that ratings are attributed to a third party (databazeknih.cz) and explaining what each ranking mode means (e.g., 'lowest live price among genuinely reviewed audiobooks'). This enriches the agent's understanding of the output.

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: the first states the core functionality and lists the options; the second provides usage context. No filler, no repetition. Every word serves a purpose. Front-loaded with key 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?

Given the tool's low complexity (2 params, enum-based, with output schema), the description fully covers what the agent needs. It doesn't need to explain return values because the output schema exists. The description is self-sufficient for this simple catalog-listing 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 coverage is 100%, so the schema already documents both parameters. The description elaborates on the 'ranking' enum values with brief explanations (e.g., 'biggest-drops' - largest recent price drop), adding context beyond the enum labels. The 'limit' parameter is not described further, but the schema already covers it; thus the description adds moderate 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 specifies a clear verb ('get') and resource ('audiobook rankings'), enumerates the four ranking modes (cheapest, best-rated, biggest-drops, price-floor), and explicitly distinguishes from single-title tools by stating 'span the whole catalog, not a single title.' This leaves no ambiguity about the tool's scope.

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 tells when to use: 'Use for "best Czech audiobooks to buy now / cheapest / most discounted" queries that span the whole catalog.' It also implicitly excludes single-title queries, guiding the agent to other tools like get_audiobook. This provides clear when-to and when-not-to 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?

Annotations already declare readOnlyHint=true, idempotentHint=true, and destructiveHint=false. The description adds value by specifying what is returned (biography, photo, country, full list of audiobook editions), which is beyond the annotations. No contradictions.

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, front-loaded with the core purpose, then expanding on details. Every sentence adds value: first sentence states what it returns, second sentence lists fields. 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?

Given the presence of an output schema (not shown but indicated), the description adequately covers return fields and parameter semantics. It does not mention that the slug is required or that it uniquely identifies an author, but the schema handles that. Overall, it is complete for this 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% (slug parameter has a description). The description adds context: slug is discoverable via search_audiobooks and includes an example ('stephen-king'). This adds meaning beyond the schema's pattern constraint, justifying a score above baseline 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 clearly states that the tool returns an author profile along with their audiobook works, listing specific fields (biography, photo, country) and the full list of audiobook editions. It distinguishes this tool from siblings like get_narrator and search_audiobooks by specifying the scope (author profile + works).

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 indicates when to use: when you need an author's profile and their works. It does not explicitly state when not to use or provide alternatives, but the sibling list (e.g., search_audiobooks, get_narrator) helps differentiate. The context is clear but lacks explicit exclusions.

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 and idempotentHint, so the description's behavioral disclosure is minimal. It adds no additional behavioral traits beyond the annotations, which is acceptable but not enhanced.

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, no redundancy. The first sentence states the purpose concisely, the second adds valuable cultural context. 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 low complexity (1 param, output schema present), the description fully covers the tool's functionality and context. The agent has enough information to invoke it correctly.

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 provides full coverage with a detailed parameter description (slug pattern, example, discovery). The tool description does not add further meaning beyond the schema, meeting the baseline for high coverage.

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 narrator profile plus their audiobooks, distinguishing it from siblings like get_audiobook or get_author. It includes cultural context that helps the agent understand the tool's relevance.

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 when narrator matters (Czech listeners choose by narrator), but does not explicitly state when to avoid this tool or suggest alternatives among siblings. No exclusive conditions 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?

Annotations already declare readOnlyHint=true, idempotentHint=true, and destructiveHint=false, so the description does not need to restate safety. It adds context about the data being 'original-research' and 'citable,' but does not disclose any additional behavioral traits like potential delays or data 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?

The description consists of two sentences covering tool purpose, output content, and data nature. Every word adds value with no redundancy or irrelevant details.

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 zero parameters, a full output schema (assumed sufficient for return values), and comprehensive annotations, the description provides all necessary context. It fully explains the tool's purpose and expected 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?

The tool has zero parameters and 100% schema coverage, so the description is not required to document parameters. However, it does describe the output content (which fills in what the schemaless input lacks), earning a baseline of 4.

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 cross-store price index for the Czech audiobook market, listing specific statistics (median/avg lowest price, savings, cheapest store, per-genre stats). The phrase 'original-research aggregate' distinguishes it from sibling tools that focus on individual offers or trends.

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 obtaining aggregate market data, not for comparing specific offers or finding individual cheapest prices. However, it does not explicitly state when to use this tool over siblings like 'compare_all_offers' or 'get_price_trend'.

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, and destructiveHint false. The description adds value by disclosing the null return case ('when there is no recorded history') and listing the output fields. However, the phrase 'currently-displayed cheapest offer' is ambiguous—it could depend on user context, which is a minor gap.

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 efficient sentences. The first sentence front-loads the key output fields, and the second provides the usage intent. Every word earns its place; no redundancy or fluff.

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 an output schema exists (not shown but indicated), the description adequately covers the return values. It explicitly mentions the output fields and the null-case behavior. The only minor gap is clarifying 'currently-displayed,' but overall it is complete for a read-only trend 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?

The input schema has 100% description coverage, so the schema already fully documents each parameter. The description does not add additional meaning or constraints beyond what the schema provides, meeting the baseline expectation.

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 what the tool does: returns price history data (window min/max, current price, % drop, floor, raw points) for the cheapest offer of an audiobook. It also provides a concrete use case ('is this a good price right now / has it dropped?'), distinguishing it from siblings like get_price_index which likely covers broader indices.

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 tells when to use the tool ('Use to answer...'), giving clear context. It does not list when not to use or mention alternatives, but the use case is specific enough to differentiate from 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?

Annotations already provide readOnlyHint, destructiveHint, idempotentHint. Description adds that the tool returns display name, audiobook count, and list of works. No contradictions; adds context about Czech audiobook publishers.

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 with no redundancy. Purpose is front-loaded; every phrase adds essential context.

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?

Output schema exists, so return values are covered. Description provides necessary context (Czech publishers, slug resolution). No gaps given the parameters and annotations.

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%. Description adds value by providing an example slug ('tympanum') and explaining that the slug is discoverable from an index page, aiding agent understanding.

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?

Clear verb 'resolves' and specific resource 'publisher slug' to its profile. Description distinguishes from sibling get_* tools (e.g., get_author, get_narrator) by focusing on publishers and their audiobooks.

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?

Description implies when to use: when a publisher slug is known. Mentions discoverability via the index page. However, lacks explicit when-not-to-use or comparisons to alternatives like search_audiobooks.

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 the tool as read-only, idempotent, and non-destructive. The description adds no further behavioral details, such as response size or rate limits, which would be useful but are not critical given the simple nature of the 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?

The description is two sentences long, front-loading the purpose (list active partners with counts) and then adding essential usage context. Every sentence is informative and there is no fluff.

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 simplicity (no parameters, output schema present), the description fully covers what the tool does and when to use it. No additional information is needed for effective agent usage.

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 no parameters, and schema description coverage is 100%. With zero parameters, the description does not need to add parameter semantics; the baseline score 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?

The description clearly states the tool lists active retail partners with audiobook counts, specifying both the verb 'List' and the resource. It is distinct from sibling tools, which focus on browsing genres, comparing offers, or getting specific entities.

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 states when to use the tool: for transparency/disclosure about how the site monetizes recommendations. It provides clear context, though it does not mention when not to use or alternative tools.

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 provide readOnlyHint, idempotentHint, and destructiveHint=false. The description adds valuable behavioral details: full-text + fuzzy search, Czech diacritics normalization, and the dataset size (12,367). No contradictions.

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 key information. Every sentence adds value with no redundancy or fluff.

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 full annotations and schema, the description is complete. It explains purpose, usage, and behavioral nuances, and the output schema (not shown) is stated to exist, so return values are covered. Sibling tools also provide context.

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 clear descriptions for both parameters (query and limit). The description does not add parameter details beyond the schema, but this is not necessary since schema already covers semantics. Baseline 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 clearly states the tool performs full-text and fuzzy search across Czech audiobooks by title, author, and narrator. It specifies the verb 'search' and resource 'audiobooks', and distinguishes from sibling tools like browse_genres and search_by_filters.

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 'Use when an agent needs to resolve a free-form query into one or more audiobook records,' providing clear context. However, it does not mention when not to use or explicitly name sibling alternatives, though this is implied.

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=true, idempotentHint=true, and destructiveHint=false. The description adds value by disclosing that year_min and year_max are accepted but skipped in V1, and partner_slug will throw if set. This goes beyond annotations to warn of current limitations.

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 pack essential information: purpose, usage context, and version capabilities. 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 the tool's complexity (7 parameters, versioning, output schema exists), the description covers the key behavioral aspects. It doesn't detail how filters combine (likely AND), but that is implied by 'combine'. The output schema handles return values, so omission is 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%, so parameters are well-documented structurally. The description adds semantic context: it names the filter categories (genre, narrator, max price, year range) and explicitly warns that partner_slug is reserved and will throw. The post-filter behavior of price_max_czk is also clarified.

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 multi-facet search of audiobooks with structured constraints, distinguishing it from the free-form sibling tool 'search_audiobooks'. The verb 'search' and resource 'audiobooks' are specific and unambiguous.

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 tells when to use: 'Use when an agent has structured constraints rather than a free-form query.' It also provides version caveats (V1 vs V2), guiding the agent away from using the partner filter prematurely.

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