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

With no annotations provided, the description carries the full disclosure burden. It helpfully enumerates the return shape (median, mean, stdDev, min, max, sample count, local currency), but says nothing about the cost profile of fanning out to as many as 19 countries or any rate/perf implications.

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

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

Three front-loaded sentences with no filler; the core action and scope come first. There is mild redundancy between "precise cross-country comparisons" and "cross-border price gaps," which keeps it just short of a 5.

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

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

For a 9-parameter tool with no output schema and no annotations, the description does solid work: it explains the aggregate return values, the filter parity with search_items, and the analytical purpose. Minor gaps remain around sampling cost and defaults, but an agent has enough to call 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?

Schema description coverage is 100%, so all nine parameters are already documented in the schema, making 3 the baseline. The description adds a useful cross-reference (same filters as search_items) but no parameter-level syntax or format detail beyond that.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

States a specific verb (compare), resource (prices), and scope (across multiple Vinted country sites simultaneously). An agent can immediately distinguish this from search_items, which surfaces listings rather than aggregate statistics.

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 frames the use case ("finding the cheapest market or understanding cross-border price gaps") and cross-references search_items for the shared filter set. It lacks an explicit when-not condition, but the context is clearly established.

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 caching behavior (1 hour) and the return structure. However, it does not mention idempotency, rate limits, or authentication requirements. The description adds value beyond the schema but lacks some behavioral depth.

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 main action, and every sentence adds value. It efficiently explains purpose, usage, and caching without unnecessary detail.

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 tool's purpose, return fields, caching, and integration with sibling tools. Given the simple input schema and no output schema, it provides sufficient context for an agent to use the tool correctly. Minor gaps like error handling are not critical.

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?

Input schema has 100% coverage with clear descriptions for country and query. The description does not add new semantic information about the parameters beyond what is in the schema. According to the guidelines, baseline is 3 when coverage is high, and the description does not enhance it further.

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 fetches the full Vinted category tree for a country, listing the return fields (IDs, names, parent IDs, item counts). It is specific and distinguishes from sibling tools like search_brands or get_size_groups.

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 explains when to use the tool (to get categories for a country) and how to use the output (pass categoryId to search_items/search_all_items). It does not explicitly state when not to use it or list alternatives, but the context is 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?

With no annotations provided, the description fully carries the burden. It discloses that results are cached for 1 hour and color catalogues change rarely, and describes the exact return fields (numeric ID, display name, hex code, short code, sort order).

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 four sentences, each earning its place: purpose, output details, usage, caching policy. No filler, well front-loaded.

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 fetch tool with one parameter and no output schema, the description fully covers purpose, output structure, usage guidance, and caching behavior. It leaves 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?

Schema coverage is 100% for the only parameter (country), so baseline is 3. The description does not add new detail beyond what the schema already provides about the country parameter; it only restates shared-country info from 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 clearly states 'Fetch the complete list of Vinted color options' with a specific verb and resource, and it distinguishes itself from sibling tools like get_categories or get_size_groups by focusing exclusively on color 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?

The description explicitly tells users to pass the returned IDs to search_items.colorIds or search_all_items.colorIds, showing when to use this tool vs others. It also mentions caching behavior but does not include explicit when-not-to-use statements.

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 behavioral burden and does disclose a meaningful trait: automatic fallback to HTML scraping when the JSON API is unavailable, which sets reliability expectations. It omits rate-limit, error, and permission behavior, so not a full 5.

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

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

Three tight sentences: retrieval modes first, then return fields, then the scrape-fallback caveat. Every sentence earns its place 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?

There is no output schema, so enumerating the returned fields (title, price, currency, brand, size, condition, description, photos, seller, etc.) is genuinely valuable. Combined with the input-mode and fallback notes, the definition is nearly complete; only failure/limit behavior is unaddressed.

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%, so all three parameters are already documented in the schema, including the country-required-with-itemId rule. The description restates the two modes but adds no syntax or format detail beyond what the schema provides, so baseline 3 applies.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

States a specific verb and resource ('Fetch complete item details') plus the two lookup modes (item ID with country, or direct URL), which cleanly separates it from search_items and compare_prices. An agent knows exactly what this returns without opening the schema.

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

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

Gives clear invocation context: country is required with itemId but inferred from a URL, so the agent knows how to call either mode. It stops short of stating when to prefer this over siblings such as search_items or compare_prices (e.g., used to expand a search hit into full details).

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, and it does disclose useful behavior: newest-first ordering, incremental semantics via afterId, the truncated flag, and polling guidance for perPage. It also reveals response shape (latestId) despite no output schema. It omits auth requirements and hard rate limits, which keeps it below 5.

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

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

Three sentences with no filler, and the core monitoring pattern is front-loaded right after the purpose statement. The nested parentheticals around truncated/perPage make it slightly dense to parse, but every clause is load-bearing.

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 14-parameter tool with no annotations and no output schema, the description covers the essentials an agent needs: the polling contract, the incremental cursor, the truncation signal, and the shared filter set. Left uncaptured are authentication expectations and the shape of individual item objects, which is a minor gap given the sibling tools likely define item structure.

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%, so the baseline is 3, and the description adds real meaning on top: it explains the intended afterId value (latestId from the previous call), the perPage/toggle-polling tradeoff, and which filter groups (brand, category, size, color, price, condition) are shared with search_items.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

States a specific verb and resource — fetch the most recently listed items for a search query, newest first — and its monitoring/afterId semantics differentiate it from search_items, which it names as the source of the same filter set. An agent can tell what this tool returns and how it differs from the general search sibling.

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

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

Gives a concrete when-to-use workflow: call repeatedly to monitor a search, passing the previous response's latestId as afterId, and notes that truncated:true means raising perPage or polling more often. It does not state when NOT to use it (e.g. one-off lookups should use search_items), so it stops short of full routing 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 provided, so description carries full burden. It discloses returned fields but does not mention read-only nature, authorization requirements, or rate limits. Adequate but lacks behavioral context beyond 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 concise sentences. Purpose and alternatives are front-loaded. No filler.

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, so description lists all return fields: username, active listing count, feedback score (0–1 float), total feedback count, country code, profile URL. Complete for a profile fetch 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%. Description adds value by explaining that sellerId is 'Numeric Vinted user ID, visible in profile URLs' and that country has a default of 'fr'. Provides useful context 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?

The description starts with a clear verb+resource: 'Fetch a seller's public profile by their numeric user ID.' It also lists the specific fields returned, and distinguishes from siblings by naming get_seller_feedback and get_seller_items.

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 states when to use this tool (fetch profile) and directs to alternatives for reviews and listings: 'Use get_seller_feedback to read review texts and star ratings, and get_seller_items to browse their listings.'

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 mentions 'paginated' and describes the output fields, but it does not disclose error handling, rate limits, or authentication requirements. This is adequate but not thorough.

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: first defines the tool's action and output, second provides the use case. It is front-loaded and every sentence is informative with 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 there is no output schema, the description adequately lists the return fields. It is fairly complete for a list tool, though it could mention pagination limits or ordering. Sibling tools are distinct enough.

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%, so the baseline is 3. The description does not add additional parameter meaning beyond what the schema already provides; it focuses on output fields. No extra value for 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 'Fetch paginated buyer and seller feedback reviews for a Vinted user' with a specific verb and resource. It lists the fields included, making the output clear. It distinguishes itself from siblings like get_seller and get_seller_items by focusing on feedback.

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 a concrete use case: 'Use this to assess seller trustworthiness and reliability before making a purchase.' It does not explicitly mention when to avoid using it or alternative tools, but the context is clear enough for an AI agent.

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 exist, so the description must cover behavioral traits. It mentions pagination and dynamic data ('currently for sale'), but lacks details on auth needs, rate limits, or nondestructive nature.

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, front-loaded with the primary purpose.

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

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

With complete schema coverage and no output schema, the description sufficiently explains the tool's return structure (same as search_items) and pagination. Additional details about pagination behavior are not necessary given the schema.

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 description adds marginal value by noting the return fields match search_items. Parameters are adequately explained in 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 clearly states the verb 'list' and resource 'items for sale by a specific seller', includes pagination, and distinguishes from siblings by specifying it returns the same fields as search_items.

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 explicitly mentions it is useful after finding a seller via search_items or get_seller, but does not provide explicit when-not-to-use or alternative 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?

With no annotations provided, the description must carry the full burden of behavioral disclosure. It states that results are cached for 1 hour, which is a key behavioral trait. No contradictions are present. The score reflects good transparency but a slight gap (e.g., no mention of rate limits or potential errors).

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 tightly written with no wasted words. It front-loads the purpose, explains the output structure, provides usage guidance, and mentions caching—all in a compact paragraph.

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 thoroughly explains the return structure (list of groups with IDs, captions, descriptions, and array of sizes with numeric IDs and display titles). It also explains how to use the output, making it fully complete 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?

The schema coverage is 100%, so the parameter descriptions are already present. The description adds useful context: 'size catalogues are shared across countries', which goes beyond the schema. This extra insight warrants a 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 starts with 'Fetch all Vinted size groups with their constituent size IDs and labels', which is a specific verb+resource combination. It clearly identifies the tool's purpose and distinguishes it from sibling tools like get_categories or get_colors.

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 explains how to use the output by passing size IDs to search_items.sizeIds or search_all_items.sizeIds. It provides clear context but does not explicitly state when not to use this tool or mention alternatives, which keeps it from a 5.

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 disclose behavior. It correctly describes the fetch as read-only and ordered by recency, but lacks details on authentication, rate limits, or pagination. This is adequate but minimal.

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 with no wasted words. The first sentence states the core action and constraints; the second provides usage guidance. Efficient and 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?

The description covers the main purpose and usage scenarios. Missing details about pagination behavior or result format are minor; the limit parameter and ordering are mentioned. With no output schema, the description is reasonably complete for a simple list 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%, so the baseline is 3. The description adds that scope is optional and items are ordered by recency, but these are already implied by schema descriptions. No additional 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?

The description clearly states it fetches the newest and trending items on Vinted for a given country, ordered by recency, with optional category scoping. This distinguishes it from sibling tools like search_items (general search) and get_seller_items (specific seller's items).

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 usage context: useful for discovering popular items, monitoring new arrivals, or finding deals. While it doesn't explicitly state when not to use or name alternatives, the context is sufficient given sibling tool names.

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 behavioral burden. It usefully discloses case-insensitive matching, acceptance of Vinted internal codes, and that color catalogues are shared across countries. It does not disclose what happens on unknown/invalid color names, whether matching returns partial results, or the shape of the resolved 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?

Three tight sentences with zero filler: purpose first, matching behavior second, alternative last. Every sentence earns its place and the key routing information is front-loaded.

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 and no annotations, so the description must stand alone for a two-param resolution tool. It covers purpose, accepted inputs, and the alternative path well, but leaves the return value format (e.g., a name-to-ID mapping) and failure behavior to inference.

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%, so both parameters are already documented in the schema, including the country enum and default. The description reinforces usage of the colors parameter but adds no format, validation, or error semantics beyond what the schema and its enum already state.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

States a specific verb+resource (resolve color names to numeric Vinted color IDs) and names the exact downstream parameters it feeds (search_items.colorIds / search_all_items.colorIds). This clearly separates it from search_items, get_colors, and resolve_size_ids among its siblings.

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

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

Explicitly tells the agent when to call this tool (to obtain numeric color IDs) and names a concrete alternative path: passing color names straight to search_items.color[] where they resolve automatically. The routing decision is fully spelled out.

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 and no output schema, the description carries the full disclosure burden and does well: it describes the return payload (matched IDs with their group, plus a list of unresolvable labels) and the one-to-many mapping behavior. It does not mention auth needs, rate limits, or error semantics, which keeps it from a 5.

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

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

Purpose and downstream destination are front-loaded, with the ambiguity caveat last. Four sentences, all carrying information, though the final 'Because "M" or "42"...' sentence is dense and could be tightened.

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 2-parameter read tool with no output schema, the description covers purpose, downstream usage, the shape of the return value (matched IDs + group + unresolved list), and the one-to-many behavior an agent must anticipate. Nothing essential for correct invocation is missing.

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

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

Schema coverage is 100%, so the baseline is 3. The description goes beyond the schema by explaining why the 'sizes' array can map to multiple IDs per label (labels recur across women's/men's/kids' groups) and by naming the group dimension used for filtering, adding real interpretive 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?

States a specific verb+resource ('Resolve human-readable size labels ... to numeric Vinted size IDs') and names the exact downstream consumers (search_items.sizeIds, search_all_items.sizeIds). It is clearly distinguishable from the sibling resolve_color_ids and the search_* 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?

Gives concrete downstream guidance ('pass them all to sizeIds to cast a wide net, or filter by group name if you need a specific category') and explains the ambiguity condition that produces multiple results. It lacks an explicit 'when not to use this / use X instead' clause, so it stops short of a 5.

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 and does disclose meaningful beyond-schema behavior: it paginates automatically, fetches pages concurrently for speed, and returns the same item fields as search_items. It does not cover failure modes, rate limits, or auth, which is a modest gap for a read-only 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?

Three tight sentences, front-loaded with what the tool does, then the routing rule with examples, then the concurrency note. Every sentence earns its place with no filler.

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 the essentials for a 15-parameter paginating search tool: pagination semantics, the maxItems bound, and field parity with search_items stand in for a missing output schema. Missing only operational caveats (errors, rate limits) that a heavy auto-paginating tool with no annotations arguably warrants.

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%, so all 15 parameters are already documented. The description only restates the maxItems ceiling behavior, adding little beyond what the schema provides. Baseline 3 applies when the schema does the heavy lifting.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

States a specific verb+resource (search Vinted listings) and the defining behavior (auto-paginate all results up to maxItems). It explicitly names and differentiates itself from the sibling search_items, so an agent can choose between them without inspecting schemas.

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

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

Gives an explicit routing rule — 'Use this instead of search_items when you need comprehensive results' — plus concrete examples ('find all Nike shoes under €30', 'list every item in size M from this brand'). The alternative and the condition that selects it are both named.

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 exist, so the description bears full burden. It explains the output structure but does not disclose read-only nature, rate limits, or authentication requirements. As a search tool, it is likely safe, but the description could be more explicit about behavioral traits.

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 front-loaded purpose. No wasted words. Effectively communicates the tool's action and additional integration guidance.

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 covers return fields adequately. Parameters are fully documented. Lacks behavioral disclosures (read-only, errors) but for a simple search tool, the completeness is 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 100%, providing full parameter definitions. The description adds usage context (output integration) but does not enhance parameter semantics beyond the schema. Baseline score 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 clearly states the tool searches Vinted's brand catalogue by keyword and lists the specific return fields (IDs, slugs, counts). It also differentiates by showing how to use the output with search_items, making it distinct from sibling 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?

Provides explicit guidance on using the returned IDs with search_items.brandIds or brand[] for automatic resolution. This implies when to use the tool, but lacks explicit exclusion or comparison to 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 exist, so the description carries the full burden. It usefully enumerates the return fields (compensating for the absent output schema) and notes results are paginated, but says nothing about rate limits, auth/permission needs, or the practical result cap handled only in the 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?

Three sentences, zero filler, and front-loaded: purpose and scope first, return contents second, routing guidance last. Every sentence 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?

For a 15-parameter search tool with no output schema, the description covers purpose, return fields, and sibling routing well. It stops short of documenting pagination limits and currency/price semantics, which live only in the schema.

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%, so every parameter is already documented in the schema. The description adds only the generic phrase 'rich filters' and no filter syntax or format details beyond what the schema provides, making the baseline 3 correct.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

States a specific verb and resource ('Search Vinted second-hand listings') plus scope ('rich filters across 19 country sites') and return shape. It explicitly distinguishes itself from search_all_items, so an agent can route without opening the schema.

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

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

Names concrete alternatives with the condition that selects them: get_categories for categoryId, search_brands for brand names, and search_all_items for multi-page results. This is explicit when-to-use guidance rather than inference.

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