Fold Laboratories Art Catalogue

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

With no annotations, the description carries the full burden and does well: it discloses that availability is transient, that impressions can sell between search and checkout, and that calling this check prevents offering sold originals. It does not describe the exact return shape or error behavior, but the core read-only re-check behavior is clearly conveyed.

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 padding: purpose and timing are front-loaded, the reason is given, and the actionable directive closes the description. 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?

The definition fully covers when and why to call the tool, and the single parameter is fully documented in the schema. However, with no output schema, the description could briefly clarify what the response indicates for each listing, e.g., whether it returns per-listing availability or throws on sold impressions.

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%, giving the baseline of 3. The schema already documents listing_ids and even ties it to get_artwork; the description adds no additional parameter-level detail, but none is needed given the clear 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 uses a specific verb and resource: 'Re-check whether specific impressions are still purchasable.' This clearly distinguishes it from the siblings get_artwork and search_artworks, which handle retrieval/discovery rather than post-search availability confirmation.

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

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

It gives explicit timing: 'immediately before presenting them to a buyer or attempting a purchase,' plus a strong ALWAYS directive before offering an impression. It explains the market context (unique/small editions can sell between search and checkout), though it does not explicitly state when not to use the tool or name alternatives.

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

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

With no annotations, the description carries the full burden of behavioral disclosure and succeeds. It explains that null means 'unspecified rather than estimated,' clarifies that AP/PP/BAT are separate objects from the numbered run with different pricing, and reveals that image URLs are temporary with an `expires_at` that must be honored. These are critical behavioral traits beyond a simple 'get detail' statement.

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 main purpose is front-loaded in the first sentence, with each subsequent sentence adding a distinct and necessary caveat: impression structure, null semantics, temporary URLs, and usage instruction. Despite its length, there is no redundancy and 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 single-parameter read tool with no output schema, the description provides all necessary contextual information: field enumeration, edition nuances, null handling, temporary URL behavior, and usage timing. Nothing critical is missing for an agent to invoke the tool correctly and interpret its response.

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 already provides full coverage for the single `artwork_id` parameter with the description 'artwork_id from search_artworks.' The tool description reinforces that the parameter targets a specific artwork but adds no new format, constraints, or semantics beyond the schema. This aligns with the schema coverage baseline of 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 opens with 'Full detail for one artwork' and enumerates the exact fields returned (attribution, medium, dimensions, edition structure, provenance, seller, impressions). This is a specific verb+resource that clearly distinguishes get_artwork from the sibling search_artworks (list/search) and check_availability (availability check). An agent can determine this tool's role without opening any 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?

The description explicitly states 'Use this before presenting a work to a buyer', giving a clear when-to-use context. It does not explicitly name alternatives or state when not to use it, but the sibling distinction is otherwise clear and the context is actionable.

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 carries the full burden, and it is highly transparent. It discloses that matching is semantic-only, budgets in query text are ignored, authenticity cannot be filtered, works taken off sale are never returned, null attribute semantics, and the importance of checking the completeness field for partial scans.

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 dense and front-loaded with the core purpose, then lists important caveats. Nearly every sentence earns its place, but it repeats the 'works taken off sale are never returned' detail already present in the include_sold schema, and the repeated IMPORTANT emphasis makes it slightly longer than necessary.

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 and no annotations, the description covers the essential operational context: response verification fields, sold and off-sale behavior, seller-stated attribute caveats, the partial completeness warning, and price filtering. An agent has enough information to call this tool correctly and interpret results safely.

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 adds real meaning beyond the schema by explaining that the query matches on meaning, that embedded budgets are ignored, and that price must be passed via min_price_usd and max_price_usd. This exceeds the baseline but does not deeply elaborate every parameter.

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

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

The description opens with a specific verb and resource: 'Search original artworks by natural-language description of what the buyer wants.' It adds meaningful differentiation from keyword search by explaining semantic matching, which also distinguishes it from the sibling tools check_availability and get_artwork.

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

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

The description gives clear context for when to use semantic search and provides guidance for passing budgets via price parameters and when to use seller_stated_tags_only. However, it never explicitly addresses alternatives like check_availability or get_artwork, leaving tool selection against siblings to be inferred from names.

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