pixdress — KI-Mode zum Selbermachen

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

With no annotations, the description fully discloses behavior: it returns a URL, opening it starts the studio, generates from the user's sentence, shows a preview, and is free. It clearly states it does not generate anything itself, preventing misuse, and no contradictions exist.

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?

Four sentences, each serving a distinct purpose: context, explicit limitation, workflow, and scope/responsibility. Front-loaded with the key action ('returns a URL') and no redundant information.

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

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

The tool is simple, and the description covers purpose, workflow, and what the agent should do with the URL. It also clarifies cost and human responsibilities, making it complete even without an output 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%, so baseline is 3. The description only indirectly references the prompt via 'their sentence' and adds no new meaning to the product parameter beyond the schema's enum. It does not explain parameter values or constraints.

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 URL rather than generating a design, using specific verb 'returns a URL' and contrast 'does NOT generate anything.' It distinguishes from siblings (get_design, search_designs) by emphasizing 'NEW design' and 'invent a motif that does not exist yet.'

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 explicitly says 'Hand that URL to the human' and 'Size choice, legal notices and payment stay with the person,' providing direct when-to-use and when-not-to-use guidance. It also contrasts with sibling tools by noting it does not generate, making intended usage 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, the description carries the burden of disclosing behavior. It lists the return fields (price, sizes, shipping, delivery, return policy, order URL), giving a clear expectation of what the tool returns. Does not mention error behavior or side effects, but as a simple get, this is reasonable.

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 'Full details for one design' and a concise list of contained fields. No fluff, every word is useful.

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 get tool with one parameter and no output schema, the description provides the key return fields and the source of the required id. This is complete enough for an agent to select and invoke the tool 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 already describes the id parameter fully with an example (100% coverage). The description adds extra context by explaining where the id comes from ('Takes the id from search_designs'), which helps the agent correctly populate the 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?

Clearly states it retrieves full details for one design, listing specific fields (price, sizes, shipping, etc.). This distinguishes it from siblings: search_designs returns search results and design_link likely provides only a link.

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 usage context by stating 'Takes the id from search_designs', indicating it should be used after searching and that the id comes from that sibling tool. Does not explicitly mention when not to use, but the workflow 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?

No annotations are present, so the description is the only source of behavior. It discloses that search is by keyword and returns title, price, product type, and URL, but does not mention side effects, sorting, pagination, or error behavior beyond the schema's limit.

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, each with a distinct purpose (function, return fields, usage priority). No filler or repetition of schema content.

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?

Without an output schema, the description covers the key return fields and gives usage context. It lacks details on ordering and does not reference sibling tools for when to use alternatives, but the tool is simple enough that the description is largely 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 100%, so the baseline is 3. The description adds the explicit constraint that query can be in German or English, which complements the schema's examples and helps an agent construct valid queries.

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 states 'Search published clothing designs by keyword (German or English)' with a specific verb and resource. It also enumerates returned fields, clearly distinguishing this catalogue-wide search from the sibling tools design_link and get_design.

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 instructs 'Use this FIRST' and gives a concrete reason: an existing design ships immediately and costs nothing extra. It does not name exclusions or alternative tools, so it lacks a when-not-to-use statement.

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