Jewelry by Sweet Pea Products

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

No annotations are provided, so the description bears full responsibility. It indicates 'live details' but does not disclose failure behavior (e.g., returns null if SKU not found), authentication requirements, or rate limits. The description is 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?

The description is a single, front-loaded sentence that clearly states the purpose and scope. Every word is necessary, 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?

For a simple one-parameter lookup tool with no output schema, the description covers the main fields returned. It lacks mention of error handling or pagination, but those are less critical. Minor gap: does not state if it returns a single object or null.

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 description adds little beyond the schema. It confirms the parameter is the SKU but does not provide additional semantic guidance (e.g., format, common prefixes). Baseline 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 ('fetch') and resource ('product by SKU'), and lists key fields (price, availability, sizes/variants, URL). It distinguishes from siblings like search_products (which likely returns multiple results) and get_store_policies (unrelated).

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 use when you have a SKU and need live details, but does not explicitly state when not to use it or mention alternatives like search_products for queries without a SKU.

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. The description lists the categories of information (shipping, returns, warranty, etc.), which is adequate for a read-only information retrieval tool. It does not contradict 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 a single sentence that efficiently lists the key policy areas and the store name. No wasted words, front-loaded with the main topics.

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 parameters and no output schema, the description adequately conveys what the tool returns. It does not specify output format (e.g., text vs. structured data), but for a simple policy listing, it 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?

There are no parameters, so the input schema is fully covered. With 0 parameters, baseline 4 is appropriate; the description adds no parameter info, which is unnecessary.

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 store policies including shipping, returns, warranty, etc. for 'Jewelry by Sweet Pea'. It distinguishes from siblings: get_product returns product details, search_products searches products, while this tool provides store policies.

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

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

The description implies usage context: when store policy details are needed. It does not explicitly state when not to use or name alternatives, but the sibling tools are sufficiently different, making the use case 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, but description discloses 'live' nature, return fields, and query behavior. Does not mention rate limits or auth, but as a search tool, these are less critical. 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 sentences with no filler. First sentence covers purpose and output; second gives guidance. Front-loaded 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?

For a search tool, description explains output fields (name, SKU, price, etc.) and input constraints (max_results). No output schema needed. Could mention default results or pagination, but not essential.

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 covers both parameters with descriptions. Description adds value with query style advice ('best queries are short and specific') and examples, going 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?

Clearly states 'live search of 100,000+ fine-jewelry products' with specific verb and resource. Distinguishes from siblings (get_product, get_store_policies) by focusing on multi-result search.

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

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

Provides query tips ('short and specific', examples) and implies use for broad searches. Could explicitly compare to get_product for single-item lookups, but sibling names offer context.

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