Be Sew Bizzy

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

Annotations already declare read-only, idempotent, and non-destructive behavior, so the description's main contribution is return-level context. It adds value by enumerating exact fields returned, including sale price, per-yard/each, stock, colors, and description. There is no contradiction with 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?

One sentence contains all key information, leading with the resource and grouping the output fields after a colon. Every phrase earns its place, with no filler or repetition.

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 one-parameter fetch tool with no output schema, the description explains the source of the id and the full set of returned details. Annotations cover safety and idempotence, so the agent has enough context to 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?

The schema already fully documents the single id parameter at 100% coverage, including that it is an id from search results. The description reinforces this same constraint but does not add meaningful meaning beyond what the schema already provides.

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 targets a single product and enumerates the concrete return fields (price, sale price, per-yard/each, stock, colors, description), so an agent knows exactly what the tool provides. It does not explicitly differentiate from the sibling get_product, which keeps it from a 5.

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?

"By the id search returned" establishes a clear precondition: the id must come from prior search results rather than arbitrary input. It does not explicitly mention sibling tools or when not to use it, but the stated context is sufficient for most selection 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?

Annotations already declare readOnlyHint=true, idempotentHint=true, and destructiveHint=false, covering the safety profile. The description adds value by specifying the exact data returned (description, price, sale price, colors with SKU and stock), which is behavioral context beyond what annotations provide. It does not cover error handling or not-found behavior, but for a simple read-only get this is sufficient.

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, well-structured sentence that front-loads the core purpose ('One product by its slug') and then lists the return fields efficiently. Every word contributes; no filler or 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 tool with only one well-documented parameter, annotations covering safety, and a description that lists the return fields, everything an agent needs to call it correctly is present. The absence of an output schema is mitigated by the explicit list of returned data. No critical information 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?

The schema has 100% coverage for the single 'slug' parameter with an example, so the description does not need to add parameter details. The phrase 'from search results' adds a hint about where the slug originates, which is a slight extra context, but the heavy lifting is done by the schema. Thus a 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 clearly states the verb 'Get' and the resource 'product', and specifies it retrieves a single product by slug. It distinguishes itself from siblings like search_products (which likely lists/search) and fetch (generic) by detailing the exact fields returned (description, price, sale price, colors with SKU and stock).

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 phrase 'from search results' implies the intended usage context—after obtaining a slug via search—but does not explicitly state when not to use this tool or name alternatives. It gives clear context for when to use it but stops short of explicit exclusions or comparisons to siblings like fetch.

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, covering the safety profile. The description adds the useful detail that the tool reports both posted hours and current open status, but it does not explain how 'open right now' is determined, timezone handling, or data freshness. This is acceptable but not rich.

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, concise sentence that immediately conveys the core value of the tool. It contains no filler or redundant restatement of the name.

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 parameterless, read-only, idempotent tool with strong annotations, the description covers the essential return content. It does not specify the exact output format or timezone, but given the low complexity and the presence of safety annotations, the definition is sufficiently complete for an agent 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?

There are zero parameters and the input schema is empty, so parameter documentation is not needed. The baseline of 4 applies; the description adds no parameter-specific semantics because there are none to describe.

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 identifies the resource (store hours) and the specific data returned: posted opening hours plus current open/closed status. It is distinguishable from sibling tools like get_product, list_classes, and search, though it lacks an explicit verb and reads as a noun phrase rather than an action statement.

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 does not state when to use this tool versus alternatives or mention any exclusions. Usage is only implied by the tool's name and the described resource; no explicit guidance is given for choosing it over search or get_product.

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 safety profile is covered. The description adds the ordering behavior ('soonest first') and the scope ('at the shop'), which is useful context beyond the annotations. It does not disclose pagination or default behavior, but the schema covers defaults.

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?

A single, information-dense sentence that front-loads the resource and ordering, then lists the returned fields. 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?

For a read-only list tool with no output schema, the description covers the resource, ordering, and return fields. It does not mention pagination or the default time window, but the schema provides defaults and the annotations cover safety. Minor gap: no explicit statement about what happens when no classes match.

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 67%: 'days' and 'query' have descriptions, but 'limit' does not. The description adds the meaning of the result set (date, time, price, instructor, url) but does not explain parameter semantics beyond what the schema provides. Baseline 3 is appropriate since the schema does most of the work.

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 a specific verb ('list') and resource ('upcoming class and event sessions at the shop'), and specifies the ordering ('soonest first') and included fields (date, time, price, instructor, url). This clearly distinguishes it from sibling tools like search or get_product.

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 this is the tool for browsing upcoming sessions, and the sibling list (search, search_products, get_product) provides context for alternatives. However, it does not explicitly state when NOT to use it or name a specific alternative for finding classes by other criteria.

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 carry the safety profile (readOnlyHint=true, idempotentHint=true, destructiveHint=false), and the description adds value beyond them by disclosing the return shape: it returns ids rather than full product objects. That tells the agent the results are identifiers to be consumed by another tool, which is genuinely useful behavioral context.

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, zero filler, with the search scope front-loaded and the fetch-chaining note placed second. Every clause earns its place, and the resource types are packed efficiently into the opening clause.

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-only tool with annotations covering safety, the description is nearly complete: it states the scope, the search dimensions, and what the call returns. The only real gap is the unresolved relationship to search_products, and result-limit/empty-result behavior is left unspecified, but the return-value note partly compensates for the missing 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% and the query parameter already includes realistic examples. The description adds meaning beyond the schema by listing the valid search dimensions (name, maker, collection, color, SKU) and the product categories, so an agent knows what kinds of queries are legitimate even though the schema only reads "query".

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 a specific verb (search), a named resource (Be Sew Bizzy's products), and concrete scope (quilt fabric, notions, patterns, embroidery supplies), with search dimensions (name, maker, collection, color, SKU). However, it does not distinguish itself from the near-twin sibling search_products, so an agent cannot tell which search tool to pick without inspecting both 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?

The description gives clear usage context: this tool returns ids to pass to fetch for detailed price/sale/stock/colors, which establishes a search-then-fetch workflow. But it offers no exclusion guidance and never addresses when to use search vs. the sibling search_products, leaving a meaningful routing decision to inference.

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 destructiveHint=false, establishing safety. The description adds behavioral context beyond annotations: the matching logic ('every word must match') and the exact return fields (price, sale price, per-yard flag, stock, colors, URL). It does not mention pagination or error cases, but for a read-only search it is sufficiently transparent.

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, well-structured sentence that front-loads the action and constraints, then lists the return fields. No redundant or filler content; every element 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?

With no output schema, the description adequately explains the return fields. It covers the search semantics and result contents. It omits details about the 'limit' parameter's effect on output quantity, but the schema's default and min/max constraints make this inferable. Overall, it is complete for a read-only search 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 50%: the 'query' parameter is described with examples, while 'limit' has no textual description. The tool description enriches the 'query' meaning by listing searchable fields and the matching rule, but it does not compensate for the undocumented 'limit' parameter. Given the partial coverage, a 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's action: searching the shop's products by specific fields (name, maker, collection, color, SKU) and defines the matching rule. It is specific and distinguishes itself from generic siblings like 'search' by identifying the resource (products) and the search criteria.

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 this is for product searches but does not explicitly state when to use it over alternatives like 'search' or 'fetch'. There is no guidance on exclusions or when not to use this tool. The context is clear from the name and description, but explicit alternatives are not mentioned.

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