catalog

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

Annotations already declare readOnlyHint=true, idempotentHint=true, destructiveHint=false, so no contradiction. Description does not add behavioral details beyond the annotations (e.g., no mention of logging, but schema note covers logging). Credit for adding the 'override any role' capability, but that is more functional than behavioral.

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, no filler, front-loaded with the main purpose and outcomes. Efficiently communicates the tool's scope and customization feature.

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 a simple 3-parameter tool with 100% schema coverage and an output schema, the description provides sufficient context for invocation. Mentions the compatibility verdict and CSV export, but does not explicitly state prerequisites (e.g., obtaining a valid build_id from list_builds), though that is inferable from siblings.

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 parameters are already documented. Description adds 'Override any role with choices' which clarifies the purpose of 'choices', but this is also implied by the schema ('role → part id overrides'). No significant additional meaning 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?

Description clearly states 'Composes a complete BOM for a reference build' with specific components (quantities, dated prices, rationale, compatibility verdict, CSV export). This is distinct from sibling tools like get_part or search_parts, which focus on individual parts.

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?

Context is clear: use for building a complete BOM for a reference build, with ability to override roles via choices. Does not explicitly mention exclusions or name alternative tools, but the purpose is self-evident and distinct from siblings.

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 mark the tool as read-only, idempotent, and non-destructive. The description adds valuable behavior beyond annotations: it produces 'a reasoned verdict per check' and states that every cited number is a 'corroborated attribute', giving insight into output quality and verification expectations.

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 compact sentences, front-loaded with the core purpose. The em-dash list of constraint categories is efficient and every clause adds actionable detail without repetition or 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?

The tool is complex with multiple engineering check categories, but the description maps those domains and clarifies output behavior (verdict per check, corroborated numbers). The presence of an output schema covers return value details, so the description is sufficient for selection and basic invocation, though a bit more detail on input expectations would round it out.

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 67%, with part_ids lacking a description; the description's 'part set' phrasing helps clarify it. build_id and project_context already have schema descriptions, and the description reinforces build_id's purpose via 'the build's engineering constraints'. project_context is not mentioned, but the schema covers it.

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 ('evaluates'), names the resource ('part set against the build's engineering constraints'), and enumerates concrete check categories such as supply windows, stall vs peak current, and shaft/wheel fit. This clearly distinguishes it from sibling tools like compare_parts or search_parts.

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 the appropriate context — use it when you have a set of parts and need engineering-constraint verification with reasoned verdicts. However, it does not explicitly state when to prefer this over siblings like compare_parts, nor does it provide exclusion 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?

This is an annotation contradiction. The description states an open-world interpretation—'Absence means the sources did not state a value — never that the part lacks the property'—while the annotations set openWorldHint=false. The readOnlyHint and idempotentHint are supported, but the open-world contradiction makes the behavioral disclosure misleading.

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 primary action, and the second sentence adds a critical semantic caveat. There is no filler, and every word 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?

Although an output schema exists and the purpose is clear, the description lacks usage differentiation from check_compatibility and, more critically, directly contradicts the openWorldHint annotation. An agent cannot confidently rely on the absence semantics described, making the overall description incomplete for safe and correct tool selection.

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 has 100% coverage of all three parameters, so the schema already carries parameter semantics. The description adds no parameter-level detail beyond reinforcing that 'two catalogue parts' map to the a and b parameters, which is the baseline expected for full schema coverage.

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 the specific verb 'compare' with a clear resource ('two catalogue parts') and scopes it as an 'aligned attribute-by-attribute comparison,' which distinguishes it from sibling tools like check_compatibility and get_part. This makes the tool's core purpose immediately clear.

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?

No when-to-use guidance or exclusions are provided. The description never contrasts compare_parts with check_compatibility, get_part, or search_parts, leaving an agent to infer when this tool should be preferred over siblings.

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, idempotentHint, and destructiveHint, so the safety profile is clear. The description adds behavioral context by specifying the record is 'full provenance-backed' and returned as a 'citable document', which goes beyond the structured 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 two sentences long and front-loaded with the core action. The second sentence adds the alias relationship, and both sentences earn their place without redundancy or 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?

The tool is simple (one parameter), has rich annotations, and an output schema exists. The description covers the essential purpose, the parameter's role, and the contract placement, making it complete for an agent to select and invoke 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 0%, but the description compensates by clarifying that the 'id' parameter is a 'search result id', giving essential meaning beyond the bare property name. For a single-parameter tool, this is sufficient semantic guidance.

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 a full provenance-backed record for a search result id as a citable document. It also distinguishes itself by noting it is an alias of get_part, providing immediate sibling differentiation.

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 context by positioning the tool as an alias of get_part shaped to the search/fetch connector contract. This implies when to use it (search/fetch flows) but does not explicitly state when not to use it or name alternatives beyond get_part.

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?

The annotations already declare readOnlyHint, idempotentHint, and non-destructive behavior, so the description does not need to restate safety. It adds value by detailing what the canonical record contains—provenance, vendors, datasheet links—which lets the agent anticipate the response shape. It doesn't mention the privacy-logging behavior of project_context, but that is disclosed in the parameter schema, so no contradiction exists.

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 dense sentence that front-loads the core purpose ('complete canonical record for one part') and then efficiently enumerates the key record components. Every phrase earns its place without any filler or repetition of the title.

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 an output schema present, the description need not detail return fields; it instead gives the high-level data categories. Combined with the annotations (read-only, idempotent) and full schema coverage, this is adequate for a two-parameter get-by-id tool and leaves no critical 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 description coverage is 100%: both id and project_context have clear descriptions, including an example for id and a note about anonymous logging for project_context. The tool description adds no extra parameter-specific meaning, so it meets the baseline of 3 but does not exceed it.

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 'The complete canonical record for one part,' clearly establishing a get-one-part-by-id action with a specific resource. It enumerates the record's contents (attributes with provenance, vendor prices, datasheet links), which distinguishes it from siblings like search_parts or compare_parts.

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 'complete canonical record for one part' clearly implies using this when you have a known part id and need the full record, and the sibling tools (search_parts, compare_parts) set the context for alternatives. However, it never explicitly says 'use this when...' or names a specific alternative, so it falls just short of full explicit 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?

Annotations already declare readOnlyHint and idempotentHint true, safely indicating a non-destructive operation. The description adds valuable context by detailing what the receipt contains (e.g., 'ready-made citation line') and provides a behavioral instruction ('Omit code for every attribute's receipt'), which goes beyond the schema. This enriches the agent's understanding without contradicting the 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 compact at two sentences, efficiently packing key details about the return contents. However, the second sentence 'Omit code for every attribute's receipt' is slightly awkward and could be clearer, though it's not verbose. Overall, it's well-structured with 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, idempotent tool with a straightforward purpose and an output schema available, the description sufficiently conveys the tool's behavior and result composition. It explains what the receipt includes and gives a usage hint. While it could mention potential edge cases or error conditions, it's adequate for a utility of this simplicity.

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 documents all three parameters (id, code, project_context) with descriptions, achieving 100% coverage. The description's phrase 'Omit code for every attribute's receipt' aligns with the schema's instruction for the 'code' parameter, adding no new information. Per the rubric, with high schema coverage, the baseline of 3 is appropriate; the description does not significantly enhance parameter understanding.

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 that the tool returns the receipt behind a stated value, specifying exact components like verbatim source quote, page, extraction method, and SHA-256 hash. This specificity distinguishes it from sibling tools like get_part (which retrieves part data) and search_parts (which searches), making the purpose and scope unambiguous.

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 purpose of fetching provenance is implied by the description and title, so an agent might infer when to use it. However, there is no explicit guidance on when to use this versus alternatives, no exclusions (e.g., when not to use), and no mention of relationships to sibling tools like compare_parts or list_builds. It briefly instructs to omit 'code' for all attributes, which serves as a usage hint, but it's not elaborated.

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 cover read-only, idempotent, and non-destructive behavior. The description adds useful content-level transparency by stating the tool returns reference builds with their roles and candidate parts. It does not discuss ranking or logging, but those are captured in the parameter 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?

The description is a single sentence that front-loads the core resource, provides concrete examples, states what is returned, and ties the tool to the BOM workflow. Every phrase 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?

For a simple list tool with one optional parameter, full schema coverage, strong annotations, and an output schema, the description is complete. It tells the agent what the tool returns, what the content is, and where it fits in the larger build_bom process.

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 for the single optional parameter is 100%, so the baseline is 3. The tool description does not add parameter-specific detail; it focuses on the resource and output contents, which is sufficient given the schema already documents project_context thoroughly.

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 names a specific resource ('catalogue's reference builds'), enumerates examples (robot, weather station, plant waterer), and specifies the result contents ('roles and candidate parts'). It also explicitly links the tool to the build_bom workflow, distinguishing it from sibling part/category 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?

It clearly positions this tool as 'the starting point for build_bom', giving the agent an actionable context for when to invoke it. However, it does not explicitly name alternatives or exclusion scenarios, 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?

Annotations already include readOnlyHint=true, idempotentHint=true, destructiveHint=false, so the safety profile is clear. The description adds that the output includes part counts per category, which is useful behavioral context beyond 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, concise sentence that delivers the essential information about what the tool returns. 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?

With an output schema and comprehensive annotations, the description adequately completes the picture. It clarifies the tool returns all categories with part counts, and the optional parameter is for ranking. Given the tool's simplicity, this 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?

The only parameter project_context has a detailed description in the schema (100% coverage), including max length and privacy note about logging. The tool description adds no additional parameter meaning beyond 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 'Every category in the catalogue with its part count' clearly states the tool lists all part categories and includes a part count. It distinguishes from siblings like search_parts or get_part, though it doesn't explicitly differentiate.

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 for fetching categories in the catalogue, but doesn't provide explicit context on when to use it vs alternatives. The optional project_context parameter suggests ranking use, but no explicit when-to-use guidance is given.

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 description isn't required to repeat those. The description adds that it's an alias of search_parts and returns result ids, which provides useful context about the interaction with fetch. 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?

Two sentences, no fluff. Each sentence provides essential information: what it does, returns result ids for fetch, and its alias relationship.

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 has a simple schema (one string param), an output schema (likely describing result ids), and annotations that cover safety. The description is short but sufficient for a simple search tool. It could mention that results are ids for fetch, which it does. The only gap is not clarifying how query affects results, but given the simplicity, it's adequate.

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 0%, but there is only one parameter 'query' which is self-explanatory. The description mentions 'Search the catalogue' but doesn't explain the query syntax or expected format. Since the parameter is simple and the description introduces the concept of returning result ids, a 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 the catalogue and returns result ids for fetch. It also mentions it's an alias of search_parts, which helps distinguish it from the sibling search_parts tool. However, it doesn't fully clarify the difference between 'search' and 'search_parts' beyond being an alias.

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 says it's shaped to the search/fetch connector contract, implying a specific usage pattern. It mentions returning result ids for fetch, guiding the agent to use fetch next. However, it doesn't explicitly state when not to use this tool or alternatives like search_parts.

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 establish the safe read-only, idempotent profile; the description adds value by disclosing that results are provenance-backed and every attribute was corroborated against datasheets or vendor pages. No contradiction.

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, the first front-loads the action and scope, the second adds filter details and data-quality context. No redundant 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?

For a 6-parameter search tool with an output schema and rich annotations, the description is mostly sufficient. It covers core search behavior, filtering, and data provenance, but omits details about limit behavior and project_context ranking (the latter only appears 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 only 33%, so the description must compensate. It clarifies that category, build, and role are filter criteria, but leaves limit semantics and possible values for the filter parameters unspecified.

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: 'Full-text search over the demo catalogue's provenance-backed part records', and explicitly names the filter dimensions (category, build, role). This clearly differentiates it from siblings like get_part or compare_parts.

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 establishes clear usage context: full-text search with filtering by category, build, or role. However, it does not explicitly state when to use an alternative sibling tool (e.g., get_part for a single record) or any exclusions.

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 clear. The description adds that it renders interactively and has the same data as build_bom, which provides useful behavioral context beyond the 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 concise and front-loaded: one sentence states the action and rendering, and a second sentence clarifies the relationship to build_bom. No unnecessary 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?

The tool is relatively simple with only two parameters and an output schema, so the description is mostly complete. It could mention how choices affect the BOM rendering, but the schema provides basic param details and the output schema covers return values.

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 50%; build_id has a helpful description in the schema, but choices is only described as an object with string properties. The tool description does not elaborate on choices or provide additional meaning beyond the schema, so it relies on the schema for parameter details.

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 composes a BOM for a reference build and renders it as an interactive view. It explicitly distinguishes from sibling build_bom by noting 'Same data as build_bom', which helps differentiate between the two.

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 indicates this tool is for rendering an interactive view, implying use when a client supports MCP Apps, while build_bom is presumably for non-interactive use. However, it does not explicitly say when not to use it or mention alternatives beyond build_bom.

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