HTR Bamboo Product & Inquiry Assistant

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

Annotations already declare readOnly/idempotent/non-destructive, and the description is consistent with them. It adds real value beyond annotations by disclosing the modeling assumptions (conservative right-angle geometry; payload, door, stacking and forklift limits) and an explicit accuracy disclaimer, though it says nothing about limits like max 10 panel lines or how defaults are applied.

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 tight sentences: purpose and outputs first, modeling basis second, disclaimer last. Every sentence carries information and nothing is repeated from the schema.

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 description names the returned quantities (which helps since there is no output schema) and sets safety expectations for a mutating-looking but read-only calculator. However, for a tool this parameter-rich with zero schema descriptions, the near-total silence on the 20+ nested inputs leaves an agent unable to use many options without guessing.

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%, and the schema is deep — 6 top-level params with ~17 nested panel fields plus a handling object. The description only hints at 'panels', 'container', and 'payload/door' (container_overrides); it explains nothing about tier_cap, stacking_basis, plan, clearance_mm, lift_mode, or capacity_mode, so parameters are effectively undocumented.

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?

States a specific verb ('Estimate') plus exactly what is computed: sheets per pallet, pallet count, and 20/40-foot container use for bamboo panel lines. No sibling tool (product search, inquiry prep) does anything similar, so an agent can route here unambiguously.

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 closing sentence sets a clear scope boundary: 'Planning estimate only; not a loading approval or freight quotation,' which tells the agent when to trust and not trust the output. It does not name any alternative or prerequisite (e.g., when to prefer a real freight quote tool), leaving some inference to the agent.

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 readOnly, idempotent, non-destructive, closed-world, so safety is covered. The description adds meaningful context about data provenance — source-backed tables, reference-only qualifications, quality flags — but 'HTR confirmation' is undefined jargon and no mention of error behavior for unknown product_id.

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, purpose front-loaded, but the latter two are dense and jargon-heavy ('Preserve table column context', 'HTR confirmation') without explaining what that means operationally.

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?

Describes the return payload (name, spec tables, flags) well enough without an output schema, but omits the key operational detail — how to source a valid product_id — and never defines 'HTR', leaving the calling agent with unresolved terminology.

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% and product_id has only min/max length constraints with no description. The description never mentions product_id or where to obtain it (e.g., from search_products results), so it fails to compensate for the coverage gap.

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?

States a specific verb ('Read') and concrete resources — product name, specification tables, quality flags — so an agent knows this retrieves detail for one product. It doesn't explicitly contrast with the sibling search_products, but the singular-object framing distinguishes it implicitly.

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 statement of when to use this versus search_products, which clearly overlaps as the discovery path. The only conditional ('Missing or withheld facts require HTR confirmation') is a post-retrieval caveat, not a selection rule.

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 readOnly, idempotent, non-destructive, and closed-world, so the safety profile needs no restating. The description does add the return payload (families plus counts), which matters because there's no output schema, but it omits result size, ordering, or whether counts are live.

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 short sentences with the purpose first and the usage cue second; every clause carries information. No boilerplate 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?

With no output schema, the description carries the burden of describing the return value and does so only at a high level. For a zero-param orientation tool that is arguably enough, but ordering, granularity, and result size remain unspecified.

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 tool takes zero parameters, so there is nothing to disambiguate and the schema burden is nil. The description correctly implies no filtering inputs are needed, though it never says so explicitly.

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?

States a specific verb+resource: lists 'HTR public product families' along with record counts. An agent can tell this is a lightweight catalogue overview rather than a product search. Slight deduction because 'HTR' is never expanded or grounded, and it's not explicitly contrasted with sibling search_products.

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?

'Use this to orient a buyer before searching' gives a sequencing hint — call this first, then search — which is genuinely useful. However, it never names the alternative (search_products) or states exclusions, so the routing guidance is implied rather than explicit.

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, so the description is not carrying the safety burden alone; it still adds real value by enumerating what is not persisted or sent and by explaining that the buyer completes contact details on the website. It stops short of describing the lifetime or validity of the generated link/draft, which matters for a non-idempotent prepare step.

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 tight sentences: the positive capability first, then the explicit non-capabilities and the scoping rule. Every clause carries information an agent needs and nothing is repeated.

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 9 parameters, zero schema descriptions, and no output schema, the description leaves the agent guessing about field semantics and about the structure of the returned draft/link. It covers the safety and scope story well but is materially incomplete for a tool of this input complexity.

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% across 9 parameters, so the description must compensate and largely does not. The only implicit parameter guidance is that contact details are deliberately excluded, which helps confirm the shape of the input but says nothing about product_id, request_type enum values, or how quantity/packaging/specifications are expected to be formatted.

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?

States a specific verb and pair of artifacts: 'Prepare an editable HTR inquiry draft and official website confirmation link.' An agent immediately knows the output is a draft plus a link, not a submitted inquiry. It does not name the closely related sibling validate_inquiry, so sibling routing still requires inference.

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 negative list ('DOES NOT submit, store the draft, send email, create a CRM record or verify an email') effectively rules out using this tool when the agent wants an actual submission, and 'Collect only procurement requirements' scopes inputs. However, it never says when to prefer this over validate_inquiry or what the expected sequence between them is.

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 readOnly, idempotent, closed-world, non-destructive, so the safety profile is covered. The description adds one genuinely useful behavioral note — that results are reference material rather than order-specific commitments — but says nothing about ranking, matching semantics (full-text vs. topic browse), or what happens when query is empty, which matters for a search tool.

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 the resource inventory and closed with the interpretive caveat — nothing is padded. The first sentence is a dense comma list, but every item adds discriminating information about the corpus.

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?

Four parameters with zero descriptions, two enums with unexplained domain-specific values, and an undefined acronym ("HTR") mean an agent cannot confidently construct a call. With no output schema there is also no compensating documentation of return shape, so the description would need to do much more than it does.

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%, so the description carries the full burden, and it does not. It never mentions the query string, the limit cap of 10, the 19-value topic enum, or the opaque family enum (knitting_tools / panels_and_surfaces / components_and_finished_goods). The content list loosely echoes some topic values (sample, inspection, shipping, calculator) but gives no guidance on how topic, family, and query combine.

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?

Names a specific verb ("Find") and enumerates the concrete resource types it returns: buyer guides, sample/inspection checklists, document scope, shipping guidance, calculators, case studies. An agent can form a clear picture of the result set. It stops short of distinguishing itself from the sibling search_products, so the guide-vs-product boundary must be inferred from the word "guides".

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?

There is no statement of when to reach for this tool versus search_products, get_product, or prepare_inquiry, and no exclusions or prerequisites. The trailing sentence constrains how to interpret results ("references, not order-specific promises") but that is a caveat on output, not usage routing.

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 readOnly, idempotent, non-destructive and closed-world, so the safety profile is covered. The description adds genuine context beyond that — bilingual English/Chinese matching and the fact that stock/price/suitability are out of scope of the result — but says nothing about result ordering or pagination behavior even though limit/offset 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?

Three short sentences, scope stated first, exclusions second. No filler, and the most load-bearing constraint is front-loaded.

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?

There is no output schema, so the description bears some burden for describing what comes back, and it only tells the agent what is NOT returned. For a search-and-paginate tool with four undocumented parameters, the definition is adequate to start a call but not to predict its results.

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%, so every parameter's meaning rests on the description, and it only loosely gestures at 'query' and 'family' via 'name, specification or category'. It says nothing about what limit/offset do, whether family and query can be combined, or what the three enum families actually contain.

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?

Specific verb+resource ('Find HTR Bamboo website products') with the searchable dimensions named (name, specification, category). It does not name the closest sibling get_product, so the boundary between search and retrieve-one is only implied rather than stated.

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 sentence 'This is not a stock, price or suitability check' is a real exclusion, which is more than most definitions offer. But it never names the alternative (get_product for details, list_product_categories for taxonomy) nor states positive preconditions, so the agent must infer the routing itself.

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, non-destructive, and closed-world behavior, so the safety profile is covered. The description adds useful behavioral context beyond that: it returns one next question plus relevant public guides and cases, and it clarifies that readiness is scoped to HTR review rather than final approval. It does not describe behavior on partial or invalid input, but the added return semantics are meaningful.

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 short sentences with zero waste: the core action is front-loaded, the return behavior follows, and the readiness caveat closes. Every sentence earns its place and there is no redundant restatement of the tool 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 complex tool with 12 parameters, nested objects, enums, and no output schema or schema descriptions, the description is too thin. It explains the high-level purpose and return shape, but an agent still has no guidance on the inquiry structure, the nested product-specific objects, or how required versus optional fields behave, which is a significant gap for correct invocation.

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% across 12 parameters, including three nested objects, so the description must carry the burden of explaining parameter meaning. It only vaguely alludes to 'product-specific missing and ambiguous fields,' which hints that nested panel/knitting/component fields exist but gives no semantics for any parameter, enum, or required product_id.

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 verb and resource: checking an HTR inquiry for product-specific missing and ambiguous fields. It is clear what the tool does, but it does not explicitly differentiate itself from the sibling prepare_inquiry, leaving an agent to infer the boundary between preparing and validating an inquiry.

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?

Usage is implied by the validation framing and the caveat that 'readiness only means ready for HTR review,' which tells an agent this is a pre-review completeness check. However, there is no explicit when-to-use guidance, no exclusions, and no mention of the alternative prepare_inquiry tool.

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