InduSpec — Industrial Materials Database

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

Annotations already establish a read-only, idempotent, closed-world operation, so the description does not need to restate safety. It adds real context by naming the returned data categories and by scoping results to 'approved' products, which implies unapproved or unknown slugs will not resolve, though the failure behavior is not spelled out.

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 compact sentence, front-loaded with the verb and resource, with the payload contents in parentheses and the keying constraint last. Nothing wasted.

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 read tool whose annotations already cover safety, this is nearly complete, and the parenthetical return-field list partly compensates for the absent output schema. It lacks any note on what happens when a slug is unknown or unapproved.

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?

With a single parameter and 100% schema description coverage, the schema already documents slug and its source. The description only reinforces that lookup is keyed by slug and limited to approved products, adding no syntax or format detail beyond the schema — 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?

States a specific verb (get) and resource (product) and specifies the shape of the payload: technical data covering description, application and parameters for an approved product. The phrase 'for one approved product by slug' implicitly separates it from search_products, though the sibling is never named.

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 only implied: the slug parameter's origin is given in the schema ('from search_products'), and 'one approved product' hints at the lookup-after-search workflow. The description itself gives no explicit when-to-use or when-not-to-use guidance and never names search_products or request_quote.

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=false, openWorldHint=true, idempotentHint=false and destructiveHint=false, so safety and repeat-call semantics are covered. The description adds that the request goes to the InduSpec team (an external submission), but says nothing about rate limits, confirmation, whether duplicate requests are merged, or what the caller receives.

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 well-formed sentence with no filler, and the qualifying constraint is placed where the agent will read it. It is efficiently brief rather than padded, though brevity here trades against disclosure.

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 five-parameter submission tool with no output schema, the description covers intent, target resource and recipient, and the schema fully documents inputs. The gaps — the meaning of 'approved', post-submission behavior and confirmation needs — are noticeable but modest given the annotation coverage.

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 all five parameters are documented and a baseline of 3 applies. The description's only additional semantic is the 'approved product' constraint tied to product_slug, which is genuinely useful but thin.

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 resource ('send a price quote request') plus the recipient, and the phrase 'for an approved product' signals the prerequisite resource, differentiating it from the read-only siblings get_product/search_products. It stops short of explaining what 'approved' means or how a slug qualifies.

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 only implied: an agent can infer this is the conversion step after get_product/search_products, and that the product must be approved. There is no explicit when-to-use or when-not guidance, and no prerequisite or sequencing statement naming the 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 openWorldHint=false, so the safety profile is covered. The description adds one genuinely useful behavior signal, that results are limited to the *approved* catalog, but says nothing about matching logic across multiple filters, pagination, or ordering.

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 front-loaded sentence naming verb, resource, scope and facets, with no filler whatsoever.

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 zero-required-parameter read tool with rich annotations and full schema coverage, the description is nearly sufficient. It leaves only minor gaps, notably what a result record contains and how multiple filters combine, and lacks an output schema to fill those in.

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 every parameter including limit, matching targets, and the °C unit is already documented. The description echoes the same facets without adding matching semantics (AND vs OR across query/category/temp_required), so it stays at the baseline.

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 (search) plus the exact resource (the approved InduSpec catalog of industrial materials) and the three facets searched, which makes it plainly distinct from get_product and request_quote. It stops short of explicitly naming the siblings, so it lands at 4 rather than 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?

The use case is implied clearly enough by a discovery-style search tool, but there is no explicit statement of when to prefer this over get_product (e.g. 'use this first to find product ids, then call get_product for details') and no exclusions.

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