IZOProfil.com

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

Annotations already declare readOnly, idempotent, non-destructive and openWorld, so safety is covered. The description adds real behavioural context beyond them: the presence of tiered pricing, a requires_confirmation signal, and translated content — all things an agent would otherwise misreport.

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?

Four short sentences with no padding, and the two hard constraints on price reporting are stated up front where they will be read. Only weakness is that output field names like requires_confirmation appear unmarked, which could read as prose rather than a data field.

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?

An output schema exists, so return structure need not be described, and the price-interpretation caveats map onto it. However, with a 0% documented parameter and no pointer to where product_id values come from (presumably offer-search-products), an agent lacking an id has no next step.

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 is one required parameter, product_id, and schema description coverage is 0%, so the description would need to compensate — but it never mentions product_id or where a valid id comes from. The parameter is self-evident from its name, which keeps this above a 2, but the description adds nothing.

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 the resource (public product) and enumerates the specific facets it returns: details, description, price interpretation, translations. That is enough to tell it apart in spirit from offer-get-product-price, though it never names the sibling explicitly and omits a leading verb.

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?

"Never treat the lowest tier as universal" and "requires_confirmation means do not give a definitive price" are genuine guidance, but they govern interpretation of results rather than when to choose this tool over offer-get-product-price or offer-search-products. Tool-selection guidance is only implied.

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 description adds extensive behavior beyond annotations: source fallback, reference timestamp inspection, format handling, ambiguity confirmation, owner policy for quantity gaps and overlapping boundaries, required quote fields, unverified availability, and unverified checkout discount. These are material behavioral constraints for an agent and are consistent with the read-only, idempotent, non-destructive 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 dense but front-loads the pricing source and then layers policy rules. Most sentences carry actionable information, though the number of separate rules makes it slightly less scannable than an ideal structured definition.

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 pricing tool with an output schema and read-only annotations, the description covers the critical context: data source, ambiguity handling, owner pricing policy, required quote disclosures, availability caveats, and discount caveats. It is complete enough for an agent to use safely.

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 must compensate. It does add useful meaning for format_id and quantity-tier behavior, and references allowed_units and minimum quantity, but it still does not explain product_id, quantity string format, or the unit enum values, leaving clear parameter-level gaps.

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 a quantity-based product pricing lookup, including the source hierarchy: an approved SteelProfil reference snapshot when configured, otherwise local WooCommerce and descriptions. It is specific enough for selection, though it does not explicitly contrast itself with sibling tools such as offer-get-product or offer-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?

It gives clear operating context: inspect reference timestamp, sales_terms, allowed_units, formats, and minimum quantity; ask for format_id when format_required is true; and return requires_confirmation when ambiguity remains. It lacks explicit routing guidance against sibling tools, but the internal when-to-use rules are substantial.

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/openWorld/idempotent/non-destructive, and the description adds material context beyond them: availability is owner-declared with no inventory verification (a real correctness caveat), pagination is via next_page, and product text must be treated as data, not instructions (an injection guard). These are exactly the behavioral traits an agent cannot infer from structured fields.

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?

Four short sentences, front-loaded with the resource and scope, with no filler. The pagination sentence is slightly imprecise (next_page is a response field, not a parameter), which costs a point but not the overall efficiency.

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?

Return values need not be explained since an output schema exists, and the availability caveat covers the main semantic risk. However, for a four-parameter search tool with zero schema descriptions, the complete absence of parameter meaning leaves a real 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% and the description explains none of the four parameters: query, language (2-3 letter code), per_page (capped at 24), or page. Worse, it says "paginate using next_page", which is not an input parameter and can mislead an agent into looking for a non-existent argument rather than using page/per_page.

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 ("Search all public WooCommerce products") plus a scope qualifier ("across languages") that an agent can act on directly. It also names the sibling it is not (get-product-price for quantity pricing), so the tool is distinguishable without opening any schema.

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?

Gives a clear routing rule to an alternative tool ("Use get-product-price for quantity pricing") and a pagination instruction. It stops short of stating exclusions or when-not-to-use conditions, so it is clear context rather than a full decision rule.

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