Netik

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

Annotations already declare this a safe read (readOnlyHint=true, openWorldHint=false), and the description goes further by disclosing the pricing contract: totals are in ILS, VAT-excluded, mirroring the website, and include amount due today plus delivery time. With no output schema, this is the main source of return-value expectations; only error/edge behavior (invalid combos, default application) is left unstated.

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: the action and pricing-parity claim come first, followed by a compact enumeration of the return payload. Every clause carries information an agent would otherwise have to guess.

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 six parameters (one nested object), no output schema, and safety already covered by annotations, the description covers the return shape and pricing semantics well. The remaining gap is workflow positioning relative to get_price/start_checkout, which matters for a pricing tool in a quote-to-checkout flow.

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%, with enums and defaults already documented in the schema, so the baseline of 3 applies. The description adds no parameter-level detail beyond the parenthetical field list, which merely restates what the schema already names.

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 ('Price a configuration') plus the three dimensions being priced (product, add-ons, care plan) and the pricing-parity guarantee with the live website. It does not explicitly differentiate itself from the sibling get_price (add-on/price lookup) or start_checkout, so an agent must infer the boundary.

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 never says when to call this versus get_price or start_checkout, nor does it state prerequisites (e.g., add-on ids must first be retrieved via get_price). The workflow role — quote first, then checkout — is only implied by the returned 'link to the same configuration'.

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 openWorldHint=false, so the safety profile is covered. The description adds useful context about what data comes back (delivery time, payment terms, add-on prices), but says nothing about pricing variability, staleness, currency, or error behavior for invalid products.

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 with zero filler, and the most important element (price) is front-loaded. It reads as an awkward noun fragment rather than a complete statement, which slightly hurts clarity but not 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?

With no output schema, the description usefully enumerates the returned fields, which is the main thing an agent needs to know before calling. For a one-parameter read-only tool with annotations, this is close to complete; only currency/format and failure modes are unaddressed.

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 single enum parameter carries its own description with examples ('site', 'landing'). The description only restates 'for one product' and adds no meaning about the enum values or their business implications 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 enumerates exactly what the tool returns for a single product: price, delivery time, payment terms, inclusions, and priced add-ons. The resource and scope ('one product') are unambiguous, though the sentence is a noun fragment with no verb and never distinguishes the tool from siblings like list_services or create_quote.

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 guidance on when to call this versus create_quote (which presumably also needs pricing) or list_services. Usage is only implied by the content listed; no prerequisites, exclusions, or alternatives are named.

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 openWorldHint=false, so the safe, self-contained read profile is established. The description adds meaningful output context the annotations don't cover: prices are final, quoted in ILS, exclude VAT, and delivery times are included. It says nothing about ordering, result size, or what an unknown product looks like, but for a fixed nine-item static list that omission is minor.

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 with no filler, leading with scope ('all nine products') before the price and delivery qualifiers. The parenthetical enumerates only six of the nine items, which is slightly noisy but still illustrative rather than wasteful.

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 parameters, no output schema, and read-only annotations, this is a low-complexity tool, and the description covers the key return semantics (products, currency, VAT treatment, delivery times) that the structured fields don't. Only catalog ordering and result size are unstated, which is not enough to block a correct call.

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 for the description to disambiguate. Baseline 4 applies; the schema and empty property set fully specify the call.

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 concretely ('All nine Netik products') and what comes back (final prices in ILS, no VAT, delivery times), which is enough to distinguish it from get_price or create_quote. The verb is implicit ('list' only in the name), so it reads as a catalog statement rather than an action, but the coverage of what the tool surfaces is specific.

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?

Listing 'all nine products' implies a browse-the-full-catalog use case, which an agent can contrast with get_price for a single item. However, the description never explicitly says when to use this versus get_price, start_checkout, or create_quote, leaving the routing 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?

Goes beyond the readOnlyHint/openWorldHint annotations by disclosing the real behavioral shape: the tool only prepares a link and a human must complete payment, which prevents an agent from assuming a completed transaction. It doesn't cover link expiry, single-use behavior, or whether repeated calls create duplicate drafts.

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, zero filler, with the return value and the human-confirmation constraint 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?

No output schema exists, so the description correctly explains the return value (a link) and the human confirmation step. For a tool with a nested addons object and enum-driven products, remaining gaps (link lifetime, add-on sourcing) are minor.

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% with enums, defaults and the product/plan coupling already documented, so the baseline is 3. The description only implies that parameters are baked into the returned link and adds no extra meaning.

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 concrete outcome: it returns a configured link to the product page rather than performing a purchase. The verb/result is specific, though it never names the sibling tools (create_quote, get_price) to sharpen the boundary.

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 explains the human handoff step (open link, enter details, confirm, payment approved by a human), which implies when this is appropriate, but it gives no explicit when-to-use vs create_quote or get_price, and no prerequisites such as fetching add-on ids via get_price.

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