Netik

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

Annotations already declare readOnlyHint=true, and the description usefully discloses the return payload (VAT-inclusive totals, amount due today, delivery time, site link) in the absence of an output schema. It does not, however, resolve the tension between the name "create_quote" and readOnlyHint by stating that nothing is persisted or quoted — a meaningful omission for a tool whose verb suggests creation.

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 with no filler, and the core function is front-loaded before the return-value summary. It packs the calculation scope and the return contents into a tight block.

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 7-parameter tool with a nested addons object and no output schema, the description covers the return shape (totals, due today, delivery, link) which the schema cannot. The remaining gap is the absence of any prerequisite or sequencing note relative to get_price.

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, enum, and default is already documented in the structured schema. The description only restates the parameter groups and adds no syntax or constraint detail beyond that, so the baseline 3 applies.

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: it prices a configuration (product, add-ons, care plan) and states the outputs it computes. An agent can tell this is a pricing calculator rather than a catalog lookup. However, it never names or contrasts the siblings get_price and start_checkout, so differentiation must be inferred.

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 "Price a configuration ... exactly as the website does" and by the returned totals, but there is no explicit when-to-use or when-not, and no routing to get_price or start_checkout. The guidance that add-on ids come from get_price lives in the schema, not the description.

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 scope information by enumerating what comes back (delivery time, payment terms, add-ons with prices), but says nothing about whether these are list vs quoted prices, currency handling of add-ons, or completeness guarantees.

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 tightly-packed sentence with zero filler, front-loaded with 'Price'. It is a noun-phrase fragment rather than a statement of action, which slightly weakens orientation but costs no length.

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 is the only place the return contents are disclosed, and it does enumerate them (price, delivery time, payment terms, inclusions, add-ons). For a two-parameter read-only lookup with full annotation coverage, that is close to sufficient; only the list-vs-quote distinction is missing.

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% and both parameters are fully enumerated, so the schema carries the load. The description only echoes the 'one product' and 'prices' aspects, adding no extra semantics such as what currency applies to add-on prices or whether currency affects availability.

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 precisely — price, delivery time, payment terms, inclusions and priced add-ons for one product — which is far more specific than the title's 'get a product price'. It implicitly separates itself from create_quote/start_checkout by being a pure information lookup, though it never says so explicitly.

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 read-side pricing lookup versus the mutating siblings (create_quote, start_checkout). There is no explicit when-to-use/when-not guidance, no mention of when to prefer list_services, and no stated prerequisites.

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?

Beyond the structural hints (readOnlyHint), the description adds critical business context that an agent needs to manage user expectations, specifically mentioning 'final prices,' 'delivery times,' and that 'VAT is included.' This defines the quality and scope of the data returned.

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 definition is a single, highly dense sentence that efficiently packs the exhaustive list of product types and pricing details into minimal space without unnecessary padding.

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?

Despite having no output schema, the description is complete. It defines exactly what the agent should expect in the return value: a list of nine items including pricing and delivery estimates.

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 schema coverage is 100% for the single parameter, so the baseline score is 3. The description is mostly reiterating the allowed currencies and does not add unique semantic value beyond the structured schema definition.

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 explicitly states that it lists all nine Netik products, providing a comprehensive scope. By specifying the list of product types (AI agents, MCP servers, etc.), it clearly distinguishes its function (general list) from transactional siblings like get_price 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?

While it doesn't explicitly say 'use this tool when...', the scope definition strongly implies the intended use: getting a broad catalog overview. The contrast with specific transactional tools like get_price makes the intended usage clear.

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?

Adds context beyond annotations: no payment is taken, a human enters details and approves, so the agent understands this is a preparation step with no financial side effect. It doesn't say whether the link expires or whether the configuration persists, which would have completed the picture.

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 repetition, and the key behavioral fact (human confirms payment) is front-loaded after the return value.

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 7 parameters, a nested addons object, and full schema coverage, the description only needs to explain the workflow, which it does clearly. Minor gaps: what happens on repeat calls, link lifetime, and how it relates to create_quote.

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% and enums/defaults are documented in the schema, so the description carries no param burden. It adds nothing about how product, care, addons and quantity interact at call time, so baseline 3 applies.

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 result: it returns a link to a product page with the configuration pre-filled. That is clearly distinct from get_price and list_services, though the boundary with create_quote is not addressed.

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 implies a workflow (prepare, then a human opens and confirms) but never says when to use this instead of create_quote, nor any prerequisites such as fetching a price or add-on ids first. No explicit exclusions are given.

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