Lons Publishing ISBN

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

Annotations already declare readOnlyHint, idempotentHint, destructiveHint=false and openWorldHint=false, so the safety profile is fully covered by structured data. The description adds no behavioral context of its own - nothing about result shape, matching/narrowing behavior, or whether a non-matching keyword yields empty or fallback content.

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 no filler, and the core purpose is front-loaded. It is efficient, though the second sentence is a fragment that could carry a bit more useful detail without bloat.

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 trivial one-optional-param read tool with full annotations this is close to adequate, but with no output schema the description should at least hint at what comes back (list of Q&A entries, single answer, etc.). That gap is minor but real.

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 optional parameter and 100% schema description coverage (including examples like 'delivery', 'format', 'pay' in the schema itself), the schema carries the burden. The description's 'optional keyword filter' merely restates that the parameter exists and is optional.

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 gives a specific verb+resource: it answers common questions about the ISBN service. An agent can immediately tell this is a documentation/FAQ lookup, distinct from the sibling offer/link/info tools, though it never explicitly contrasts itself with them.

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?

'Optional keyword filter' implies you may call it with or without a query, but there is no explicit when-to-use guidance, no mention of what to do when no keyword matches, and no routing against sibling tools. Usage 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?

Annotations already declare readOnlyHint=true, idempotentHint=true, destructiveHint=false, and openWorldHint=false, so the safety profile is fully covered structurally. The description adds only that the payload is a fixed catalog (packs, prices, delivery, payment, contact) but says nothing about caching, rate limits, or freshness that would go beyond the 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?

A single front-loaded sentence that names the action first and then the return contents; every listed item earns its place and there is no filler 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 return values, and it does so comprehensively (pack tiers, dual-currency pricing, inclusions, delivery, payment, contact). It is complete for a read-only catalog lookup, though it omits any note on response format or how the lang parameter shapes the output.

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 a single optional 'lang' parameter with 100% schema description coverage and an explicit enum with default, so the schema fully documents it. The description mentions 'supported languages' as returned content but adds no meaning about what the lang parameter controls, 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 resource (returns ISBN packs) and enumerates exactly what comes back: three pack tiers, USD and FCFA prices, inclusions, delivery delay, payment methods, languages, and contact. This content profile is clearly distinct from the sibling faq, get_order_link, and get_required_book_info, so an agent can route without opening a 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?

Usage is implied by the content: call this when a user asks about ISBN pack options or pricing. However, no explicit when-to-use statement, prerequisites, or comparison against the potentially overlapping sibling 'faq' is provided, leaving 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?

Annotations already declare readOnly/idempotent/non-destructive, but the description earns credit for the scope disclaimer that matters most here: it "never performs or initiates a payment and collects no payment data." For a tool named get_order_link this pre-empts a serious misreading, though it says nothing about rate limits, link expiry, or whether the link is stable across calls.

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, zero waste, with the primary purpose front-loaded ahead of the payment-method detail and the safety disclaimer. Every clause carries distinct information.

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 and does so at a functional level (a Stripe Checkout link vs. a Mobile Money order page). It stops short of stating the exact return shape (e.g., a URL field) or link lifetime, but for a 3-parameter read-only tool this is close to sufficient.

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%, so the baseline is 3. The description goes beyond the schema by explaining what the parameter values actually yield ("card = Stripe Checkout link; mobile_money = order page with the Mobile Money form"), which the flat enum descriptions do not convey.

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 gives a specific verb and resource ("Returns the secure page where the CUSTOMER pays for an ISBN pack") and even distinguishes the two return shapes by payment method. It does not, however, differentiate itself from siblings like get_isbn_offer, so an agent must infer the boundary itself.

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 agent can infer this is called when a customer needs a payment link, and the card/mobile_money mapping hints at when each variant applies. There is no explicit when-to-use vs. get_isbn_offer or get_required_book_info, and no stated preconditions.

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 annotations already declare read-only, idempotent, non-destructive, and closed-world behavior, so the safety profile is covered. The description adds the post-payment timing context, but it does not disclose additional traits such as return format, pagination, or whether the required fields vary by language.

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 a single, well-formed sentence that front-loads the core purpose and then explains the agent's benefit. Every clause earns its place with no redundant or filler text.

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 simple one-parameter read tool with rich annotations and full schema coverage, the description sufficiently explains what is returned ('the fields') and why to call it. It could be slightly stronger by mentioning that the field list may depend on the customer language, but that detail is available in the schema.

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 the single 'lang' parameter is fully documented in the schema with its enum values and default. The description adds no additional meaning for the parameter, which matches the baseline of 3 when the schema does the heavy lifting.

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 uses a specific verb ('Lists') and resource ('the fields the customer fills in on the thank-you page after payment'), making the tool's purpose clear. However, it does not differentiate from sibling tools like faq or get_order_link, so the agent must infer the distinction from context.

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 phrase 'so an agent can help prepare them in advance' implies the usage context: use this tool before the customer reaches the thank-you page. There are no explicit when-not conditions or named alternatives, leaving the routing decision partially implied.

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