Near Fine

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

Annotations already declare destructiveHint=true and idempotentHint=true; the description reinforces destruction with the concrete analogy 'deleting it as its Delete button on Near Fine does.' It adds genuinely new context beyond annotations: the first-time sign-in requirement and what is returned (the cancelled alert and the person's plan).

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?

Three short sentences, front-loaded with the action and id provenance, then auth, then return value. The repeated 'Near Fine' branding is slightly redundant but costs little.

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 supplies the return values, and it also covers the auth prerequisite and where the id comes from. Only irreversibility of the delete and failure modes are left unstated, which is a minor gap for a destructive tool.

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% for the single id parameter, so the baseline would be 3. The description adds value by specifying the origin of the id (list_alerts or set_alert), which the schema does not say.

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 (cancel), a specific resource (one of the person's alerts), and the identifier basis (by its id). It also names where the id comes from (list_alerts or set_alert), which separates it cleanly from those siblings.

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?

'from list_alerts or set_alert' tells the agent the prerequisite step and therefore the context in which this tool applies. It does not state an explicit when-not or an alternative cancellation path, so it stops short of full routing guidance.

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, and closed-world. The description adds real value beyond that: the sign-in requirement on first call, the deterministic ordering (finds, then checking, then rest, newest first), and a full status taxonomy. No pagination or rate-limit note, keeping it short of a 5.

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?

Information is front-loaded: purpose first, then ordering, then return fields, then statuses, then the plan. It's a dense single block but nearly every clause carries useful semantics; the status enumeration is long but earns its place for an agent interpreting results.

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 full burden of describing return values, and it does so thoroughly: fields per alert (id, query, country, status, timestamps, link, find details) and the plan. An agent can interpret the response shape without any output 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?

There are zero parameters, so the schema baseline is 4. The description correctly adds nothing parameter-related, since there's nothing to document.

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 opens with a specific verb and resource ('List the person's alerts on Near Fine') and the tool name makes it trivially distinct from set_alert/cancel_alert. It's clear what it does, though it never explicitly contrasts with sibling tools like search_books or list_sources.

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 rather than stated. 'The first time, they sign in' signals the auth prerequisite, but there's no explicit when-to-use/when-not guidance (e.g., when to prefer list_alerts over search_books).

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, closed-world behavior. The description adds useful substance beyond that by describing the return shape (each source with the countries it serves), which matters since no output schema exists.

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 tight sentences, zero waste, with the core purpose front-loaded and the filter behavior following immediately.

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 single optional-parameter read tool with full annotation coverage, the description supplies everything needed: what it returns, and how the one parameter affects results.

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 country parameter already documents the ISO 3166-1 alpha-2 pattern. The description's mention of filtering by buyers served adds a little meaning but largely restates the schema, 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 (List) and resource (bookseller catalogs Near Fine searches), plus what each entry carries (countries served). This clearly distinguishes it from search_books and the alert tools.

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 second sentence explains that passing a country narrows results to sources serving buyers there, giving clear usage context for the optional filter. It does not name alternatives or when-not-to-use, keeping it just short of a 5.

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 establish a safe, read-only, idempotent, open-world search, and the description adds substantial behavioral context beyond them: filtering rules for price caps and formats, cheapest-first ordering, currency handling, shipping inclusion rules, match scores, attribute verdicts, source failure reporting, and expected latency. There is no contradiction with 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?

The description is front-loaded with purpose and query guidance, but it is heavily bloated by an exhaustive list of dozens of booksellers that does not help an agent invoke the tool. The remaining return-value and behavior details are valuable, so the structure is functional but not concise.

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 full burden of explaining returns, and it does so thoroughly: offers, seller, condition, prices and currencies, URLs, match scores, attribute verdicts, source status, amazon_url, and search_url. It also notes the few-second latency, making the definition complete for calling and interpreting the tool.

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 would be 3, but the description adds meaningful query semantics beyond the schema: examples like 'wolf hall signed first edition under £200', currency behavior for price caps, and which requested attributes are filtered or judged. Country is handled mostly by the schema, but overall the description enriches parameter interpretation.

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: search for a book across all booksellers Near Fine covers for the buyer's country. It distinguishes exact ISBN lookups from title/author keyword searches and mentions price caps and format attributes, so an agent knows what the tool is for without opening the 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?

It clearly explains how to use the tool: pass an ISBN for an exact edition, or title and author keywords, optionally with a price cap or attributes such as first edition, signed, hardcover, ebook, or audiobook. It does not explicitly compare against sibling tools like set_alert or list_sources, but those are not search alternatives, so the guidance is strong though not fully comparative.

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 well beyond the annotations: discloses the six-month checking window, single email notification, that pre-existing listings never trigger, that an alert stays pending until its first check, that re-setting is a no-op (consistent with idempotentHint=true), and that a full plan returns an error with a plans_url workaround. This is exactly the mutation-side context the annotations do not carry.

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?

Purpose is front-loaded and the ordering (what it does, how it behaves, what it returns, error case) is logical. A few sentences are clause-heavy and slightly run-on, but every one carries information rather than repeating structured fields.

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 correctly shoulders the burden by enumerating the return payload (alert, status, link, plan quota/usage/check frequency) and the failure mode (full plan as an error, upgrade at plans_url). Nothing needed to call it correctly 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 coverage is 100% so the baseline is 3, but the description adds real meaning by saying the query is parsed exactly as search_books parses it, and by spelling out what the alert matches (condition, signature, price cap) — semantics the schema example only hints at.

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 (Set) and resource (an alert) scoped to a search query, which is clearly distinct from sibling actions like cancel_alert and list_alerts. It also pins down what the resulting alert does — checks for six months, emails once — so the agent knows exactly what object it is creating.

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 clear context for the operation (an alert on a search that gets periodically re-checked) and clarifies the query syntax by reference to search_books. It does not explicitly state when to prefer this over a one-off search_books call or how it relates to list_alerts, so there is no explicit exclusion guidance.

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