Rankera

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

The annotations already declare readOnlyHint=true, idempotentHint=true, destructiveHint=false, and openWorldHint=false, covering the safety and side-effect profile. The description adds value by stating the return format ('Returns markdown with the source page'), which is not in the annotations. It does not mention rate limits, auth needs, or latency, but for a read-only, idempotent Q&A tool, this is sufficiently transparent.

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?

One tightly written sentence that front-loads the tool's purpose, scope, and return format. No redundant or filler text; every clause adds 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?

For a single-parameter, annotation-rich, read-only Q&A tool with no output schema, the description covers purpose, scope, return format, and an analogous web endpoint. The only missing piece is explicit guidance on when to choose this over siblings like get_pricing or search_site.

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% (the 'question' parameter is documented with a concrete example). The description adds the transformation rule (hyphenated URL slug), which is useful but not essential for calling the tool. Baseline 3 when schema already fully documents the parameter.

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 states a specific verb+resource ('Answer a plain-language question about Rankera') and clarifies the scope ('from its verified facts and its own pages'), distinguishing it from siblings like get_page or search_site by being a Q&A tool rather than a raw fetch or search.

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 implies usage (plain-language Q&A) and provides a crucial alternative form ('the same answer as fetching rankera.ai/{question-with-hyphens}'), but it does not explicitly say when to use this tool versus the siblings get_brand_facts, get_page, get_pricing, etc. No exclusions or explicit 'use this instead of X' 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 this a safe, idempotent, read-only, non-open-world fetch, so the bar is low. On top of that the description discloses the nature of the payload, notably that it contains 'what not to state,' which tells the agent the output carries compliance constraints rather than plain data.

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 zero filler: the first front-loads what the tool returns, the second immediately states when to call it. Every clause earns its place.

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 and no parameters, the description carries the burden of describing the return content, which it does by enumerating the fact categories. It does not describe the format or granularity of the facts returned, a minor remaining gap for a static-content 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?

The tool takes zero parameters, so there is no parameter semantics for the description to supply; baseline 4 applies. The description correctly implies a self-contained, no-argument 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 a specific resource (verified brand facts about Rankera) and enumerates its contents: identity, pricing, inclusions, policies and prohibited statements. It is clearly distinguishable from generic page/search tools, though it does not explicitly contrast itself with the overlapping sibling get_pricing.

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?

'Use this before describing Rankera' gives an explicit trigger condition for invocation rather than leaving usage to inference. It lacks any when-not-to-use guidance or named alternatives among the siblings, so it stops 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 declare readOnly, idempotent, non-destructive, and closed-world behavior, so the safety profile is covered. The description adds useful behavior context by stating the output is 'clean markdown' and that only 'published' pages are served. It says nothing about failures for unpublished or off-site URLs, but that is a minor gap.

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?

One sentence with zero filler, front-loading the return format and the domain scope. It is a noun phrase rather than a verb clause, so the action is only implied by the title, which slightly weakens the opening.

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 one-parameter read tool, the description covers the return artifact (markdown) and the scope (published pages), and annotations carry the safety profile. It still omits what happens for unpublished pages or invalid URLs and gives no retrieval guidance, leaving modest gaps.

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% with a single well-documented url parameter, so the baseline is 3. The description's 'published page on rankera.ai' reinforces the accepted domain constraint and the markdown return, but adds no syntax or format detail 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 names a specific resource (published pages on rankera.ai) and its return artifact (clean markdown), which is concrete enough for an agent to know what it fetches. It doesn't explicitly contrast with siblings like search_site or ask_question, but 'any published page' implies direct fetch rather than query-driven retrieval.

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 use this rather than search_site, ask_question, or list_services. The only implicit signal is 'published page', which hints at scope but does not tell the agent which sibling to pick for a given request.

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, idempotentHint, destructiveHint=false, and openWorldHint=false, so safety and caching behavior are covered. The description adds nothing beyond them — no statement of return format, currency, freshness, or whether pricing is region-dependent.

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?

It is a single short fragment with no waste, but it is under-specified rather than genuinely concise — a lead position is wasted on phrase rather than an action statement.

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 should carry more of the return-value burden; 'what each includes' hints at plan contents but not structure, currency, or tier count. Annotations make correctness of invocation clear, so the gap is moderate rather than severe.

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 has zero parameters, so per the rubric the baseline is 4. There is nothing parameter-related for the description to explain, and it does not mislead about inputs.

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 phrase names the subject matter (plans, prices, and inclusions) but is a noun fragment with no verb, so it never states that the tool retrieves or returns anything. It also does nothing to distinguish itself from siblings like get_brand_facts or list_services, which could plausibly overlap in returning site content.

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 when-to-use statement, no prerequisites, and no named alternative among the five siblings. The agent must infer from the name alone that this is the pricing lookup.

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 safety, repeatability and closed-world scope are covered. The description only adds that each entry carries a one-line description; it says nothing about whether the list is exhaustive, ordered, or paginated. With no output schema, that return-shape gap is a real, if modest, miss.

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 no wasted clauses, and the parenthetical enumerating channels/features/services is the most informative part, placed early. Slightly awkward phrasing ('What Rankera offers') costs it the top score.

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 zero-parameter read tool, complexity is low and the description does disclose that each item has a one-line summary. But with no output schema, it should say more about what the response contains (count, ordering, whether prices or links are included) so the agent can decide whether it still needs get_pricing.

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. No parameter-level context is needed or expected here.

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 conveys the resource (Rankera's offerings: channels, features, services) but opens with a noun phrase rather than a verb and never states the operation explicitly as a listing action. It also does nothing to separate this catalog from siblings like get_pricing or get_brand_facts, which an agent could plausibly confuse it with.

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 when-to-use guidance, no condition selecting this over search_site or get_page, and no exclusions. The agent must infer from the name alone that this is the catalog-enumeration entry point.

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 readOnly, idempotent, non-destructive and closed-world behavior, so safety is covered. The description adds value beyond them by enumerating what each result carries (titles, URLs, markdown URLs, descriptions) even though no output schema exists, though it omits the result-count cap of 20 and the default of 8.

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: scope first, then the return contents and the follow-up call. Every clause is actionable.

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?

There is no output schema, and the description compensates by listing returned fields and pointing at get_page for follow-up. The only real gap is the undocumented limit/pagination behavior, which is minor for a simple keyword search.

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 carries the full burden, yet it only implies that query takes keywords. The limit parameter, its default of 8 and maximum of 20, and any guidance on result volume are never mentioned.

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 (search) plus a precise resource and scope (every page on rankera.ai) and the matching mode (by keywords). It also names the sibling get_page as the read counterpart, so an agent can separate it from ask_question or list_services 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 an explicit next-step rule: use get_page to read a result, which establishes search-then-read workflow. It does not say when to prefer this over ask_question or the other lookup siblings, so exclusions are missing.

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