PolarJay

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

Annotations already declare readOnly, idempotent, closed-world and non-destructive, so safety is covered. The description contributes the return format ('full text ... as Markdown'), which matters because there is no output schema, though it says nothing about behavior for missing or invalid routes.

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 what is returned, then the required input, then the scope limit. No sentence is filler.

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 with full annotation coverage, this covers purpose, input format, and return type. The remaining gap is error behavior for a path outside the site or a non-existent page, which the description leaves 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%, so baseline is 3, but the description adds value beyond the schema by giving concrete example paths (/en/pricing, /en/how-it-works), which reveals the localized route structure that the schema's generic 'starting with /' does not.

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 the specific resource ('the full text of one page of polarjay.com as Markdown'), which is clear and concrete. It is a generic page reader, but it doesn't explicitly contrast itself with siblings like get_pricing or get_product, which serve structured subsets of the same site.

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?

'Only pages of polarjay.com' is a scope constraint, not guidance on when to pick this over get_pricing or get_product. Usage is implied (reach for this when you need raw page text), but the alternatives are never named or excluded.

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 as a safe, read-only, idempotent operation. The description adds useful scope details: prices are in US dollars, exclude tax, include queries, free trial, done-for-you service, free scanner, and the pricing page URL.

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 compact sentence that front-loads the key pricing scope and content list. It is efficient, though it lacks an explicit verb such as 'returns' that would make the action even clearer.

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 read-only pricing content tool with one optional parameter and no output schema, the description sufficiently explains what information is returned and its currency/tax basis. No important gaps remain for an agent deciding whether to call it.

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 single optional locale parameter is already documented in the schema. The description does not add meaning about locale, which is acceptable given that the schema carries this burden.

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 clearly identifies the resource as published plans and enumerates what the response includes, distinguishing it from generic page or FAQ content. It does not explicitly say how it differs from the sibling get_product, so it stops short of full sibling differentiation.

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 explicit guidance on when to call this tool versus alternatives such as get_product or get_page. The pricing focus implies usage, but no conditions or exclusions are stated.

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, so the safety profile is covered; the description adds the substantive value of what the response contains, including source URLs for every fact and future/roadmap assistants. There is no output schema, so this return-content disclosure is doing real work, though pagination/format details are absent (trivial for a single-object read).

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 front-loaded sentence led by the imperative 'Use this first', with no filler. The trailing enumeration is long but every item tells the agent something about scope, so it earns its length, if only just.

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 compensates by listing the returned content in detail, and annotations cover safety. The only minor omission is any mention of the locale parameter or output shape, which is low-stakes for a single-item descriptive read.

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 'locale' parameter is fully documented as an enum with only 'en'. The description says nothing about locale, so it adds no meaning beyond the schema — 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+resource ('describe PolarJay') and enumerates exactly what the response covers (capabilities, measured assistants, languages, audience, operator, source URLs), which separates it from get_pricing / how_to_start / list_faq by content. It never names a sibling explicitly, so differentiation is inferred rather than stated.

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 first' gives a clear ordering cue that this is the entry-point tool for the product overview. It gives no explicit when-not condition or named alternative for the overlapping siblings (get_page, list_faq), leaving that 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, and closed-world, so the safety profile is covered. The description adds value beyond that by disclosing what the payload contains (two signup URLs and a contact address), which matters because there is no output schema.

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; the key distinction (two starting paths, no sign-up / no card) comes first. The trailing 'plus the contact address' is slightly list-like but still earns its place by signaling scope.

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-required-param informational tool with no output schema, the description gives an adequate preview of the return contents. It does not explain whether URLs are localized or how the data is structured, but no important calling decision is left unclear.

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?

Only one optional parameter (locale) with 100% schema description coverage and an explicit enum, so the schema carries it entirely. The description contributes nothing about locale or default behavior, which is acceptable at this coverage level but not additive.

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 — the two onboarding paths (free scanner, free trial) plus URLs and a contact address — which is specific enough to distinguish it from get_pricing, get_product, and list_faq. It stops short of a clean verb+resource statement (it reads as a content inventory rather than 'Returns...'), so not a 5.

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 'how to start' framing implies the trigger (a new user asking how to get going), but there is no explicit when-to-use guidance and no routing against siblings such as get_pricing, which overlaps with the 'free trial' content mentioned here.

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 and openWorldHint=false, so the safety profile is fully covered. The description adds that results are published content rather than drafts and that filtering is optional, but says nothing about ordering, result count, or whether the full list is small enough to fetch unfiltered.

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 the resource stated first and the filtering behavior second; nothing is redundant or buried. It is arguably slightly under-sized for a tool with two parameters and no output schema.

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, so the description should hint at the return shape; it implies question/answer pairs but never says whether these are returned as a list, whether the answer is rendered text or markup, or what an empty result looks like. For a simple read tool this is close to adequate but not complete.

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 meaning the schema lacks: the query terms match against either the question text or the answer text, which the schema's generic 'Words to look for' does not convey. The locale parameter's effect is left entirely to the schema, so it is not a full 5.

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 resource (the questions and answers published on the PolarJay FAQ page) and its scope, which is clearly recognizable against siblings like get_pricing or get_product. It does not explicitly contrast itself with those siblings, but the resource noun does the differentiating work.

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 word 'Optionally filtered' signals that calling with no parameters returns the full set and that the filter is a narrowing path, so usage is implied. There is no explicit when-to-use/when-not guidance and no reference to an alternative tool for FAQ-adjacent questions.

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