Vitextra Knowledge Base

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

Annotations already cover the safety profile (readOnly, idempotent, not open world), so the bar is lower. The description still adds real value by disclosing the return shape (schema.org objects with url, name, site, score, description, schema_object) despite there being no output schema, though it says nothing about result count or pagination.

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 leads with the capability and then enumerates the return fields. No filler, every clause carries 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 usefully compensates by naming the return format and fields, and annotations cover the safety profile. It is slightly thin on result volume/pagination and on how it compares to sibling search tools.

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 both parameters (query, language) are fully documented in the schema. The description adds no parameter-level detail beyond that, which makes the baseline 3 appropriate.

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 ('question answering over the site content') and adds the return format, so the agent knows exactly what the tool does. However it does not differentiate itself from the sibling search_knowledge_base, which plausibly overlaps in function.

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 'question answering' framing but there is no explicit when-to-use, when-not, or routing to alternatives such as search_knowledge_base or get_document. The agent must infer selection from the tool's nature alone.

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, so the safety profile is covered. The description adds genuinely new behavioral context by disclosing the return format (Markdown) and the breadth of content types it can return, including structured product data such as pricing, features and FAQ.

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, both load-bearing: the first defines the action and output format up front, the second gives provenance guidance for the single required parameter. The content-type enumeration is dense but each item adds discriminating detail rather than 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 single-parameter read tool with 100% schema coverage and no output schema, the description supplies the missing pieces an agent needs: Markdown return format, covered page types, and URL sourcing. Minor omissions remain, such as error behavior for an invalid or out-of-scope URL.

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 schema already documents accepted URL forms (full URL, path, trailing .md), so the baseline is 3. The description goes beyond the schema by stating where valid URLs originate (search_knowledge_base, list_products), which directly improves invocation correctness.

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 ('Read a Vitextra page as Markdown') and enumerates the page classes it covers, so an agent can immediately tell this is the retrieval step. The closing sentence distinguishes it from search_knowledge_base and list_products by naming them as URL sources rather than alternatives.

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 workflow context: pass a url obtained from search_knowledge_base or list_products, which tells the agent this tool follows discovery. It stops short of exclusions, e.g. it never says when to prefer this over the sibling 'ask' tool for answering questions about the same content.

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 readOnlyHint=true, idempotentHint=true, destructiveHint=false and openWorldHint=false, so the safety profile is fully covered structurally. The description's contribution is the return shape (page URLs, Markdown URLs, short descriptions), which is useful given there is no output schema, but it discloses nothing about ordering, completeness, or size of the result set.

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 with zero filler that immediately states the verb, scope, and returned fields. Nothing is redundant or padded.

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 carries the burden of describing what comes back, and it does so adequately for a simple no-required-parameter listing tool. It is only slightly thin on whether results are paginated or ordered, which matters less for a product catalog enumeration.

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 parameter and schema description coverage is 100%, so the schema already documents the two-letter language code and its default. The description adds no further meaning, such as whether language affects the descriptions or just the URLs, so the baseline of 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 ("List all Vitextra products") and even enumerates the return contents (page URLs, Markdown URLs, one-line descriptions). The purpose is unambiguous, though it does not explicitly distinguish itself from siblings like search_knowledge_base or get_document.

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 gives no when-to-use context, no prerequisites, and never names an alternative tool. An agent must infer from the name alone that this is the full-catalog enumeration path versus search_knowledge_base or get_document.

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, closed-world and non-destructive, so the safety profile is covered. The description adds context beyond the annotations by disclosing the return shape (titles, page URLs, Markdown URLs, short descriptions), which tells the agent what it gets back and why a Markdown URL matters.

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: the first establishes scope and coverage, the second states the return fields and the follow-up action. Everything is front-loaded and each 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, the description carries the return-value burden and does so by listing the payload fields, plus it points to the companion tool for full content. Nothing material for correct invocation 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%, so query, limit, category and language are already documented, including the category enum values. The description adds no syntax or format detail beyond the schema, so the baseline of 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 gives a specific verb and resource ('Search Vitextra knowledge base') and enumerates the content types covered (documentation, product pages, how-to guides, FAQ, glossary, blog). It also routes to a sibling ('read a page in full with get_document'), but it does not distinguish itself from 'ask' or 'list_products', leaving partial 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?

It names one alternative ('get_document') and the condition that selects it (need the full page), which is genuine routing guidance. However, there is no guidance on when to search versus using 'ask' to answer a question directly, so the usage context is only partially covered.

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