Xevol Store

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

Annotations already cover read-only, non-destructive, and closed-world, so the bar is lower. The description still adds value beyond them by stating the item is free and that no Workspace-scoped data is returned, redirecting that need to another endpoint.

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?

Front-loaded with the core purpose and compact overall. The trailing sentence is convoluted, and embedding a URL as prose makes the scope note harder to parse than a short clause would.

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 lists what the returned item contains, and it preempts a common confusion about Workspace applicability. Minor gaps remain around behavior for unknown publisher/slug or ambiguous matches.

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 must carry the parameters. It does clarify that 'name' is the publisher name and 'slug' the item slug, both sourced from search_store, which is meaningful. It adds nothing about format or validation beyond the regex patterns already in 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?

States a specific verb and resource: fetch one store item by publisher name and slug, and enumerates what the response contains (behavior, requirements, install footprint, settings, link). It also distinguishes itself from the sibling search_store by noting both keys originate there.

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?

Makes clear this is the follow-up to search_store for a single item and explicitly scopes out Workspace concerns, pointing to the server endpoint that covers them. No explicit 'when not to use' for a single-item lookup, but the flow is clear.

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, openWorldHint=false, and destructiveHint=false, so the safety profile is covered. The description still adds real context: that the tool is free and installs nothing, that results are unranked so the caller must match them to a business, and what the returned link points to. It omits result ordering/pagination behavior.

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?

Front-loaded with purpose, but the sentences are long run-ons that pack filtering, URL templating, and licensing into one paragraph. Phrases like 'match it to the business yourself' are cryptic and the https://xevol.com/<name>/<slug> template adds bulk for modest value.

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 five parameters and no output schema, the description should explain returned data, but it describes only the `link` field of each card. For a search tool whose results must be interpreted and matched by the caller, missing card structure (titles, publisher, kind markers) is a real gap, though the parameter and licensing gaps are otherwise handled.

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 must carry the burden, and it largely does: q is explained as all-words-must-match, goodFor as a kind of customer, app and kind are named as filters, and limit 200 is described as the whole-store retrieval. It omits default values and the meaning of each kind enum value, which the schema only lists without explaining.

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 ('Find') and resource (Xevol's store listings) and enumerates the content types returned (jobs, products, services, screens). It is clear this is a search over the store catalog, though it never names or contrasts with the sibling get_store_item, so differentiation is left implicit.

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 concrete usage context: pass 'nothing' to browse the whole store, and 'q' requires every word to appear in the card. It also warns that matching results to a business is the caller's job. No explicit when-not-to-use or alternative-tool routing is provided.

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