SmartVisuals Catalog

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

The annotations already declare readOnlyHint=true and openWorldHint=false, so the safety profile is covered. The description adds useful return details, including slug, name, publication status, and match reason, but it does not disclose ranking behavior, pagination, or limits beyond what the schema provides.

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 three tightly written sentences: purpose first, return shape second, usage context third. Every sentence contributes useful information without repetition or 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 two-parameter read-only search tool with no output schema, the description is complete enough to call correctly. It explains the search scope, return fields, match reason, and typical discovery use case.

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 query and limit are already documented in the schema. The description gives example query phrases, which adds some meaning, but it does not explain parameter syntax or limit behavior beyond the schema baseline.

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 and resource: 'Search the SmartVisuals catalog by keyword.' It also describes what is returned, but it does not explicitly differentiate itself from sibling tools such as list_visuals or get_visual.

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 gives a clear usage context: use it to discover which visual fits a reporting need, with examples like 'retention cohort' and 'radar comparison.' However, it does not state when not to use it or name alternative tools for listing or retrieving details.

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 and openWorldHint=false, so the safety profile is covered. The description adds valuable return-content detail by explaining that the snippet includes the publicCustomVisuals GUID array and a queryState template with placeholder field references.

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, front-loaded with the return value and followed by the usage condition. There is no redundant or filler text.

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 tool with one fully documented parameter, no output schema, and safety annotations, the description is complete enough. It explains both what is returned and when to use 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 description coverage is 100%, so the single slug parameter is already documented as the visual URL slug. The description adds no additional parameter semantics beyond what the schema provides, which is the baseline expectation 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 states a specific verb and resource: return the PBIR layout snippet and binding notes for a SmartVisuals visual. It clearly distinguishes the output from general visual lookup tools by describing the snippet contents, though it does not explicitly name sibling 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?

It gives a clear usage condition: use this when programmatically adding a SmartVisuals visual to a Power BI report layout file. It does not mention when not to use it or name alternatives, but the context is unambiguous.

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 readOnlyHint=true and openWorldHint=false, so the safety profile is covered. The description adds real value by enumerating what the response contains (GUID, data roles, version, use cases, tier limits, diagnostic flags), which matters because there is no output schema. It omits error behavior for an invalid slug.

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: the scope/return payload comes first, then the workflow note. Every clause carries information an agent would otherwise have to guess.

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 one well-documented parameter, no nested objects, and no output schema, the description's return-field enumeration closes the main gap. Only the failure mode for an unrecognized slug is left unspecified.

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 slug parameter is documented in the schema with concrete examples ('gantt-chart', 'radar-chart'). The description only implies the identifier via 'one ... visual' and adds no format or matching detail beyond the schema, so the 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 ('Return the full catalog entry') and a precise resource ('one SmartVisuals Power BI custom visual'), then enumerates the returned fields. The 'one ...' scope cleanly separates it from the listing siblings find_visuals/list_visuals.

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?

Explicitly sequences it: 'Use after find_visuals to inspect a specific visual,' which tells the agent the discovery-then-detail workflow. It does not address when NOT to use it (e.g., use list_visuals for bulk needs) or what happens on an unknown slug, so it falls short of full alternative routing.

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 and openWorldHint=false, so the safety profile is covered and the description's job is lighter. The description adds real value by disclosing the returned fields (slug, name, shortName, status) and defining what each status means—context that is not in any structured field.

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 tight sentences: the action and scope, the filter with its value definitions, and the return shape. The scope is front-loaded and nothing is repeated for padding.

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-parameter read tool with no output schema, it covers action, filter semantics, and return fields—enough for an agent to call it correctly. It does not mention result size or pagination, which matters for a 'list every visual' call on a potentially large catalog.

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 enum is already typed, so the baseline is 3. The description earns an extra point by defining the domain meaning of each enum value ('live' = published on Microsoft Marketplace, etc.)—semantics the schema only names, not explains.

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 definition pairs a specific verb ('List') with a specific resource ('every visual in the SmartVisuals catalog') and names the fields returned. It implicitly distinguishes itself from find_visuals by promising an exhaustive enumeration, though it never names that sibling explicitly.

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 explains the optional filter ('Omit to return all visuals'), which gives clear usage context for the one parameter. It offers no guidance on when to prefer this over find_visuals or get_visual, so the agent must infer the distinction from the 'every visual' wording.

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