VISEON Ask

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

No annotations are provided, so the description carries the full behavioral burden, yet it discloses nothing about result limits, pagination, ordering, or whether the search is exhaustive. The existence of an output schema covers return shape but not runtime behavior of the lookup.

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 efficient sentence with the core scope front-loaded and no filler. It is terse to the point of under-specifying, but nothing is wasted.

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 an output schema present, return values need not be explained, and a one-parameter lookup is inherently simple. Still, with no annotations and no behavioral notes, an agent lacks information on result size, pagination, and how to disambiguate from the other retrieval siblings.

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 0%, so the description must compensate. It does add meaning: the parameter is a schema.org type identifier and the tool returns all entities of that type, which is more than the bare 'type: string' schema says. However, it does not specify format (full URL vs. short name) or case sensitivity.

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 ('Find') and resource ('all entities of a specific schema.org type'), which is enough to understand the operation. It does not differentiate itself from siblings like get_entity or fuzzy_find_and_traverse, which also retrieve entities.

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 prefer this over get_entity (single entity lookup) or fuzzy_find_and_traverse (fuzzy, relationship-aware search). The agent must infer the use case from the name 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?

With no annotations provided, the description carries the full behavioral burden. It does disclose return behavior ('bounded entity context with relationship IDs') and that ranking occurs, but says nothing about read-only/non-destructive nature, permission requirements, or performance. 'Find/rank' implies a safe read, but the safety profile is left to inference.

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, purpose front-loaded ahead of the sibling pointer, with zero filler. Every clause earns its place by either describing the operation or routing to the alternative.

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?

The tool is moderately complex (4 params, nested weights, output schema), and the description covers purpose, return shape, and the handoff to get_entity; the output schema removes any need to explain return values. It falls just short of complete by not clarifying the boundaries against the other finder siblings.

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%, including documentation of the nested weights object and enum-like entity type list, so the schema does the heavy lifting. The description adds no parameter-level detail (no mention of limit bounds, weights, or type filtering), which is acceptable at full coverage but yields the baseline 3.

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 ('Find and rank schema.org entities from natural language') and explicitly routes the agent to get_entity for full detail, which cleanly separates it from that sibling. However, it does not differentiate itself from find_by_type or search_content, which also retrieve entities, leaving some ambiguity about which finder to pick when the query is not clearly natural language.

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 phrase 'from natural language' implicitly defines the condition that selects this tool, and 'use get_entity for full detail' names the alternative and the reason to switch. It stops short of stating exclusions versus find_by_type or search_content, so no explicit when-not 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?

No annotations are supplied, so the description carries the full burden, and it discloses almost nothing beyond the read verb. It does not state error behavior for an unknown URL, whether unresolved/redirected URLs are followed, or any rate/access constraints; 'complete data' is the only behavioral hint.

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 the verb, resource, and retrieval key in order and no filler. Nothing could be removed without losing 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 one-parameter read tool with full schema coverage and an existing output schema, the description covers what is needed to invoke it correctly. The remaining gap is purely behavioral (failure modes, URL handling), which is minor given the tool's simplicity.

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% and the single 'url' parameter is already documented as 'Full URL of the entity'. The phrase 'by URL' reinforces that the entity is identified by its canonical URL, but adds no format or validation detail beyond the schema, so 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?

The description states a specific verb ('Get') and resource ('schema.org entity data') with the retrieval key ('by URL'), so an agent immediately knows this is a direct fetch of a single entity. It does not, however, contrast itself against siblings like find_by_type or fuzzy_find_and_traverse, which is the only thing keeping it from 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?

Usage is only implied: 'by URL' signals the caller must already possess the entity's URL, which implicitly separates it from the search/discovery siblings. There is no explicit when-to-use, when-not-to-use, or named alternative, so it stays at implied 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?

With no annotations, the description carries the full behavioral burden and mostly fails it. It does not disclose whether this is a read-only traversal, how deep it traverses, whether results are directional, or any scoping/limit behavior — all important for a relationship-graph query.

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, which is efficient. But it is terse to the point of under-specification for a 2-parameter graph query tool.

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?

An output schema exists, so return-value explanation is not required. Still, for a graph query sitting among overlapping traversal siblings, the definition omits both the predicate parameter's meaning and any usage routing, leaving the agent under-informed.

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%. The description implies 'subject' means the entity to start from, but the optional 'predicate' parameter is never mentioned, leaving a filter parameter entirely undocumented in both schema and description.

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 clear verb ('Find') and resource ('entities connected to a subject'), so the purpose is discernible. However, it offers no differentiation from siblings like fuzzy_find_and_traverse or find_by_type, which plausibly overlap with this graph-traversal use case.

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 tool versus the four siblings, no prerequisites, and no exclusions. The agent must infer that this is the direct relationship lookup while fuzzy_find_and_traverse is the fuzzy variant, which is exactly the routing decision the description should make explicit.

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?

No annotations are provided, so the description carries the full burden of behavioral disclosure. 'Full-text search' implies read-only semantics but nothing is said about result limits, ranking, pagination, or matching behavior. An output schema exists, which reduces the need to describe returns, but the description still adds almost no behavioral context.

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 a single five-word phrase with no filler and the action is front-loaded. It is efficient, though its brevity reflects under-specification rather than disciplined conciseness.

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 only one required parameter and an output schema handling the return value, the description barely clears the bar. It is nonetheless thin for a tool that must be distinguished from three other search-like siblings in a crowded namespace.

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% and the sole parameter 'query' is a bare string with no description. The phrase 'full-text search' weakly implies the parameter is the search expression, but no syntax, matching rules, or examples are given to compensate for the schema gap.

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 verb (search) and resource (content across the graph) plus the search mode (full-text), so the purpose is unambiguous. However, it makes no attempt to differentiate from siblings like fuzzy_find_and_traverse, which sounds like an adjacent search capability.

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 indication of when to use this tool versus find_by_type, fuzzy_find_and_traverse, or get_entity. No prerequisites, no exclusions, no alternative routing are provided.

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