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

No annotations provided, so description carries full burden. It describes autonomous conversation, structured outcome, and async delivery, but does not disclose side effects, rate limits, cost, or auth requirements beyond the 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?

Three concise paragraphs, front-loaded with the main action. Every sentence adds value, with no fluff or redundancy.

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?

Fairly complete for a call initiation tool: covers async behavior, input hints, and duration. Missing detailed return value structure (no output schema), but mentions 'structured outcome' implicitly.

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 description adds value by explaining the role of lead_context ('Tell Vora everything you know') and specific_objective as a refinement. Does not redundantly repeat schema details.

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 states the verb 'Make an outbound phone call using your voice agent,' specifying the resource (phone call) and distinguishing it from siblings like vora_calls and vora_create_agent.

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?

Provides guidance on call duration (1-5 minutes), two methods for result retrieval (polling vora_calls vs. callback_url), and emphasizes providing lead_context. Lacks explicit when-not-to-use or alternatives to other tools.

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 provided, so description must convey behavior. It describes a read-only query operation, mentions AI-generated recommendations, and implies no side effects. Could explicitly state non-destructive nature, but sufficient.

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?

Efficiently uses bullet points, front-loads purpose. Every sentence adds value. No redundant or vague wording.

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?

Covers main use cases and analytics feature. No output schema, but description hints at return content. Could mention defaults (e.g., last=10) or pagination, but adequate for typical usage.

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?

Input schema has 100% coverage; all parameters have descriptions. Description maps to some params (call_id, agent_id, include_analytics) but adds little extra meaning beyond listing them. Baseline score of 3 is 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?

Description clearly states the tool queries call history, results, and analytics. Lists specific use cases (specific call, recent history, aggregate analytics). Distinguishes from sibling 'vora_call' (singular) by covering multiple calls and analytics.

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?

Provides explicit scenarios (by call_id, agent_id, analytics). Lacks comparison with siblings like 'vora_call' for single-call vs. list/analytics. Still offers clear context for when to use.

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?

Without annotations, the description carries full burden. It discloses key behaviors: the agent persists across calls, improves over time, and automatically compiles knowledge, generates objection handling, selects voice/language, and builds workflows. This provides sufficient transparency.

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 concise and well-structured. It starts with a clear purpose, then uses bullet points to list automatic features. Every sentence is informative without redundancy.

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?

Given 5 parameters and no output schema, the description covers prerequisites, automatic behaviors, and parameter details. It does not specify the return value (e.g., agent ID), but this is a minor gap. Overall, it provides sufficient context for using the tool.

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 baseline is 3. The description adds value by noting auto-detection for 'workflow' and 'language', and clarifying 'additional_context' as extra beyond registration. This enhances understanding beyond 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?

The description clearly states the tool's purpose: 'Create a persistent voice agent for a specific use case.' It uses a specific verb ('create') and resource ('voice agent'), and distinguishes from sibling tools like vora_update_agent by focusing on creation.

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 explains the prerequisite of having a registered account (via vora_register) and notes that multiple agents can be created for different use cases. It implies when to use the tool, but does not explicitly contrast with alternatives like vora_update_agent.

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 burden. It discloses the multi-turn nature, that questions are returned, and that completion yields an account_id and API key. It does not mention error handling or rate limits, but the iterative process and outcome are well communicated.

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 well-structured in three paragraphs: purpose, multi-turn process, and outcome. It is concise enough to convey all necessary information without excessive repetition. It could be slightly more concise, but it earns its length.

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?

Given the tool's complexity (multi-turn, no output schema, no annotations), the description provides a complete picture for an agent: how to start, continue, and detect completion. It mentions the expected outputs (account_id and API key) and the status check. It lacks error handling details but is sufficient for correct invocation.

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 baseline is 3. The description does not add significant meaning beyond the schema; it only reiterates the multi-turn context. The schema already explains each parameter. Therefore, no extra value is provided.

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 states the tool's purpose: 'Create your Vora account through conversational onboarding.' It also distinguishes itself from siblings (vora_call, vora_calls, vora_create_agent, vora_update_agent) by focusing on account registration, which is a unique action. The multi-turn process is well explained.

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 provides clear usage guidelines: call the tool, answer questions, repeat until status 'complete'. It explains that this produces better voice agents than one-shot configuration. However, it does not explicitly contrast with siblings or state when not to use it, but the purpose is distinct enough to infer.

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, so description carries full burden. Discloses that changes take effect on the next call and that apply_learnings analyzes past calls. Lacks details on permissions, error handling, or idempotency.

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?

Well-structured with a clear opening, bullet list of use cases, and a concluding note on effect. Could be slightly more concise, but generally efficient.

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?

Given the complexity of 7 parameters and no output schema, the description covers the main actions and effects. Explains each parameter's role and the overall behavior, though it could mention parameter combinations.

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% with detailed descriptions, but the description adds value through concrete examples (e.g., 'We already use Toast' for objection) and usage scenarios, enhancing meaning beyond 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?

The description clearly states the tool is for incrementally improving a voice agent without full recompilation, listing specific use cases. It distinguishes from sibling tools like vora_create_agent (creation) and vora_call (calls) by focusing on updates.

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?

Provides clear context on when to use (for incremental updates) and when to force a full recompile (website significantly changed). Does not explicitly exclude alternatives but implies usage scenarios.

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