Alai

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

The description adds valuable behavioral context beyond what annotations provide. While annotations indicate this is a write operation (readOnlyHint: false) that's non-destructive and works in an open world, the description reveals this is an asynchronous operation that returns a generation_id for polling, which is crucial implementation detail not captured in annotations.

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 perfectly structured and front-loaded: purpose statement first, then organized parameter explanations, and finally return value clarification. Every sentence earns its place with zero redundancy or wasted words, making it highly scannable and 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 tool's complexity (5 parameters, asynchronous operation, sibling tools) and the presence of an output schema (which handles return value documentation), the description provides complete contextual information. It covers purpose, all parameter meanings, usage guidance, and behavioral characteristics without needing to duplicate what the output schema will specify.

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?

With 0% schema description coverage, the description fully compensates by explaining all 5 parameters' meanings and behaviors. It clarifies presentation_id identifies the target, slide_context provides content, slide_type has specific options with default, additional_instructions offers extra guidance, and slide_order controls positioning with append behavior when omitted.

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 with a specific verb ('Add') and resource ('slide to an existing presentation'), distinguishing it from siblings like generate_presentation (creates new presentation) or delete_slide (removes slide). The opening sentence directly communicates the core functionality.

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 context about when to use this tool (to add slides to existing presentations) and implies when not to use it (for creating new presentations, which would be generate_presentation). However, it doesn't explicitly name alternatives or provide exclusion criteria beyond what's implied by the purpose statement.

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 description adds valuable behavioral context beyond annotations: it specifies that deletion is 'permanent' and affects 'all its slides,' which clarifies the irreversible and comprehensive nature of the operation. Annotations already indicate destructiveHint=true and readOnlyHint=false, so the description complements rather than contradicts them by detailing the scope of destruction.

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, front-loaded sentence with zero wasted words. It efficiently conveys the core action and scope without redundancy, making it highly concise and well-structured for quick understanding.

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 (destructive operation with 1 parameter), annotations cover safety aspects (destructiveHint, readOnlyHint), and an output schema exists, reducing the need for return value explanation. The description adequately covers the permanent and comprehensive deletion behavior, though it lacks parameter guidance, keeping it from a perfect score.

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?

The description does not mention the presentation_id parameter or provide any additional semantic details about it. With 0% schema description coverage and 1 parameter, the baseline is 4 for zero parameters, but since there is one undocumented parameter, the description fails to compensate, resulting in a score of 3 as it adds no parameter-specific value 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 specific action ('Permanently delete') and resource ('a presentation and all its slides'), distinguishing it from sibling tools like delete_slide (which only deletes individual slides) and get_presentations (which retrieves presentations). It precisely communicates the tool's destructive scope.

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 implies usage for deletion scenarios but does not explicitly state when to use this tool versus alternatives like delete_slide or export_presentation. It provides no guidance on prerequisites (e.g., needing the presentation_id) or exclusions, leaving usage context inferred rather than clearly defined.

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 indicate this is a destructive, non-read-only operation, but the description adds value by explicitly stating the action ('Delete'), which aligns with the annotations. However, it doesn't provide additional behavioral context like confirmation requirements, irreversible effects, or permission needs beyond what annotations imply.

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, clear sentence with no wasted words. It's front-loaded with the core action and resource, making it highly efficient and easy to parse.

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 destructive nature (annotations show destructiveHint: true) and the presence of an output schema, the description is minimally adequate. However, for a destructive operation, it could benefit from more context about consequences or error handling, though the output schema may cover return values.

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?

With 0% schema description coverage, the description doesn't explain the parameters 'presentation_id' and 'slide_id' at all. However, since there are only 2 required parameters and their names are self-explanatory, the baseline is appropriate. No additional semantic details are 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 action ('Delete') and target resource ('a slide from a presentation'), making the purpose immediately understandable. However, it doesn't differentiate from sibling tools like 'delete_presentation' or 'create_slide' beyond the obvious scope difference.

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 no guidance on when to use this tool versus alternatives like 'delete_presentation' for removing entire presentations or 'create_slide' for adding slides. It lacks context about prerequisites, error conditions, or typical workflows.

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 indicate this is a non-destructive, non-read-only operation, which the description aligns with by describing an export process. The description adds valuable context beyond annotations: it explains the asynchronous behavior (returns generation_id to poll), mentions download URLs upon completion, and lists specific output formats. However, it doesn't cover rate limits, authentication needs, or error conditions.

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 front-loaded with the core purpose in the first sentence, followed by structured parameter explanations and return behavior. Every sentence adds value: the first defines the tool, the Args section clarifies inputs, and the Returns section explains the asynchronous process. No wasted words 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?

Given the tool's moderate complexity (asynchronous export with multiple formats), the description is fairly complete. It covers purpose, parameters, and return behavior. With an output schema present, it doesn't need to detail return values further. However, it could improve by mentioning prerequisites (e.g., presentation must exist) or error cases, but overall it provides sufficient context for effective use.

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?

With 0% schema description coverage, the description compensates well by explaining both parameters: presentation_id is described as 'ID of the presentation to export', and formats is detailed with a list of options ('link', 'pdf', 'ppt') and a default value (['link']). It adds meaning beyond the bare schema, though it could clarify if formats is required or optional beyond the default note.

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 with specific verbs ('export') and resources ('presentation'), listing the output formats (PDF, PPTX, link). It distinguishes itself from siblings like create_slide, delete_presentation, and get_presentations by focusing on export functionality rather than creation, deletion, or retrieval.

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 implies usage by mentioning the need for a presentation_id and the asynchronous nature (returns generation_id to poll), but it doesn't explicitly state when to use this tool versus alternatives like generate_presentation or get_presentations. No exclusions or specific contexts are provided, leaving usage somewhat open to interpretation.

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 indicate this is not read-only (readOnlyHint: false) and not destructive (destructiveHint: false), but the description adds valuable behavioral context beyond annotations. It explains the asynchronous workflow ('Returns a generation_id to poll' and 'Poll get_generation_status until status is completed'), mentions cost implications ('Increases cost' for num_creative_variants), and provides default behaviors (e.g., language matching input). No contradictions with annotations exist.

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 with a clear purpose statement upfront, followed by a detailed parameter list and workflow instructions. It is appropriately sized for a complex tool with 12 parameters. However, the parameter explanations could be slightly more concise (e.g., some details like 'Increases cost' might be inferred), and the polling instruction is repeated, making it slightly verbose.

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 (12 parameters, asynchronous workflow, cost implications) and the presence of an output schema (which handles return values), the description is complete. It covers purpose, usage guidelines, parameter semantics, behavioral traits (asynchronous polling, cost), and references to sibling tools. The annotations provide safety context, and the description fills in all necessary operational details without redundancy.

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?

With 0% schema description coverage and 12 parameters, the description carries the full burden of explaining parameters. It provides detailed semantics for all parameters: examples (e.g., slide_range: 'auto', '1', '2-5'), constraints (e.g., num_creative_variants: '0-2'), dependencies (vibe_id requires num_creative_variants >= 1), defaults (export_formats defaults to ['link']), and references to other tools for discovery (theme_id, vibe_id). This compensates fully for the lack of schema descriptions.

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: 'Generate a presentation from text content.' It specifies the verb ('Generate'), resource ('presentation'), and distinguishes from siblings like 'create_slide' (which likely creates individual slides) and 'export_presentation' (which exports existing presentations). The description also mentions the asynchronous nature with 'Returns a generation_id to poll,' which is a key behavioral aspect.

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 context for usage by referencing sibling tools: 'Call get_themes to discover available theme IDs' and 'Call get_vibes to discover available vibes.' It also mentions prerequisites like 'Requires num_creative_variants >= 1 when set' for vibe_id. However, it doesn't explicitly state when to use this tool versus alternatives like 'create_slide' or 'export_presentation,' which prevents a perfect score.

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 indicate this is a non-destructive, open-world operation (readOnlyHint: false, destructiveHint: false, openWorldHint: true), which the description doesn't contradict. The description adds valuable behavioral context beyond annotations: it explains that the tool returns a generation_id for polling and that transcripts become available upon completion, clarifying the asynchronous nature and output process.

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 appropriately sized and front-loaded: the first sentence states the purpose clearly, followed by a structured 'Args' and 'Returns' section that efficiently explains parameters and output without unnecessary details. Every sentence earns its place, making it easy to scan and understand.

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 moderate complexity (2 parameters, asynchronous operation) and the presence of an output schema (which likely covers the generation_id return), the description is fairly complete. It explains the purpose, parameter usage, and output process. However, it could benefit from more guidance on tool selection vs. siblings and error handling, leaving minor gaps.

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 carries the full burden. It adds meaning by explaining that 'presentation_id' identifies the presentation and 'slide_ids' specifies which slides to process (with omission meaning all slides), which clarifies parameter roles. However, it doesn't provide details on ID formats or slide selection constraints, leaving some semantic gaps.

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 ('generate') and resource ('speaker notes/transcripts for slides in a presentation'), making the purpose specific and understandable. However, it doesn't explicitly differentiate from sibling tools like 'generate_presentation' or 'export_presentation', which might also involve generation or output creation processes.

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 implies usage by specifying 'Omit to process all slides' for the slide_ids parameter, suggesting when to use default behavior. However, it lacks explicit guidance on when to choose this tool over alternatives (e.g., vs. 'generate_presentation' or 'export_presentation') or any prerequisites, leaving some context gaps.

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 description adds valuable behavioral context beyond what annotations provide: it lists the possible status values (pending, in_progress, completed, failed) and provides polling guidance. While annotations already indicate read-only and non-destructive behavior, the description enhances understanding with operational details about timing and state transitions.

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 perfectly concise with three sentences that each serve distinct purposes: stating the tool's purpose, listing status values, and providing usage guidance. There's no wasted text, and the information is front-loaded with the core functionality.

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 has an output schema (which will document return values), annotations covering safety aspects, and relatively simple functionality, the description provides excellent contextual completeness. It covers purpose, status values, polling guidance, and typical completion times - everything needed to understand when and how to use this status-checking 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?

With 0% schema description coverage for the single parameter (generation_id), the description doesn't explicitly explain what generation_id represents. However, the context ('status of an async operation') strongly implies this is an ID returned from an async operation like generate_presentation or export_presentation. This provides meaningful semantic context despite not directly documenting the parameter.

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 with specific verb ('Check') and resource ('status of an async operation'), and explicitly lists the types of operations covered (presentation, slide, export, or transcript). It distinguishes this from siblings like create_slide or export_presentation by focusing on status checking rather than creation/export operations.

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 explicit guidance on when to use this tool ('Check the status of an async operation') and includes specific usage instructions: 'Poll every 2-5 seconds' and 'Most operations complete in 30-120 seconds.' This gives clear temporal context for when and how frequently to invoke the tool.

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 provide readOnlyHint=true, openWorldHint=false, and destructiveHint=false, indicating a safe, read-only operation with limited scope. The description adds context by specifying ownership filtering and the return format (list with IDs and titles), which is useful but does not disclose additional behavioral traits like pagination, rate limits, or error conditions beyond what annotations cover.

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 two sentences, front-loaded with the core purpose and followed by return details. Every sentence adds value without waste, making it efficient and well-structured for quick understanding.

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 simplicity (0 parameters, annotations covering safety, and an output schema), the description is complete. It explains what the tool does, the scope (user-owned), and the return format, which is sufficient as the output schema handles detailed return values.

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?

The input schema has 0 parameters with 100% coverage, so no parameter documentation is needed. The description appropriately does not discuss parameters, earning a baseline score of 4 for not adding unnecessary information 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 specific action ('List all presentations') and the resource ('presentations owned by the authenticated user'), distinguishing it from siblings like create_slide, delete_presentation, or export_presentation. It precisely defines the scope of the operation.

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 implies usage context by specifying 'owned by the authenticated user,' which helps differentiate from tools that might list all presentations regardless of ownership. However, it does not explicitly state when to use this tool versus alternatives like get_themes or get_vibes, nor does it provide exclusions or prerequisites.

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 description adds valuable context beyond annotations: it specifies that themes are filtered to those 'available to the authenticated user' (implying permission-based filtering) and describes the return format (IDs and names). While annotations cover safety (readOnly, non-destructive), the description provides useful behavioral details about output format and authentication scope.

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, perfectly front-loaded with the core purpose first, followed by usage guidance. Every word earns its place with zero redundancy or wasted space. The structure is ideal for quick comprehension.

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 simplicity (0 parameters, read-only operation with good annotations, and an output schema exists), the description is complete. It covers purpose, authentication scope, output format, and downstream usage without needing to explain return values (handled by output schema) or safety (covered by annotations).

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?

With 0 parameters and 100% schema description coverage, the baseline would be 4. The description appropriately doesn't discuss parameters since there are none, and instead focuses on what the tool returns and how to use that output, adding semantic value beyond the empty 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 verb ('List') and resource ('themes available to the authenticated user'), making the purpose specific and unambiguous. It distinguishes itself from siblings like 'get_presentations' or 'get_vibes' by focusing specifically on themes.

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 explicitly states when to use this tool: to get theme IDs and names that can be passed to 'generate_presentation'. It provides a clear alternative by naming the sibling tool where the output should be used, giving perfect guidance on usage context.

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 provide readOnlyHint=true, destructiveHint=false, and openWorldHint=false, covering safety and scope. The description adds valuable context about authentication ('authenticated user'), return format (IDs, names, sources), and downstream usage (for generate_presentation), which goes beyond what annotations provide without contradicting them.

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 two sentences with zero waste: the first states the purpose and scope, the second explains the return format and downstream usage. It's front-loaded with the core function and efficiently structured.

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 simplicity (0 parameters, read-only, non-destructive), rich annotations, and presence of an output schema, the description is complete. It covers purpose, authentication, return details, and integration with generate_presentation, providing all necessary context for an agent to use it correctly.

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?

The input schema has 0 parameters with 100% coverage, so no parameter documentation is needed. The description appropriately focuses on output semantics and usage context, adding value beyond the empty schema. A baseline of 4 is applied for zero parameters.

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 with specific verb ('List') and resource ('vibes available to the authenticated user'), and distinguishes it from siblings by specifying what information is returned (IDs, names, sources) and how it's used (passed to generate_presentation). It's not just a restatement of the name.

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 explicitly states when to use this tool: to get vibe information that 'can be passed as vibe_id to generate_presentation.' It provides clear context about its relationship with the sibling tool generate_presentation, making it evident when this tool should be used versus alternatives.

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 description adds valuable context beyond annotations by specifying that it verifies API keys and returns user IDs. While annotations already indicate it's read-only, non-destructive, and closed-world, the description provides the specific authentication testing purpose and expected return value.

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 perfectly structured sentences: first states the purpose, second provides usage guidance. Every word earns its place with zero redundancy or wasted space.

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 simplicity (0 parameters, annotations covering safety, output schema exists), the description is complete. It explains what the tool does, when to use it, and the expected outcome without needing to detail parameters or return format.

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?

With 0 parameters and 100% schema description coverage, the baseline would be 4. The description appropriately acknowledges this by not discussing parameters, focusing instead on the tool's purpose and usage context.

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 with specific verbs ('verify', 'return') and resources ('API key', 'user ID'), and distinguishes it from sibling tools by focusing on authentication testing rather than presentation/slide operations.

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 states when to use this tool: 'Use this to test authentication.' This provides clear guidance that this is for authentication verification rather than data operations, differentiating it from all sibling tools which handle presentation/slide management.

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