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

With no annotations, the description carries the full burden of behavioral disclosure. It does not explain side effects (e.g., updating invoice balance), partial payment handling, or required invoice state. This is significant for a financial mutation.

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 no filler. It immediately states the action and target, earning a top score for 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?

For a financial operation with 5 parameters and no output schema, the description is too minimal. It does not address payment constraints, effects on invoice status, or return behavior. More context is needed for an agent to use it safely.

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 each parameter having a concise description. The tool description adds no extra meaning beyond what the schema already provides, but the schema itself is sufficient.

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 'Apply a payment to an existing invoice' uses a specific verb and resource, making it clear what the tool does. It distinguishes the tool from siblings like create_invoice and search_payable_invoices by focusing on payments to existing invoices.

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 the tool is for existing invoices, but it does not explicitly state when to use it versus alternatives or provide contextual prerequisites. It offers no exclusions or sibling references.

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 burden of disclosing behavioral traits. It merely restates the function name ('Approve a deliverable/task') without describing side effects, reversibility, response format, or required permissions. This is essentially a tautology and provides no additional behavioral insight.

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 very short and front-loaded, but it lacks structure and completeness. It is a single phrase that is concise but under-specifies the tool's behavior, making it less useful than a more detailed but still concise description.

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 no output schema and no annotations, the description fails to explain return values, errors, workflow implications, or any post-approval effects. It is not complete enough for an agent to understand the full context of using this 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 the baseline is 3. The description does not add any meaning beyond the schema's parameter descriptions; it only mentions 'in a project' which aligns with clientName/projectName but does not clarify their role or relationship to deliverableId.

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 'Approve' and the resource 'deliverable/task' within a project context. It differentiates from sibling tools like create_task or update_project because no other tool is about approving deliverables.

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?

No guidance is provided about when to use this tool versus alternatives, prerequisites, or situations where approval is needed. The description simply states the action without any contextual usage 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 provided, the description carries the full burden. It does disclose a key behavior beyond the tool name: 'The file will be downloaded and attached.' This adds context that the tool fetches the URL content. However, it does not mention permissions, error handling, whether it overwrites, or the response shape, leaving some behavioral gaps.

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 exceptionally concise: two short sentences that communicate the core purpose and download behavior without any fluff. It is front-loaded with the primary action and uses no unnecessary words.

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 has six parameters and no output schema, yet the description provides no context on how to specify the target record (e.g., the relationship between entityId, entityType, clientName, and projectName). This leaves the agent uncertain about which parameters to use together, making the description incomplete for effective 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 all parameters are documented in the input schema. The description adds minimal parameter meaning beyond the schema, only referencing 'URL' which matches the 'url' parameter. Per the baseline, a score of 3 is appropriate when the schema already handles parameter documentation.

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 action: 'Attach a file to a Moxie record by providing a URL.' This specifies the verb (attach), resource (Moxie record), and method (via URL). It is specific and distinguishes the tool from all siblings, none of which deal with file attachment.

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 when a URL is available and a file needs to be attached, but it does not explicitly state when to use this tool versus alternatives, nor does it provide exclusions or prerequisites. It lacks guidance on parameter combinations (e.g., which of entityId, clientName, projectName to provide), leaving usage somewhat ambiguous.

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 of behavioral disclosure. It only states 'Create a new calendar event' without mentioning required permissions, side effects like attendee notifications, or validation behavior, which is insufficient for a mutation tool.

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 sentence, front-loaded with the action and resource, and contains no wasted words. It is appropriately concise and clearly 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?

The tool has 8 parameters, no output schema, and no annotations, yet the description is only one sentence. It fails to explain return values, error behavior, or other contextual details needed to use the tool effectively, making it incomplete for the tool's complexity.

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 100% description coverage for all 8 parameters, so the schema fully documents the parameters. The description adds no additional parameter semantics, which matches the baseline score of 3 for high schema coverage.

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 uses the specific verb 'Create' with a clear resource 'calendar event', and the word 'new' differentiates it from sibling update_calendar_event and delete_calendar_event. This is a clear, specific statement of purpose.

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. It does not mention preconditions, exclusions, or relationships with the other calendar event tools, leaving the agent without contextual usage information.

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 to rely on, the description needed to disclose behavioral traits but only states the basic creation action. It does not mention prerequisites, idempotency, validation rules, or what the response will contain, leaving the agent without critical 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, clear sentence that front-loads the action and resource. It is appropriately concise with no wasted words.

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?

Despite having 19 parameters and no output schema, the description is only a one-liner. It does not inform the agent about expected return values, permissions, or other operational details, making it incomplete for fully informed tool 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?

The input schema provides complete descriptions for all 19 parameters, so the description does not need to repeat parameter details. Since coverage is 100%, the baseline score of 3 is appropriate; no additional parameter meaning is added, but none is required.

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 function: creating a new client in Moxie CRM. The verb 'create' and resource 'client' are specific and easily distinguish it from sibling tools like create_contact or create_project.

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?

No guidance is provided on when to use this tool versus alternatives such as create_contact or create_opportunity. The description lacks any context for choosing this tool, leaving the agent without direction on when it is the appropriate choice.

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 of behavioral disclosure. It only states the action 'create' and the association, but fails to mention prerequisites (e.g., client must exist), side effects, permissions, or response format. This is insufficient for a mutation tool.

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 no wasted words. Every word contributes to the core purpose, making it highly concise and well-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?

For a tool with 11 parameters and no output schema, the description is too sparse. It does not mention that the client must already exist, nor does it explain the overall workflow or what happens on failure. The schema covers parameter details, but the description lacks the broader context needed for confident 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?

Schema description coverage is 100%, so the baseline is 3. The description adds minimal extra meaning by noting the client association, but does not elaborate on how parameters interact or any additional constraints 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 uses a specific verb 'Create' and identifies the resource 'contact', clearly distinguishing it from sibling tools like create_client and search_contacts. It also notes the association with a client, which further clarifies its purpose.

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 stating the contact is associated with a client, which suggests an existing client is required. However, it does not explicitly compare against alternatives or state when not to use the tool, leaving the guidance implicit.

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 full burden for behavioral disclosure. It only states the action without mentioning permissions, reversibility, side effects, or whether an existing client/project must be associated.

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 sentence that front-loads the action and resource. Zero wasted words, ideal 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?

Given 9 parameters and no output schema, the one-sentence description is insufficient to understand expected return values or operational details such as whether the expense is draft/final, currency handling, or confirmation behavior.

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 schema provides 100% description coverage for all 9 parameters, so the description adds no extra meaning beyond the schema. Baseline of 3 applies because the description doesn't need to compensate.

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 uses a specific verb ('Create') and resource ('expense record'), clearly distinguishing it from sibling tools like create_invoice or create_client. It unambiguously states the tool's purpose.

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?

No guidance is provided on when to use this tool vs alternatives, nor any exclusions or prerequisites. The description only states what it does, not the context in which it should be chosen.

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. It discloses the optional side effect of creating a pipeline opportunity, but omits other important behavior: whether it requires an existing form template (formName), any validation rules for pipelineStageName matching, or what the response looks like. The tool mutates data, but safety, permission requirements, and failure behaviors are not addressed.

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 concise sentences with no redundancy. It front-loads the primary action ('Create a new form submission') and immediately communicates the optional behavior. Every word earns its place, making it appropriately sized for the tool's complexity.

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?

Despite having 19 parameters and no output schema, the description is minimal. It does not mention return values, error scenarios, or how the tool integrates with related entities like form templates or lead records. The description leaves significant gaps about expected behavior and outcomes, which is insufficient for a tool with this many inputs and side effects.

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 baseline is 3. The description groups parameters as 'lead information and custom answers' and highlights pipelineStageName as the trigger for opportunity creation, but the schema already explicitly explains pipelineStageName's behavior. The description adds minimal semantic value beyond what the schema provides; it simply aggregates concepts rather than deepening parameter understanding.

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 action: 'Create a new form submission with lead information and custom answers.' This specifies a distinct verb+resource (creating a form submission) and differentiates it from sibling tools like create_opportunity or create_contact, which serve different purposes. The optional pipeline opportunity behavior adds clarity without confusing the primary purpose.

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: when you need to create a form submission with lead data and custom answers, use this tool. It also mentions the conditional use of creating a pipeline opportunity via pipelineStageName. However, it does not explicitly state when not to use this tool or compare it to alternatives such as create_opportunity for standalone pipeline creation. Guidance is implied rather than 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 behavioral disclosure burden. It does disclose a key behavior: the invoice is created as a draft if sendTo is absent. However, it omits other important behaviors such as validation of client/template names, sending side-effects, or the structure of the response. The single disclosed behavior adds some value but is incomplete.

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 concise sentence, front-loaded with the primary action and immediately followed by a conditional behavior. No redundant words or unnecessary detail.

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 has 11 parameters, 2 required, and no output schema. The description is too sparse to provide a complete operational picture. It only mentions the draft behavior, leaving out the overall flow, prerequisites, expected return, and interactions with other entities like templates or existing clients. Given the complexity, this is insufficient.

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%, giving a baseline of 3. The description does not add any parameter meaning beyond the schema and, in fact, introduces 'sendTo' which is not a parameter in the input schema (the schema has 'sendToContacts' and 'sendInvoice'). This inconsistency could confuse an agent and reduces the description's value.

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 'Create a new invoice in Moxie CRM', which is a specific verb + resource. It uniquely identifies the tool's function and is distinct from sibling tools like search_payable_invoices. The draft condition adds useful scoping.

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 gives one implicit usage guideline: if sendTo is not provided, the invoice becomes a draft. However, it does not mention alternative tools, prerequisites like client existence, or when to choose this over other invoice-related tools. It provides minimal contextual 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 provided, so the description carries the full transparency burden. It discloses a notable behavioral trait: 'This endpoint (/action/opportunities/create) may not be officially documented,' alerting the user to potential instability or lack of support. However, it does not mention side effects, permissions, or return values, which are important for a mutation tool. The unofficial-status disclosure adds value but is not comprehensive.

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 only two sentences, both of which are necessary. The first sentence delivers the core purpose, and the second provides a critical caveat and alternative. There is no redundant or filler content, so it is appropriately sized and front-loaded.

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?

Despite having 8 parameters and no output schema, the description provides a clear purpose and an essential alternative recommendation. It could be more complete by mentioning what the endpoint returns or prerequisites like authentication, but the caveat about its unofficial status is crucial for decision-making. Given the schema covers parameter semantics, the description is mostly sufficient for correct 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?

Schema description coverage is 100%, so the baseline is 3. The description does not add any parameter-level meaning beyond what the schema already provides. The note about pipelineStageName refers to the sibling tool, not this one, so it does not clarify parameters here. The schema descriptions themselves are adequate for all 8 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 function: 'Create a new sales opportunity in the pipeline.' The verb 'create' and resource 'sales opportunity' are specific, and the note distinguishing this from the official create_form_submission method differentiates it from a key sibling tool.

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 provides an alternative and a when-not-to-use signal: 'The official way to create opportunities is via form submissions with a pipelineStageName using create_form_submission.' This tells the agent to prefer the sibling tool, which is clear usage guidance. It implies that this endpoint should be used only if the official method is unavailable or inappropriate.

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 is the only source of behavioral information. It discloses neither side effects (e.g., client association, status), permissions, nor any post-create behavior. The description essentially restates the purpose without added 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 a single sentence that is front-loaded and contains no filler. It efficiently communicates the core purpose.

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?

Despite comprehensive schema descriptions, the overall context is incomplete: no usage guidelines, no behavioral disclosure, and no indication of return values or side effects. For a 9-parameter create tool, this is insufficient to fully guide an agent without additional context.

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 schema provides 100% description coverage for all 9 parameters, each with meaningful descriptions. The tool description itself adds no parameter-level detail, so the baseline 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?

The description clearly states the action ('Create') and the resource ('a new project') in the context of 'Moxie CRM'. This distinguishes it from sibling tools like create_client and create_task, which target different resources.

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?

No guidance is provided on when to use this tool versus alternatives such as create_opportunity or update_project. No prerequisites or typical use-case context is mentioned.

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. It simply says 'create' but does not disclose whether the operation is safe, requires permissions, or has side effects beyond creation. It also omits behavior around the 'tasks' array (subtask creation), validation of exact-match fields, or return values, which are critical for a write operation with 11 parameters.

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 sentence of seven words, with zero filler or redundancy. It is front-loaded with the core action and resource. While it is minimal, this dimension rewards brevity and the sentence earns its place by conveying the essential purpose.

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 (11 parameters, nested objects, no output schema, no annotations), the description is too minimal. It does not explain what the tool returns, how subtasks are handled, or any edge cases. The schema covers parameters, but the description fails to provide broader workflow context such as typical usage or integration with other tools.

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%, with each parameter having a description, so baseline is 3. The tool description itself adds no parameter-specific meaning. However, the schema is already rich (e.g., 'must match exactly a status in your kanban' and 'Exact match of a client record in your CRM'), so no additional compensation from the description is needed.

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 'Create a new task/deliverable in a project', which clearly identifies the action (create) and the resource (task/deliverable within a project). It is distinct from sibling tools like create_project or create_client, though it does not explicitly contrast them. The phrasing 'task/deliverable' may cause slight ambiguity.

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?

No guidance is provided on when to use this tool versus alternatives, nor any exclusions or prerequisites. The description is purely imperative and does not mention scenarios where this tool should be chosen over siblings like create_project or create_client. This leaves the agent without clear selection criteria.

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 burden of behavioral disclosure. It only states that a ticket is created, omitting important behavior such as userEmail validation ('ticket will be rejected if the email is not found'), ticket type requirements, or what happens on success/failure. This is a significant transparency gap for a creation tool.

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 no wasted words. While it is minimal, conciseness is a strength here; the lack of detail does not inflate the score but the structure is 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?

For a tool with six parameters, a nested object, and no output schema, the one-sentence description provides very little beyond the schema itself. It does not explain required inputs, rejection behavior, or the tool's relationship to related sibling tools, leaving the description incomplete for effective tool selection and 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 the schema already thoroughly documents all six parameters including required fields and nested formData. The description adds no parameter-level meaning beyond what the schema provides, so the 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?

The description 'Create a new support ticket in your workspace' uses a specific verb and resource, clearly distinguishing this tool from siblings like create_ticket_comment and create_form_submission. The workspace scoping adds context without ambiguity.

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?

No guidance is provided about when to use this tool versus alternatives such as create_ticket_comment or how to handle prerequisites like using a known contact email. The description does not mention exclusions or scenarios where another tool would be more appropriate.

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 only states the action 'Add a comment' but does not disclose mutational effects, authentication requirements, failure modes, or response behavior. This is a significant gap for a write operation.

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 no wasted words. It efficiently conveys the core action, though it could be expanded slightly to cover behavioral aspects without losing 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?

Given the tool's simplicity and complete schema coverage, the description is minimally adequate. However, the absence of an output schema and annotations means the description should ideally explain return values or side effects, which it does not.

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%, so all parameters are already described structurally. The description adds no additional semantic context beyond what the schema provides, which is acceptable but not enhanced.

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 uses a specific verb ('Add') and resource ('comment to an existing ticket'), clearly distinguishing it from sibling tools like create_ticket. It precisely communicates the tool's function without ambiguity.

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 'existing ticket' implies the tool should be used for commenting on already-created tickets, providing implicit usage context. However, there is no explicit guidance on when to prefer this over alternatives or any exclusions, though no direct alternative exists among siblings.

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 must disclose behavioral traits. It notes the optional auto-creation of related entities, which is helpful. However, it does not disclose failure modes (e.g., behavior when required entities don't exist and auto-create flags are false), permission requirements, or reversibility. Disclosure is partial but non-trivial.

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 concise, front-loaded sentences. The first states the primary action, and the second adds an important optional behavior. No redundancy 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 tool with 10 parameters and no output schema or annotations, the description is thin. It omits return value details, error handling, and broader operational context beyond the auto-create feature. Essential information like required parameters and success/failure behavior is left to the schema, which doesn't cover runtime semantics.

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?

All 10 parameters have descriptions in the schema, so the baseline is 3. The description adds a high-level summary of auto-create behavior but no new parameter-level details beyond what the schema already provides.

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 function ('Create a time entry to track work') and highlights a distinguishing capability (optional auto-creation of client/project/deliverable). This is specific and sets it apart from sibling create tools like create_client or create_project.

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 'to track work' implies a usage context, but the description does not specify when to choose this tool over alternatives or mention prerequisites, exclusions, or when not to use it. No alternative tool references are provided, leaving guidance implicit.

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 of behavioral disclosure. It only says "Delete a calendar event", which implies a destructive operation but does not indicate permanence, permissions, side effects, or what happens to related data.

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, precise sentence with no wasted words. It is appropriately concise for a simple delete operation.

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 a mutation with no annotations and no output schema. The description provides minimal context, omitting behavioral details, error handling, or return value expectations. A delete operation warrants more guidance than this.

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 schema description coverage is 100% (eventId has a clear description). The tool description does not add any meaning beyond what the schema already provides, so the 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?

The description "Delete a calendar event" uses a specific verb and resource, making it clear that this tool removes a calendar event. It distinguishes from sibling tools like create_calendar_event and update_calendar_event by the action it performs.

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?

No guidance is provided on when to use this tool or when alternatives might be appropriate. The description only states the action, with no mention of prerequisites, exclusions, or alternative 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?

With no annotations provided, the description carries the transparency burden. The word 'List' indicates a read operation, which is clear. However, the description does not disclose any additional behavioral traits such as pagination, ordering, or response structure. For a simple list tool, this is adequate but not rich.

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, concise sentence that is front-loaded with the verb and object. Every word earns its place, with no superfluous 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?

Given the tool's simplicity (no parameters, no output schema), the description provides sufficient context: it names the action and the exact scope. It could optionally mention the return format, but for a basic list operation, the description is complete enough for an agent to invoke 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 zero parameters, so the baseline is 4. The description adds nothing about parameters because there are none, which is appropriate. The schema coverage is 100% vacuously, so no compensation is needed.

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 ('List'), the resource ('all clients'), and the scope ('in your Moxie workspace'). This directly distinguishes it from sibling tools like search_clients, which implies filtering, and create_client, which is a write 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 for retrieving the full client list with no filtering, but it does not explicitly mention alternatives or exclusions. The presence of sibling search_clients suggests a filtered alternative, but no explicit guidance is given on when to use one over the other.

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. It only states the core action and does not disclose response format, pagination, permissions, or any caveats (e.g., whether archived templates are included).

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, concise sentence that front-loads the purpose without any filler or redundant 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 zero-parameter, read-only list tool, the description is sufficient for an agent to select and invoke it correctly. It clearly indicates the resource and scope. However, the lack of output schema and any returned field details is a minor gap, preventing a 5.

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 tool has zero parameters, and schema description coverage is 100%. Per the rubric, 0 params sets a baseline of 4; the description correctly omits parameter details because there are none to explain.

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 ('List') and the resource ('email templates'), with scope ('in your workspace'). This distinguishes it from sibling tools like list_invoice_templates and other list_* 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?

The description implies usage by naming the resource, but it does not explicitly mention when to use this tool versus alternatives like list_invoice_templates or search_payable_invoices. There is no when-not or alternative guidance, so it stays at implied usage.

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 must carry the full burden. It adds the scope 'in your workspace' but otherwise simply restates the core action already implied by the name. It does not disclose response format, pagination, or any operational constraints, which is a gap given the lack of 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 a single, concise sentence that front-loads the verb and resource. Every word adds value, and there is no redundancy or fluff.

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-parameter list-only tool with no output schema, the description provides adequate context by stating what is listed and the scope. It doesn't mention return format, but that is not essential for such a simple operation. It feels complete for its complexity level.

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 tool has zero parameters, so the schema fully covers parameter semantics. The description adds no parameter information, which is appropriate since there is nothing to explain. Baseline for 0-parameter tools is 4.

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 action ('List') and resource ('available form names'), and scopes it to the workspace. It distinguishes itself from sibling list tools like list_vendor_names and list_pipeline_stages by specifying the resource type.

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 implied: use when you need form names. However, there is no explicit guidance on when to choose this over other list tools, nor any mention of exclusions or prerequisites. The context signals show it's the only form-name listing tool, but the description doesn't highlight that.

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 burden. It explicitly states that all invoice templates are listed and scoped to the workspace, but does not mention pagination, return format, or whether hidden/archived templates are included. This is adequate for a simple list operation but lacks deeper behavioral detail.

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 no extraneous words. It efficiently conveys the essential action and scope.

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 (no parameters, no annotations, no output schema), the description covers the core operation but omits details about the return payload, such as whether template names, IDs, or other fields are included. It is not misleading, but it leaves some gaps for a fully self-contained description.

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 tool has zero parameters, making the input schema fully covered. There is nothing for the description to add about parameters, so baseline 4 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 clearly states the tool lists all invoice templates in the workspace. The verb 'List' is specific and the resource 'invoice templates' is unambiguous, distinguishing it from sibling tools like list_email_templates.

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?

No guidance is provided on when to use this tool versus alternatives such as list_email_templates or search_payable_invoices. It does not mention any exclusions or contextual prerequisites, leaving the agent to infer usage.

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 burden of disclosing behavior. It indicates a read-only list operation, but provides no additional context about pagination, ordering, or whether all stages include archived ones. The simple phrasing is adequate but not informative beyond the obvious.

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 one short, front-loaded sentence with no wasted words. It fully states the tool's purpose 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?

For a parameterless list tool, the description is sufficient to convey the basic action and scope. There is no output schema to explain return values, but the mention of 'pipeline stages' implies the returned data. Slightly more detail on what constitutes a pipeline stage could improve completeness, but it is not critical.

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 schema has zero parameters and 100% coverage, so the description need not explain parameters. Per the rubric, zero params warrants a baseline of 4, and the description offers no contradictory or supplementary parameter info.

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 uses the specific verb 'List' with the resource 'pipeline stages' and provides scope ('for opportunities in your workspace'). It clearly distinguishes from siblings like list_project_task_stages, which target project tasks rather than opportunity pipelines.

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?

No guidance is given on when to use this tool versus alternatives. It lacks any mention of when-not-to-use or explicit comparisons to sibling tools such as list_project_task_stages, leaving the agent to infer context solely from the name.

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 accurately indicates a read-only operation ('List') and 'all available' suggests comprehensive retrieval without filters. There are no hidden side effects mentioned, but for a zero-parameter list tool, the behavior is straightforward and effectively conveyed.

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 no wasted words. It immediately states the action ('List') and the object ('all available project task stages'), making it highly concise and well-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?

For a tool with zero parameters, no annotations, and no output schema, the description provides sufficient context. It clearly indicates the resource type and scope, and there is no additional complexity that would require further explanation. The description fully covers the tool's purpose and behavior.

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 tool has zero parameters, and the schema is empty. According to the guidelines, 0 params warrants a baseline of 4. The description adds no parameter information, but none is needed since there are no parameters to document.

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 function: 'List all available project task stages in your workspace'. It uses a specific verb ('List') and resource ('project task stages'), and the scope ('in your workspace') is clear. It also distinguishes from sibling tools like list_pipeline_stages by specifying 'project task stages'.

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 describing what it does, but it does not explicitly state when to use this tool versus alternatives. While it is clear that this tool lists project task stages, there is no mention of exclusions or alternative tools. For a simple list tool, this is adequate but lacks explicit 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 burden of behavioral disclosure. It clearly states the read-only nature ('List') and the resource scope ('all vendor names'), but lacks details about output format, error conditions, or any limitations beyond the name. This is adequate for a simple list operation but not rich.

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 sentence of seven words, front-loaded with the action and resource. Every word earns its place, and there is no superfluous 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?

Given the tool's simplicity (no params, no output schema, no siblings with overlapping names), the description is sufficiently complete for an agent to understand the tool's purpose and expected result. It lacks explicit mention of return shape, but 'list all vendor names' strongly implies a list of names.

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?

There are zero parameters, and schema coverage is trivially 100%. The description does not need to explain parameters, and per the rubric, the baseline for 0 params is 4. No additional semantics are required.

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 uses a specific verb ('List') and resource ('vendor names'), and adds context ('for expense tracking'). This clearly distinguishes it from sibling list tools like list_clients and list_form_names.

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. It does not mention any exclusions, prerequisites, or cases where another tool would be more appropriate, leaving the agent without context for selection.

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 present, so the description alone must convey behavioral traits. 'List' implies a read-only operation, but the description does not disclose output format, pagination, or any side effects. It adds minimal information beyond the tool's name.

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. Every word contributes to the intended meaning.

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 zero-parameter, simple list-all nature of the tool, the description covers its core purpose. It lacks return-shape details, but for a trivial enumeration tool this is a minor gap.

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 zero parameters, the baseline is 4. The description is consistent with the schema and implies that no inputs are needed, which is sufficient for this tool.

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 verb 'List' plus the resource 'users' and scope 'your Moxie workspace' clearly state the tool's function. It is distinct from sibling tools that target other resources (e.g., clients, projects, stages).

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 use when you need all workspace users, and no sibling tool covers users, so alternatives are implicitly excluded. However, there is no explicit 'when to use' or 'when not to use' 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 provided, so the description carries the burden. The verb 'search' implies a read-only operation, and the criteria are stated, but it does not disclose return format, pagination, or case sensitivity. For a simple search tool, this is adequate but not rich.

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 that contains no filler. Every word contributes to understanding the tool's purpose and search scope.

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 search tool with no output schema, the description is largely complete: it states the target resource and the type of query. A minor gap is not explicitly stating what is returned (e.g., a list of matching clients), but the simplicity of the tool makes this acceptable.

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 tool description's 'by name or contact information' merely echoes the parameter description in the schema. The description adds no extra meaning beyond the schema, so the baseline score of 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 uses a specific verb ('Search'), names the resource ('clients'), and specifies the search criteria ('by name or contact information'). This clearly distinguishes it from siblings like list_clients (which returns all clients) and search_contacts (which searches a different resource).

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 when to use the tool—when you need to find clients by name or contact info—but does not explicitly mention alternatives or exclusions. It does not reference sibling tools like list_clients or search_contacts, so the guidance is only implicit.

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. It only says 'Search for contacts' without mentioning return format, pagination, permissions, or any other behavioral trait. This adds no transparency beyond what the tool name implies.

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 concise sentence with no redundant information. It is front-loaded and appropriately sized for the simplicity of the 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?

The description is incomplete for a tool with no output schema and no annotations. It does not explain what is returned, how many results to expect, or any usage context. The agent is left without essential information about the tool's behavior and output.

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 already provides a full description of the 'query' parameter (searching by name, email, or phone), giving 100% schema coverage. The tool description adds no additional parameter semantics, so the 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?

The description uses the specific verb 'search' with the resource 'contacts', and scopes it to 'your Moxie workspace'. This clearly distinguishes it from sibling tools like search_clients or search_projects, which target different resources.

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?

No usage guidance is provided. The description does not indicate when to use this tool versus alternatives such as search_clients or list_clients, nor does it mention any exclusions or prerequisites. The agent is left without context for tool selection.

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 must disclose behavioral traits. 'Search' implies a read-only operation, but the description does not explicitly state whether it is non-destructive, what the return format is, or whether any side effects occur. The minimal description adds little beyond the tool name.

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 concise sentence that front-loads the action and resource. Every word earns its place, with no redundancy or irrelevant detail.

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 tool with one optional parameter and no output schema, the description is minimally viable but not rich. It does not indicate what the response looks like (e.g., a list of invoices), nor the behavior when query is omitted. Given the low complexity, this is adequate but could be more informative.

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 provides 100% coverage for the single 'query' parameter with a description ('Search query to filter invoices'), so the schema carries the semantic burden. The description itself adds no parameter information, which is acceptable given full schema coverage.

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 identifies the verb 'search' and the resource 'payable invoices' in the Moxie workspace, distinguishing it from sibling tools like search_clients and search_projects. However, it does not explain what distinguishes 'payable invoices' from other invoice-related concepts, leaving slight ambiguity.

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 other search tools, nor any mention of exclusions or alternative approaches. The description simply states the action without contextualizing it within the broader toolset.

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 burden. It discloses that the search is scoped to the workspace and that the query is an optional client-name filter, but does not specify default behavior (e.g., empty query returns all projects), return format, or any side effects (though search implies read-only). The disclosed filter behavior adds some transparency but significant behavioral details remain implicit.

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?

Single sentence, 10 words, front-loads the core action and scopes the search. No wasted words or redundant restatement of the tool name.

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 search tool with one optional parameter and no output schema, the description provides adequate context about what it searches and its filter capability. However, it could optionally state that no query returns all projects or hint at the response format, but these omissions are not critical 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?

The input schema has 100% coverage with the description of 'query' explicitly stating it filters by client name. The tool description adds the 'optionally' nuance and workspace context, but does not introduce new parameter semantics beyond the schema. Baseline 3 is appropriate given high schema coverage.

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 uses a specific verb ('Search') and resource ('projects'), and clarifies the workspace scope ('Moxie workspace') and the optional filter by client name. This distinguishes it from sibling search tools like search_clients and search_contacts, which target different resources.

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 the tool's role (find projects, optionally narrowed by client name) but does not explicitly mention when to prefer it over alternatives or when not to use it. It provides clear context for a typical search use case, but lacks explicit exclusions or comparisons to sibling tools like list_clients.

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 burden of behavioral disclosure. It only states 'Update an existing calendar event', which indicates mutation but provides no details about partial vs. full updates, error behavior if the event does not exist, permission requirements, or response format. This is a significant gap for a mutation tool.

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 focused sentence, making it concise and easy to parse. However, it is also under-specified, lacking important behavioral and usage details. Still, for what it does say, there is no waste.

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 9 parameters, no output schema, and no annotations, the description is extremely incomplete. It does not explain what the return value is, whether update is partial or full replacement, how errors are handled, or any side effects. For a complex mutation tool, this is wholly inadequate.

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% with each parameter having a clear description (e.g., 'New title for the event'). The tool description adds no extra semantic meaning beyond the schema, so the baseline 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?

The description 'Update an existing calendar event' clearly specifies the verb (update), resource (calendar event), and scope (existing), which distinguishes it from sibling tools like create_calendar_event and delete_calendar_event. It is specific and unambiguous.

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 offers no explicit guidance on when to use this tool versus alternatives. It only implies use for existing events via the word 'existing', but does not state prerequisites, exclusions, or how it differs from create/delete. No context or alternative tools are mentioned.

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 burden of disclosing behavioral traits. It only says 'update', implying mutation, but does not explain partial-update behavior, required existing record, or return values.

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 concise sentence that communicates the core purpose with no unnecessary words.

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 has 12 parameters, no annotations, and no output schema, yet the description provides only the basic action. It fails to explain how to identify the project (e.g., projectId vs projectName) or what the update semantics are, making it inadequate 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 the schema already explains all 12 parameters. The description adds no parameter-specific information, making the baseline 3 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?

The description clearly states the tool updates an existing project, using a specific verb and resource. It does not explicitly differentiate from related tools like create_project or search_projects, but the action is unambiguous.

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?

No guidance is provided on when to use this tool versus alternatives. The description does not mention prerequisites, such as requiring an existing project ID, or contrast with create_project or search_projects.

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