AI Logo Maker - ManyMotions

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

Annotations declare a non-read-only, non-idempotent, open-world write, and the description adds materially more: it consumes the user's credits, requires a signed-in ManyMotions account (with the client prompting sign-in when missing), and returns a job id and status. Not calling it on the agent's own initiative is a behavioral guardrail not expressible 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?

Front-loads the action and default, then the consent/credit constraint, then the return value, then the negative-scope list. Dense but every sentence carries operative information (credit cost, auth precondition, exclusion set).

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 9-parameter, credit-consuming generation tool, the description covers the decision-critical context: consent requirement, account precondition, scope exclusions, and result shape. An output schema exists, yet the description optionally notes the return (job id and status), so nothing blocking a correct call is missing.

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% across 9 parameters, so the description must compensate. It does partially: it implies the count parameter's default (4 concepts in one job) and describes the prompt input (brand name, industry, style, colors), but ratio, duration, model_id, model_name, resolution and advanced_params get no explanation anywhere.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

States a specific verb+resource+scope: starting generation of a prepared logo project, with a stated default (4 raster logo concepts per job). It distinguishes itself from siblings get_logo_job, prepare_logo_project, render_logo_widget and update_logo_project by being the generation trigger on an already-prepared 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?

Gives explicit when-to-use ('only after the user has explicitly asked to generate', new text-to-image designs from a brief) and when-not (uploaded/reference images, editing an existing logo, SVG/vector export, background removal, video, trademark checks), plus the precondition that the project be 'prepared'. No routing inference is left to the agent.

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

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

The description adds real behavioral context beyond the annotations by disclosing the refresh side effects (saving completed logos, refunding credits for a failed job) and the scope limit (no new generation). However, those side effects are state-changing, which directly conflicts with the declared readOnlyHint=true / destructiveHint=false / idempotentHint=true profile; an agent trusting the annotations would assume this is a pure read. The mismatch undercuts the behavioral disclosure.

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 tight sentences: the purpose leads, the operational consequence and the negative scope limit follow. Every clause carries information, and nothing is padding.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

An output schema exists, so return values need not be described, and the annotations cover the safety profile (albeit inaccurately). The description covers purpose, effect, and scope limit, but omits when to call it (e.g., after a generation completes) and any detail about the job_id. Nearly complete for a one-parameter 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 0% for the single required job_id, so the description must compensate. It only implies that the id names an existing generation job in the user's account; it gives no format, source, or validity guidance for the identifier. Baseline 3 for a one-parameter tool where the meaning is inferable but undocumented.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

States a specific verb and resource ('Refresh an existing Logo Maker generation job in the user's ManyMotions account') and explicitly rules out the generation use case ('it never starts a new generation'), which cleanly separates it from sibling generate_logo. It does not distinguish itself from update_logo_project or prepare_logo_project, so the sibling differentiation is only partial.

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?

Use is implied rather than stated: the description explains what refreshing accomplishes (settle a job by saving logos or refunding credits) but never says when an agent should call this versus generate_logo or update_logo_project, nor the polling/retry conditions under which a refresh is 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?

Annotations only signal a non-read-only, non-idempotent, non-destructive write; the description goes well beyond that by stating the review widget renders immediately, nothing is generated, no credits are charged, and no sign-in is required. Those are precisely the side-effect and auth facts the schema cannot express.

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?

Front-loads the purpose, then the prompt convention, then side effects, then routing exclusions — each sentence adds distinct information with no filler. The length is justified by the amount of routing and side-effect detail packed in.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

An output schema exists, so return values need not be described, and the description covers the remaining gaps: no-credit/no-generation behavior, immediate widget rendering, no-auth, and precise routing against all relevant siblings. Nothing an agent needs in order to call this correctly is missing.

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 must carry the load and does so well for the required 'prompt' (prescribing the logo-brief content and the exact style suffix). However, count, ratio, duration, resolution, model_id, model_name, and advanced_params get no meaning or guidance at all, leaving most of the surface undocumented.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

States a specific verb+resource ('Prepare a ManyMotions Logo Maker project') and immediately scopes it to text-to-image logo designs from a brand brief, which cleanly separates it from siblings like generate_logo and update_logo_project. An agent can tell what it does and does not do without opening the schema.

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 enumerates both sides: use only for new text-to-image logo designs from a brief, and do not use for uploaded/reference images, editing an existing logo, SVG/vector export, background removal, video, or trademark checks. This is exactly the when/when-not/alternatives routing the dimension asks for.

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

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

Annotations already establish the safety profile (readOnlyHint=false, idempotentHint=true, destructiveHint=false, openWorldHint=true), but the description adds real behavioral content: refresh either saves completed logos or refunds credits on a failed job, and it never starts a new generation. It does not surface any auth, rate-limit, or side-effect-on-recall detail, but the save/refund disclosure is meaningful context beyond the 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?

Three tightly packed sentences, front-loaded with what the tool does, then its refresh semantics, then the prerequisite. Every sentence conveys a distinct constraint with no 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?

With an output schema present the return value need not be explained, and annotations plus the description cover safety, idempotency, and the widget/refresh behavior. Prerequisites and the boundary against generate_logo are stated, so nothing essential for correct invocation is missing.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 0% and there is one parameter (project_id), so the description must carry the load. It adds some meaning by requiring 'a prepared logo project', implying the id must reference a project already set up via prepare_logo_project, but it gives no format or validation detail. Marginal compensation for a zero-coverage param.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

States a specific verb+resource ('Render the inline Logo Maker widget') scoped to 'a prepared logo project', and distinguishes itself from the sibling generate_logo by declaring it 'never starts a new generation'. An agent can tell this apart from generate_logo/get_logo_job without opening any schema.

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?

Gives an explicit prerequisite ('Always call prepare_logo_project first') and a clear exclusion boundary ('never starts a new generation'), which implies generate_logo is the alternative for new jobs. It stops short of naming generate_logo directly, so it is clear context rather than a fully enumerated alternative map.

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

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

Annotations already declare readOnlyHint=false, idempotentHint=true, destructiveHint=false and openWorldHint=false, so the safety profile is covered structurally. The description adds the widget-UI audience constraint but says nothing about partial-vs-full update semantics (what happens to fields not passed) or whether the project must already be prepared, which matters 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?

Front-loaded with the action and the affected fields, followed by scope and exclusions; no filler sentences. The exclusion list is long and runs as a comma chain, but each item carries routing value.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

An output schema exists, so return values need no explanation, and annotations cover safety. Still, with 9 parameters at 0% schema coverage and a nested advanced_params object, the description leaves several parameters opaque, which is a real gap for an agent invoking it.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 0%, so the description carries the burden, and it does name several editable fields (prompt, model, ratio, resolution, count, advanced params). However it gives no value semantics for ratio, resolution, duration, or the nested advanced_params object, and leaves model_id/model_name and the required project_id unaddressed.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

States a specific verb and resource ('Update the prepared logo project') and enumerates the editable fields (prompt, model, ratio, resolution, number of concepts, advanced params). It positions itself in the workflow ('before opening ManyMotions or generating') but never names the sibling tools, so differentiation from prepare_logo_project/generate_logo is inferred rather than explicit.

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?

Explicit when-to-use ('only for new text-to-image logo designs from a brief') plus an unusually thorough when-not list covering uploaded/reference images, editing an existing logo, SVG/vector export, background removal, video, and trademark checks. It also scopes the audience ('Intended for the widget UI'), leaving little to inference.

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