Ultimate Business Machines (no account)

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

Annotations already declare read-only, idempotent, and closed-world behavior. The description adds useful content-level transparency by stating that the tool returns an overview, the money-back promise, contact paths, and links to main pages. It does not discuss response format or limits, but for a static informational tool this is solid extra 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?

Two sentences, both front-loaded and purposeful. The first enumerates the informational scope; the second gives an invocation cue. No filler or redundancy.

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

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

With no parameters and no output schema, the description carries the context burden and does so completely: it tells the agent what the tool contains and when to use it. Nothing material is missing for an 'about' 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?

The tool has zero parameters, so there is no parameter semantics to explain; the baseline for a parameterless tool is 4. The description correctly does not invent parameters or misdescribe input.

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 this as an informational 'about' tool covering what UBM is, who it's for, how it works, the money-back promise, and contact details. It lacks a strong action verb but the resource and scope are unambiguous, and it is distinguishable from siblings that are transactional or listing-oriented.

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?

It gives an explicit trigger: 'Start here when someone asks what UBM is or does.' That is clear guidance for an agent deciding when to invoke it. It does not name alternatives or state when not to use it, which keeps it from a 5.

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=true, idempotentHint=true, and openWorldHint=false, so the safety profile is covered. The description adds useful domain context by enumerating the connection paths (server address, OAuth, personal token), which a developer-facing tool would need. It still omits what the call produces, which is the main behavioral unknown for a zero-parameter 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?

A single compact sentence with no filler, and the parenthetical examples are genuinely informative rather than padding. The structure is slightly weak because it opens with a nominal phrase ('How a business...') instead of a leading action statement.

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?

There is no output schema, so the description carries full responsibility for telling the agent what it gets back — and it does not, leaving ambiguity about whether the result is guidance text, endpoints, or credentials. It does cover the breadth of topics the tool addresses, so an agent knows roughly what it is for.

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 takes zero parameters, so there is no parameter semantics to document; the baseline of 4 applies. Nothing in the description misrepresents the (empty) input contract.

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 frames the topic (how a business connects its AI agent to a UBM account) and enumerates the three connection methods, which distinguishes it from generic siblings like ubm_about. However, it is phrased as a documentation heading rather than a tool action — there is no verb stating what invoking it actually does or returns (instructions? a URL? a token?).

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 on when to call this versus ubm_about or ubm_get_guide_questions, despite those siblings overlapping as 'informational' tools. There are no prerequisites or exclusions stated; the agent must infer usage from the name alone.

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

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

The annotations already declare read-only, idempotent, closed-world behavior, so the description's main burden is return semantics. It usefully describes question kinds: 'one' takes one answer id, 'many' takes a list, and 'text' takes free text, which helps the agent interpret and use the response. It does not elaborate on freshness or ordering of questions, but for a read-only no-parameter tool this is reasonably transparent.

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 compact and front-loaded: it first identifies what is returned, then gives the workflow step, then explains answer-type handling. Every sentence contributes useful information for invoking or interpreting 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?

For a no-parameter, read-only retrieval tool with no output schema, the description provides enough context: what the questions are, how required versus optional questions work, how answers map to ids, and where the answers go next. There is no meaningful invocation detail 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?

This tool takes zero parameters, so the baseline is 4 under the scoring rules. The description correctly focuses on response/usage semantics rather than inventing parameter details.

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

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

The description states a specific resource and payload: the Solutions guide's questions about a business, including the answer ids each question accepts. It also situates the tool in the broader workflow by naming ubm_recommend_plan, so an agent can distinguish its retrieval role from downstream recommendation.

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?

It gives explicit usage instructions: this is Step 2, ask the person the questions, only the required ones are mandatory, and then pass the answers to ubm_recommend_plan. That is a clear when-to-use path plus the next action, leaving little inference.

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 readOnly, idempotent, and closed-world behavior. The description adds useful return-content context—dependency/co-requisite information like Accounting needing Invoicing & Payments or the Customer Portal—which the annotations do not convey.

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, front-loaded with the tool's output, followed by the input instruction. The parenthetical example earns its place by illustrating co-requisite semantics.

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 read-only single-enum lookup with no output schema, the description adequately covers what information comes back and how to source the id. Only minor gaps remain, such as invalid-id 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?

Schema coverage is 100% and the enum documents valid ids, so the baseline is 3. The description adds meaning by stating where the id comes from (ubm_list_services), which is not in 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?

States a specific verb and resource ('One UBM service in detail') and enumerates the returned content: what it does, package membership, and co-requisites. This clearly distinguishes it from ubm_list_services, which is named as the id source.

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 directs the agent to pass an id obtained from ubm_list_services, implying the list-then-detail workflow. It does not state exclusions or error behavior for an unknown service, but the intended flow is clear.

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, idempotentHint, and openWorldHint=false, covering the safety profile. The description adds value by stating that each business type includes examples and how UBM helps that kind of business, which tells the agent what content to expect 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?

The description is two sentences with zero waste, front-loading the resource and its contents before specifying the workflow step. Every sentence adds necessary information without redundancy.

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

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

Given the tool's simplicity (no parameters, no output schema) and the annotations covering safety, the description provides enough context: it lists the categories, mentions examples, and identifies the next step. An agent has all it needs to call 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 tool has zero parameters, so the baseline is 4. There is no parameter information needed, and the description appropriately does not discuss parameters since none exist.

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 specifies the exact resource (kinds of business) and enumerates the categories, making it clear what the tool returns. It also differentiates from sibling tools by naming the next step (ubm_get_guide_questions), so an agent can distinguish its role 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?

The description explicitly frames the tool as 'Step 1 of tailoring a plan' and directs the agent to pick a type then call ubm_get_guide_questions. This provides clear context for when to use it, though it lacks explicit when-not-to-use conditions or alternatives (none exist for this resource).

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=true, idempotentHint=true, and openWorldHint=false, so the safety profile is known. The description adds useful behavioral context by stating the exact return content (audience, purpose, included services) and explicitly excluding pricing, which prevents misuse as a price lookup.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is two sentences, front-loaded with the resource and package categories, followed by the key scope limitation and alternative for pricing. Every clause adds information without repetition.

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 listing tool with no output schema, the description sufficiently defines the package categories, the information each package entry contains, and the boundary that pricing is handled elsewhere. An agent has enough to know what to expect and when not to use 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?

There are zero input parameters, so parameter semantics are not a burden on the description. The baseline for a no-parameter tool 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 states a specific resource (UBM's ready-made packages), enumerates the package categories, and specifies the exact information returned: who each is for, what it does, and which services it holds. It also distinguishes itself from pricing by explicitly noting that prices are not included and naming ubm_quote_plan for that 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?

It gives clear usage context by saying there are no prices here and routing price-related needs to ubm_quote_plan. It does not explicitly contrast with other listing siblings like ubm_list_services or recommendation tools such as ubm_recommend_plan, but the package-vs-pricing distinction is 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?

Annotations already declare readOnlyHint=true, idempotentHint=true and openWorldHint=false, so safety is covered and the description only needs to add substance — which it does by describing the shape of each result ('one-line summary and its page') and by actively denying that pricing is present. It stops short of noting result volume or ordering, a minor gap given no output schema exists.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

Two sentences, zero filler. The inventory statement comes first and the pricing exclusion — the most likely source of a wrong call — is front-loaded as the closing clause.

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 enumeration with no output schema, the description tells the agent what it returns, at what granularity, and what it explicitly does not return. Nothing needed to invoke it correctly is absent.

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 takes zero parameters, so there is no parameter semantics to explain — the baseline applies. The description usefully clarifies that no filtering or pricing inputs exist, which is the only semantic an agent could otherwise guess at.

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 resource and scope: 'Every service UBM offers', with concrete examples (CRM, Lead Management, Scheduling, Invoicing & Payments, Website Machine) and the per-item payload ('one-line summary and its page'). It is clearly distinct from the pricing/plan tools, but it never names ubm_get_service, the sibling an agent would use to go deeper on a single listed service.

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 carves out a negative case with a redirect: 'No prices: use the Solutions guide tools for what a plan costs.' That is real routing guidance. What's missing is the positive follow-up path — nothing says to call ubm_get_service for detail on an item returned here, nor when to prefer ubm_list_packages.

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 mark it read-only, idempotent, and closed-world. The description adds useful behavioral context: pricing follows the Solutions guide/billing, may be the best of individual services, package plus extras, or Everything, and enterprise is handled by in-person quote. It does not cover rate limits or auth, but those are less critical for a read-only pricing 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?

Two sentences, front-loaded with the price outcome, and each clause carries useful meaning about pricing or team-size mapping. The parenthetical pricing details make it dense but not wasteful; it could be slightly tighter.

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 two-parameter read-only quote tool with no output schema, the description establishes the return (monthly/yearly price), explains team_size, and notes the enterprise exception. It leaves some service-array detail to the schema enum, but overall it is complete enough 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 0%, so the description must carry parameter meaning. It fully explains team_size (solo/small/mid/large/enterprise with ranges and enterprise caveat) and gives the pricing logic for the services set, but it does not describe the 18 service enum values or clarify the array's selection semantics beyond 'set of UBM services'.

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 identifies the resource as the monthly and yearly price of a set of UBM services for a given team size and ties it to the Solutions guide and billing. It is not a verb-first statement and does not explicitly contrast with siblings such as ubm_recommend_plan or ubm_request_plan, so it misses the top band.

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?

It implies this is the pricing/quote tool and explains the team-size categories, including the enterprise 'quoted in person' caveat. However, it does not state when to prefer this over ubm_recommend_plan, ubm_request_plan, or ubm_list_packages, so selection guidance remains implied.

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 cover the safety profile (readOnly, idempotent, closed-world), and the description adds genuinely new context: the response is grouped into two buckets, each item carries quoted-answer justifications and benefit text, and how to encode multi-select answers. It omits failure behavior (e.g., partial or missing answers), which keeps it from a 5.

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 dense sentences that are front-loaded with the return shape, then the input contract, then the next step — no filler. The first sentence is long and could be split, but every clause carries 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?

With no output schema, the description correctly takes on the burden of describing return values (grouping, reasons, benefits), which is the main thing an agent needs. The nested answers object is explained. Only edge-case behavior for incomplete answers 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 coverage is only 50% — business_type has an enum but no prose description — and the description compensates by clarifying that it is a business type id and by defining the two accepted shapes for answers (single id vs. list for 'many' questions). It also points to ubm_get_guide_questions as the source of question ids, adding meaning the schema lacks.

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 resource (recommended services from the Solutions guide's advisor) and spells out the returned structure: grouped as where to start vs. add later, with reasons quoting the answers and how each helps. It also distinguishes itself from ubm_quote_plan, which handles the pricing step instead.

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 concrete invocation guidance — pass the business type id plus answers as question id -> answer id, or a list of ids for 'many' questions — and names the follow-up step explicitly ('Then price it with ubm_quote_plan'). It does not state when not to use it or what to do if answers are incomplete, so it stops short of a 5.

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?

Adds real context beyond the annotations: UBM does not auto-email the person, a human team replies, and there is a rate limit of a few per day per network. These are non-obvious traits for a mutation/openWorld tool. It still doesn't say what a successful call returns or how duplicate submissions are handled.

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 action and purpose are front-loaded before the constraints, and every clause carries information (consent, reply model, rate limit). Slightly dense but no filler sentences.

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, nested-object mutation with no output schema and very thin schema descriptions, the definition covers consent, side effects, and throttling but leaves most field semantics and the expected result unexplained. Adequate to decide whether to call, not fully adequate to call 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?

Schema description coverage is only 11% across 9 parameters, so the description carries the burden — yet it only clarifies name plus 'an email or phone number' (useful, since neither is required in the schema). business_type, business, role, message, and preferred are left entirely to enums and maxLengths, with no explanation of where business_type values come from or how 'plan' maps to answers.

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 concrete verb and resource: send a business's plan and contact details to UBM's team, plus the downstream intent (they get in touch). The reference to the Solutions guide's own 'send me this plan' form distinguishes it cleanly from quote/recommend/see-demo/start-signup siblings.

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 gating condition: 'Only call this when the person has asked to be contacted, with the details they gave you.' That is a clear when-to-use with a consent prerequisite, though it never names the alternative sibling (e.g. ubm_see_demo, ubm_start_signup) an agent should pick instead when the person is not asking to be contacted.

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 readOnly, idempotent and closed-world, so the safety profile is covered. The description adds genuinely non-obvious behavior beyond that: the demo is shared across users, it resets, and messages created in it never reach real customers — exactly the caveats an agent needs before encouraging a user to experiment.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

Two sentences, front-loaded with the payload and followed by the reset/isolation caveat. The parenthetical credential list is slightly clunky but each clause carries real information, so nothing is wasted.

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

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

With no parameters and no output schema, the description carries the full burden and discharges it: it says what comes back, what the credentials are for, and the shared/reset/no-real-messages constraints. An agent could call this and explain the result to a user without further information.

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?

Zero parameters, so the baseline is 4. The description still adds value by enumerating the credential components returned (company ID, email, password), which tells the agent what it will be able to hand the user.

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 precisely what the tool returns: each industry's demo website plus the shared demo login (company ID, email, password). That is a concrete resource with a clear intent ('let the person click around UBM themselves'). It never names a sibling, but no sibling plausibly overlaps with demo-credential retrieval, so ambiguity is low rather than zero.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

Usage is only implied by the clause 'so the person can click around UBM themselves' — an agent can infer this is for users who want to trial the product before signing up. There is no explicit when-to-use, when-not-to-use, or pointer to ubm_start_signup / ubm_quote_plan as the follow-on once the demo is done.

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, idempotentHint and openWorldHint=false, and the description is consistent with them. It adds real context beyond the annotations: the agent never creates the account, the human completes company name/email/password and terms acceptance, and pricing plus the money-back guarantee are surfaced on the page. It does not say whether the link expires or how long it is valid.

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, front-loaded with the deliverable, then the human-in-the-loop constraint. No redundant restatement of the title and 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 no output schema, the description correctly signals that the return value is a link, and it explains the division of labor between agent and human. Minor gap: it does not specify the return shape precisely (URL string vs object) or link lifetime, but everything needed to decide to call it is present.

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 only 25%, with just from_guide documented, so the description has to carry weight. It does clarify the interaction between the first three parameters — services or a package, plus team size pre-filled — but leaves the package-vs-services relationship (mutually exclusive or combinable?) and team_size semantics unstated.

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

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

The description states a concrete output (a pre-filled sign-up link) with the dimensions that get filled in: services or package plus team size. The verb is implicit ('start signing up') rather than an explicit 'returns a link that…', but the resource and result are unmistakable and clearly distinct from siblings like ubm_quote_plan or ubm_request_plan.

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 — you call this when a person is ready to create their own account — and the from_guide parameter hints at the ubm_recommend_plan handoff. However, it never explicitly says when to prefer this over ubm_request_plan, ubm_quote_plan, or ubm_connect_agent, leaving the boundary to inference.

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