Start Companies LLC Formation

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

Annotations are minimal (readOnlyHint false, etc.), so description carries the burden. It discloses that the tool registers the request, sends an email with reference, returns a payment link, and that Start Companies replies within 24 hours. It does not discuss idempotency or error states, but covers core behavior well.

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?

Four sentences with no fluff. The first sentence encapsulates the main purpose and outputs. Subsequent sentences add precise usage constraints and post-call expectations. Every sentence earns its place.

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 (7 required) and no output schema, the description covers the key actions, preconditions, and a downstream expectation. It lacks details on return value format or error cases, but for a form submission tool it is substantially complete.

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 individual parameter descriptions, so baseline is 3. The description adds meta-context that 'everything was captured here' (reassuring completeness) and links 'paquete' to package confirmation, but does not explain individual parameters beyond schema. Adequate.

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 registers an LLC formation request, sends a confirmation email, and returns a payment link. It distinguishes from sibling tools (all read/info tools except start_itin_application) as the creation action, and specifies the prerequisite of explicit package confirmation, differentiating from recommend_llc_package.

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

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

Explicitly states 'Call this ONLY after the user has explicitly confirmed the package.' Also advises handing off to a person if not ready to pay, providing clear when-to-use and when-not-to-use guidance. Though it doesn't name sibling alternatives, the precondition is unambiguous.

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 indicate readOnlyHint=true, idempotentHint=true, and destructiveHint=false, so the agent knows this is a safe, read-only operation. The description adds behavioral context by noting that passing a reference number matches payment to a prior request, which is beyond what annotations provide.

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 three sentences, front-loaded with the core purpose, and every sentence adds distinct value: purpose, usage guidance, and reference parameter context. No extraneous 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 has no output schema or nested objects, and schema covers all parameters, the description is mostly complete. Minor gap: it doesn't mention that the user must have an existing lead or request to get a link (implied for the 'referencia' case, but not explicit for initial payment when no reference is passed).

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 already covers all parameters with descriptions (100% coverage). The description adds marginal value by explaining that 'referencia' should be a reference from 'create_llc_lead' and describing the enums implicitly, but the schema's enum and property descriptions are 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 clearly identifies the tool as returning a Stripe checkout link for three specific packages, distinguishing it from siblings like 'get_order_status' and 'get_renewal_info'. The verb 'Returns' and resource 'checkout link' are 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 explicitly states when to use this tool ('user already knows which package they want and wants to pay now' or 'submitted the request earlier and wants to pay afterwards'), and implies when not to use it (e.g., when user needs a recommendation, which would go to 'recommend_llc_package'). It also provides guidance on passing a reference number if available.

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 and idempotentHint=true, so the safety profile is covered. The description adds valuable context: the return contents (three packages, categories) and the prerequisite role. No contradictions.

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 with no wasted words. The first sentence front-loads the return contents, and the second provides a clear usage instruction. Every sentence is necessary.

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 covers all relevant aspects: what is returned (packages, pricing, inclusions, add-ons, renewals, advisory, support) and when to use it. No output schema exists, but the description compensates fully. The tool is simple (read-only, zero params), so completeness is high.

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 no parameters; schema coverage is 100% trivially. The description does not need to explain parameters, and the baseline score of 4 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 tool returns the three US LLC formation packages with price, turnaround, inclusions, add-ons, renewals, tax advisory, and support. It specifies the source (Start Companies) and distinguishes from siblings like recommend_llc_package by positioning itself as the prerequisite call.

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 instructs 'Always call this before discussing prices, renewals, advisory or what is included,' providing clear usage guidance. It does not list alternative tools or when-not-to-use, but the instruction is direct and actionable.

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

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

Annotations already indicate read-only, idempotent, and non-destructive behavior. The description adds valuable context: 'Never returns personal data' and explains the email's role as a second factor. This goes beyond the structured annotations without contradicting them.

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

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

The description is four sentences, each serving a distinct purpose: purpose, input requirements, agent instruction, and output constraint. Front-loaded with the core action. 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?

The description covers what the tool does, required inputs, and a behavioral constraint (no personal data). However, with no output schema, it does not describe the format of the returned status (e.g., possible values, structure). For a simple status check this is adequate but not fully complete.

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 descriptions for both parameters. The description adds extra meaning: the reference number format (SC-MMDD-XXXX) and clarifies that the email is an authentication factor, not a search key. This enriches the schema's baseline.

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 'looks up a previously submitted LLC formation request and returns its status'. This specific verb+resource combination distinguishes it from sibling tools like create_llc_lead (for creation) and get_llc_options (for options). No 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 description explicitly tells the agent to ask the user for both the reference number and email before calling, and explains that the email is a second factor, not a search key. It implies usage after a request is submitted. While it does not explicitly mention alternatives or when not to use, the context is clear and actionable.

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 destructiveHint as false, so no contradiction. The description adds behavioral context beyond annotations by explaining that this tool does not handle purchases and triggers a human handoff, which is critical operational information not captured in annotations.

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

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

The description is three sentences, each serving a distinct purpose: return value, scope details, and usage directive. It is front-loaded with the core purpose. Minor verbosity in the filing forms list but justified for completeness.

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 a read-only schema and no output schema, the description covers what is returned (cost, coverage, filing types) and the action boundary (no sale). Some detail on when exactly to hand off could be richer, but overall it gives sufficient context 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 baseline is 3. The description adds value by explaining that 'Delaware costs more' for the 'estado' parameter and defines multimember context, but this contextual pricing is only lightly implied and not fully elaborated.

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 returns renewal costs and covered services, specifies the two main IRS forms by LLC type, and identifies exactly what triggers its use. It distinctly separates itself from sibling tools that handle LLC creation or ordering.

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 says when to use this tool ('whenever the user asks about renewing, keeping the LLC active, IRS filings, penalties, the annual report...') and also clarifies when not to use it for completing a sale ('Renewals are NOT sold through this server'), directing the agent to hand off via WhatsApp, email, or client portal.

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 and idempotentHint=true. The description adds that the tool returns a package 'and explains why', revealing an explanation behavior not inferred from annotations. The read-only statement reinforces the annotation without contradiction. No additional side effects or constraints are disclosed, but the existing annotation coverage is high.

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 inputs and output. The second sentence adds a crucial behavioral caveat (read-only) without redundancy. Every word earns its place; no filler or unnecessary details.

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 5 parameters (all optional) and no output schema, the description gives only a vague output description ('returns the appropriate package and explains why'). Missing details: output format, data types, whether partial inputs are valid, error handling, and how this complements sibling tools like get_llc_options. For a tool with this complexity, the description is incomplete.

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 schema. The description groups four boolean service parameters as 'which services the user needs', which adds no new meaning beyond the schema. The parameter names are in Spanish, but the schema provides English-like descriptions. The description does not clarify parameter relationships, defaults, or optionality—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 verb 'returns' and the resource 'appropriate package', naming the inputs (state, membership count, services) and output (package with explanation). It is easily distinguishable from sibling tools like create_llc_lead (creation) or get_llc_options (listing options), fulfilling a specific recommendation role.

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

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

The description explains when to use the tool: when you have state, multi-member flag, and service needs. It adds a clear read-only note. However, it does not explicitly mention when not to use it or suggest alternatives (e.g., get_llc_options for a list of all packages), missing an opportunity to guide agent decision-making.

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 explains the tool provides informational content and returns a link, which aligns with the readOnlyHint and idempotentHint annotations. It adds behavioral context beyond annotations by describing what the tool outputs (explanation and link) and the scope of eligibility. No contradictions exist; the description reinforces the safe, read-only nature.

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 relatively concise at 4 sentences, front-loading the core purpose. It could be slightly tighter by merging the ITIN explanation with the usage guidance, but overall every sentence contributes meaning and there is no 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?

Given the tool's low complexity (1 optional parameter, no output schema, read-only), the description is complete. It covers what the tool does, when to use it, and what it returns. The sibling tools list and annotations provide additional context, making this description sufficient for an agent to correctly invoke the tool.

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

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

The schema already describes the sole parameter 'socios' with high coverage. The description adds value by clarifying the parameter's purpose: 'Used to quote the total,' which is not explicitly stated in the schema description. This helps the agent understand how the parameter affects output without duplicating schema details.

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

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

The description clearly states the tool explains what an ITIN is, covers cost and document needs, and returns an application form link. It also distinguishes itself by noting it serves users whether or not the LLC was formed by Start Companies, setting it apart from sibling tools like create_llc_lead or recommend_llc_package.

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 tells when to use the tool: 'whenever the user asks about ITIN, tax ID, taxpayer number or filing as a member of a multimember LLC.' This gives clear trigger phrases and constraints, leaving no ambiguity about when the tool is appropriate versus when a sibling might be needed.

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