State-by-state LLC dissolution: exact fees, forms, official state links. Not legal advice.
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Average 4.4/5 across 2 of 2 tools scored.
The two tools have clearly distinct purposes: one provides detailed requirements for a specific state, while the other lists fees across all states. There is no overlap or ambiguity in which tool to select.
Both tools follow a consistent verb_noun pattern: 'get_llc_dissolution_requirements' and 'list_llc_dissolution_fees'. The naming is uniform and predictable.
With only two tools, the surface is somewhat thin, but for a narrowly-scoped informational server it is reasonable. The two tools cover the two main ways users would interact with LLC dissolution data: per-state detail and cross-state fee comparison.
The domain is LLC dissolution by state, and the tools cover the key requirements (fee, form, filing method, processing time, office link) plus a comparative fee list. A minor gap could be a tool for comparing full requirements across multiple states, but the existing set handles the primary use cases.
get_llc_dissolution_requirementsHow to dissolve an LLC in a given stateAGet the requirements to dissolve (close) an LLC in a specific US state: the exact filing fee, the form name, how to file, typical processing time, and the official state filing office link. Reviewed against each state’s own Secretary of State. Use when someone asks how to close, dissolve, cancel or wind up an LLC in any state, what it costs, or which form they need.
| Name | Required | Description | Default |
|---|---|---|---|
| state | Yes | US state name or two-letter code, e.g. "Texas" or "TX" |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint=true and idempotentHint=true, so the agent knows this is a safe, deterministic operation. The description adds meaningful context: it claims the information is 'Reviewed against each state’s own Secretary of State', implying authoritative and verified data, and lists the exact return fields. This goes beyond the annotations by setting expectations for data quality and content.
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: the first states what the tool does and lists the specific output fields, the second gives usage guidance. Every sentence earns its place, there is no fluff, and the most important functional information is 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?
With only one parameter, no output schema, and safe-read annotations, the description is complete. It explicitly lists the return fields (fee, form name, process, processing time, official link) and describes the acquisition context. The addition of the sibling tool name and the phrase 'Reviewed against each state’s own Secretary of State' gives sufficient context for an agent to select and use the tool 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 single parameter 'state' is fully described in the schema with examples ('Texas' or 'TX'). The description adds only the phrase 'specific US state', which does not materially enhance the schema description. With 100% schema coverage, 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 uses a specific verb 'Get' with a clear resource 'requirements to dissolve an LLC in a specific US state' and enumerates exact data points (filing fee, form name, process, processing time, official link). It clearly distinguishes from the sibling tool `list_llc_dissolution_fees` by covering more than just fees.
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 'Use when someone asks how to close, dissolve, cancel or wind up an LLC in any state, what it costs, or which form they need.' This provides clear context for use. However, it does not explicitly mention when to use the sibling tool instead (e.g., 'if only fees are needed, use list_llc_dissolution_fees'), so it lacks an explicit exclusion/alternative.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
list_llc_dissolution_feesDissolution filing fees for all statesAList the LLC dissolution filing fee for all 50 US states and DC, quoted exactly as each state publishes it. Use when someone compares costs across states or asks which states charge to close an LLC.
| Name | Required | Description | Default |
|---|---|---|---|
No parameters | |||
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint=true and idempotentHint=true, covering safety. The description adds behavioral nuance by stating fees are quoted exactly as each state publishes them, signaling precision and no interpretation. This goes beyond structured 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 two sentences: the first states what the tool lists and its scope, the second gives when-to-use guidance. It is front-loaded, efficient, and contains no 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 simple, parameterless listing tool with strong annotations, the description is fully adequate: it covers scope (50 states + DC), precision (exact quotes), and use cases. No output schema is needed for a straightforward list, and no critical information 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?
The tool has zero parameters, and the schema is empty (100% coverage). No parameter explanation is needed, so the baseline score of 4 applies, and the description does not need to compensate for any parameter gaps.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description uses a specific verb ("List"), identifies the resource (LLC dissolution filing fee), and scopes it precisely to all 50 US states and DC. It clearly distinguishes from the sibling tool get_llc_dissolution_requirements, which covers requirements rather than fees.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides explicit usage context: "Use when someone compares costs across states or asks which states charge to close an LLC." It does not mention exclusions or alternative tools, but the guidance is clear enough for typical selection.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
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