UK Immigration Lawyers — visa data tools

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

Annotations already mark the tool as read-only and idempotent. The description adds valuable context beyond that: coverage specifics (412 codes, 270 with published rates, 38 national pay scales, 104 not eligible), the authoritative source, the update date, and a 'not advice' caveat. This gives the agent a good sense of data scope and limitations.

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 with the primary purpose, then adds only high-value details: coverage counts, source, update date, and a caveat. Every sentence earns its place, and there is no repetition of schema or annotation 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 read-only lookup tool with well-documented parameters and no required inputs, the description covers the key context an agent needs: what the tool returns information about, the acceptable lookup keys, and data coverage. It does not explicitly describe the output shape, but the absence of an output schema is partly mitigated by the clear domain scope.

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 reinforces that queries use job titles and SOC codes, which mirrors the schema, but it adds no extra parameter-level detail such as formatting rules, precedence between query and soc, or how limit behaves beyond what the schema already supplies.

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 names a specific verb ('look up'), a precise resource (UK Skilled Worker visa going rate and minimum salary), and the lookup keys (job title or SOC 2020 code). It clearly identifies what the tool does and is readily distinguishable from the sibling tools, which cover licence checks and visa cost estimation.

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 clearly implies when to use this tool: whenever the goal is to find the going rate or minimum sponsored salary for a UK Skilled Worker role by job title or SOC code. It does not explicitly name alternatives or state when not to use it, but the context is clear enough for an agent to select it appropriately.

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 read-only and idempotent behavior. The description adds meaningful context beyond this: it clarifies the legal/interpretive meaning of a register match ('does not mean the employer will sponsor a given job') and explicitly labels the output as information, not advice. This goes beyond the structured hints.

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 written sentences with the core action front-loaded and no wasted words; each sentence adds a distinct point: what it does, what the results mean, and a disclaimer. It is 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?

For a simple read-only lookup with no output schema, the description covers what it returns (matching organisations, sponsorship routes, rating) and warns about false positives. Combined with the rich parameter descriptions in the schema and the readOnly/idempotent hints, an agent has enough 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?

Schema coverage is 100%, so the baseline is 3 and the description need not repeat parameter details. It does echo the name/town search semantics ('by organisation name (and optionally town)') without adding format or syntax details, so it adds no significant value 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?

States a specific verb (Check) and resource (Home Office register of licensed sponsors), and explicitly describes what it searches by and returns. This clearly differentiates it from siblings (going_rate, visa_cost_estimate) without needing to open their schemas.

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 makes the primary use case evident—checking whether a UK employer holds a sponsor licence—and adds an interpretive caveat about register presence. However, it does not explicitly state when to prefer this tool over siblings or when not to use it, leaving the routing inference 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?

Annotations already establish read-only and idempotent behavior; the description adds meaningful context such as the fee schedule date of 8 April 2026, IHS part-year rounding, route extras like the citizenship ceremony, and the exclusion of legal fees. It consistently says this is an estimate and not advice, which is transparent about the tool's limits without contradicting 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 compact and front-loaded: the first sentence states the core purpose, followed by a concise route list, the effective date, and scope caveats. No sentence is filler, and the length is appropriate 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?

The description covers the route set, fee components, schedule date, and exclusions, which is strong for a read-only estimator. Since there is no output schema, it would be slightly improved by stating the return format or currency, but the listed components largely tell an agent what to expect.

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 documents route meanings, priority costs, and dependant handling. The description adds value beyond the schema by mentioning the fee schedule date, IHS adult/child rates and part-year rounding, and route-specific extras, giving the agent context about how the parameters influence the calculation.

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 opens with a specific action and object: 'Estimate the Home Office fees for a UK visa or citizenship application,' then lists the exact fee components and supported routes. This clearly distinguishes the tool from siblings like going_rate and sponsor_licence_check by scope and route coverage.

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 its use case through 'Estimate the Home Office fees' and the route list, but it never explicitly says when to use this tool over siblings or what to use when a route is unsupported. The 'Government fees only' and 'Information, not advice' disclaimers clarify boundaries but do not route the agent to alternatives.

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