UK Stamp Duty Calculator (SDLT / LBTT / LTT)

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

Annotations already declare readOnlyHint=true, destructiveHint=false, idempotentHint=true. The description adds valuable behavioral details: it returns a banded breakdown, total tax payable, and effective rate, and states rates are current as of April 2026. This fully informs the agent of the tool's output and currentness.

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 a single, well-organized paragraph that front-loads the main purpose. While it is information-dense and thorough, it includes some redundancy (e.g., listing tax names twice). It earns each sentence, but could be slightly more concise without losing clarity.

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 moderate complexity (4 parameters with enums, jurisdiction differences) and no output schema, the description is highly complete. It explains all input scenarios, output structure (banded breakdown, total, effective rate), and rate currency. An AI agent can confidently invoke this tool based on the description alone.

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% with each parameter having a description. The tool description adds significant extra meaning: for 'property_type' it explains that mixed-use qualifies for commercial rates with no surcharge; for 'buyer_type' it details FTB relief up to £625k and corporate flat 17% rate. This goes well 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?

The description clearly states the tool calculates UK property transaction tax (SDLT, LBTT, LTT) for multiple jurisdictions and property types, naming specific reliefs and surcharges. It effectively distinguishes itself from sibling tools (bridging_cost_analyser, btl_stress_tester, development_appraisal) which address different financial topics.

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 when to use the tool: 'Use when a user asks about stamp duty, SDLT, LBTT, LTT, additional dwelling surcharge, ADS, first-time buyer relief, or transaction tax on a specific UK property purchase.' This provides clear, actionable guidance for an AI agent.

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