Lookup Tax Rule

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

The description discloses several behavioral traits beyond the annotations: automatic country-library routing based on active company, required citation of source URL, handling of validity periods, and historical lookback for past dates. These are important operational details not captured in the readOnly/idempotent hints. No contradictions with 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?

Although the description is lengthy, it is well-structured and information-dense. It starts with purpose, then usage criteria, provides examples, explains return behavior, and covers historical usage. Each sentence earns its place; there is no filler or redundant phrasing.

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 complexity (country-specific rules, historical validity, citation requirements), the description covers all essential aspects: what it does, when to use it, how to handle past periods, what it returns, and how to find keys. The absence of an output schema is compensated by explicit description of the return value. Nothing needed for correct invocation 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 100% with detailed descriptions for both parameters. The description adds value by providing concrete examples of valid keys, clarifying how as_of works ('The system walks the rule history and returns the version in force on that date, plus the period it applies to'), and emphasizing when to omit it. This goes slightly beyond the schema but doesn't radically expand semantics.

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's function: 'Look up a verified tax or accounting rule by its key.' It specifies the resource (a rule) and the verb (look up), and provides concrete examples of keys for UK and UAE, making it easy to distinguish from siblings like get_tax_facts or list_tax_rules.

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 use case: 'Use this for ANY question about specific deadlines, thresholds, notice periods, regulatory dates, or rules where being wrong would mislead the user.' It also states when not to rely on memory ('ALWAYS prefer this over stating a rule from memory') and how to handle past periods with as_of. It names the alternative for unknown keys (list_tax_rules) and explains when to use it.

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