Tizona — verification and routing for autonomous agents

LORIKEET

calculate_gst

Read-onlyIdempotent

Add GST to a GST-exclusive amount, or extract the GST from a GST-inclusive amount, in exact integer cents. GST in an inclusive price is one ELEVENTH, not one tenth. "basis" is required — "exclusive" adds, "inclusive" extracts (synonyms accepted); an unknown basis throws rather than returning a wrong figure.

Input Schema

TableJSON Schema

Name	Required	Description	Default
`basis`	Yes	Whether the amount already includes GST.
`amount`	Yes	The money amount, e.g. "110.00". At most two decimal places.

TDQS

A4.6/5.0

Behavior5/5

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

Beyond the read-only/idempotent annotations, the description discloses the one-eleventh calculation rule, exact integer-cent precision, synonym acceptance for basis, and a throw-on-unknown-basis failure mode. This is rich behavioral context that annotations did not provide.

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

Conciseness5/5

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

Three sentences, front-loaded with the core behavior, then the critical rate caveat, then the parameter-specific contract. There is no filler; every sentence contributes operational information.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness4/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a simple two-parameter calculator with read-only/idempotent annotations, the description covers the main calculation paths and failure behavior. There is no output schema, and the description stops just short of stating the exact return value structure, but the exact-cent language gives enough direction for likely invocation.

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

Parameters4/5

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

Schema coverage is 100%, so the schema already documents both parameters. The description adds value by mapping 'exclusive' to add, 'inclusive' to extract, noting synonyms are accepted, and stating that an unknown basis throws instead of returning a wrong figure.

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

Purpose5/5

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

The first sentence names a precise operation on a specific resource (GST amounts) and distinguishes the two supported modes: add-to-exclusive vs extract-from-inclusive. It also sets it apart from the financial sibling tools by scoping to GST-only arithmetic.

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

Usage Guidelines4/5

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

It gives clear, actionable conditions: use 'exclusive' when the amount excludes GST and 'inclusive' when it includes GST. It does not name sibling alternatives explicitly, but the decision context is unambiguous enough for an agent to select this tool.

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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TDQS

A4.2/5.0

Disambiguation4/5

Most tools map cleanly to a distinct action and resource: single-URL lookup, batch triage, watch/pull lifecycle, and the entity-name operations are each clearly separated. The only likely confusion is between check_ai_crawler_access and verify_ai_crawler, but the descriptions draw that boundary well.

Naming Consistency4/5

Tool names overwhelmingly follow a verb_noun convention such as calculate_gst, verify_email_address, and normalise_entity_name. The non-verb award_pay_rate and the slightly awkward total_invoice and pull_ai_crawler_watch are minor deviations from an otherwise consistent pattern.

Tool Count5/5

Fourteen tools sits comfortably in the well-scoped range, and each cluster earns its place: entity matching, Australian compliance, email verification, and AI crawler access all have distinct tool groupings. Nothing feels redundant, and the count reflects the server's broad verification purpose without bloat.

Completeness4/5

The surface covers the core verification workflows well, including batch and watch variants for crawler access and a full set of entity-name operations. The main gap is that the server name promises routing but the tools mostly verify and triage rather than actively route; minor lifecycle niceties like unwatching are also absent.

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