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Tizona — verification and routing for autonomous agents

MAGPIE

superannuation_guarantee
Read-onlyIdempotent

Compute the Australian Superannuation Guarantee on a qualifying-earnings amount, exact to the cent. Returns the SG, the rate, the earnings subject to SG after the annual maximum-contributions-base cap, and the financial year used. Computed the CURRENT way — from 1 July 2026 the base is qualifying earnings (not OTE) and the cap is annual, under Payday Super, so old quarterly-OTE code is now wrong. You supply the qualifying-earnings figure; this does NOT define what counts as qualifying earnings. ATO-sourced, not tax advice. Current financial year only; an out-of-range date throws.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
asAtNoYYYY-MM-DD — which schedule to use. Defaults to today.
qualifyingEarningsYesThe qualifying-earnings amount to compute SG on, e.g. "5000.00".

TDQS

A4.4/5.0
Behavior5/5

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

Annotations already declare the safe read profile (readOnlyHint, idempotentHint, destructiveHint false). The description adds substantial context beyond that: the exact-to-the-cent accuracy guarantee, the list of returned fields, the method-change rationale (Payday Super), the ATO sourcing caveat and non-advice disclaimer, and the throw-on-out-of-range-date behavior. This is genuinely informative and consistent with the annotations — no contradiction.

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

Conciseness4/5

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

Purpose is front-loaded in the opening sentence, followed by returns, then the critical method caveat, then scope constraints. It is on the longer side, but every sentence carries distinct information — the Payday Super warning, the qualifying-earnings boundary, and the date constraint all earn their place. No filler or tautology.

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

Completeness5/5

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

Despite lacking an output schema, the description compensates by enumerating the return values (SG, rate, capped earnings, financial year). It also covers accuracy, temporal scope, error behavior, and legal caveat — everything an agent needs to invoke and interpret the tool correctly. No output schema or sibling routing gaps remain.

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

Parameters3/5

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

Schema coverage is 100%, so both parameters are already documented (qualifyingEarnings amount with example; asAt format and default). The description contributes one useful caveat — that the tool does NOT define what counts as qualifying earnings and trusts the supplied figure — which clarifies the parameter's scope. Otherwise it mostly restates schema content, matching the baseline for full coverage.

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?

States a specific verb (compute), a specific resource (Australian Superannuation Guarantee), and the exact input basis (qualifying-earnings amount). The precision guarantee ('exact to the cent') and distinct domain clearly separate it from all siblings, which concern awards, GST, entity names, email verification, and crawler access — none overlap with SG calculation.

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?

Gives strong temporal context: the tool computes the current way (post-1 July 2026 Payday Super basis) and explicitly warns that old quarterly-OTE code is now wrong, so an agent knows not to reach for legacy methods. It also scopes usage to 'Current financial year only; an out-of-range date throws.' It names no sibling alternative, but none of the listed siblings is a relevant SG fallback, so this is a minor gap rather than a routing omission.

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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