Aus Accounting MCP

Read a cited legislation section

read_tax_legislation_section

Read-onlyIdempotent

Retrieve the full text of a cited tax legislation provision using its row ID, and optionally include neighbouring sections for context.

Instructions

Read one cited provision in full from the configured corpus.

Returns the same citation fields as search plus the stored text up to 12000 characters; total_chars reports the whole length and a caveat names the register page when the text is truncated. neighbours adds the provisions either side, each cited and truncated like a search match, so a subsection can be read in context without guessing the labels around it. Preserve the citation and the attribution. Local reads only, not a confirmation of current law.

Input Schema

TableJSON Schema

Name	Required	Description	Default
`row_id`	Yes	row_id returned by search_tax_legislation, such as 'C2004A05138:0421:40-25'.
`neighbours`	No	Provisions to return on each side of the cited one, in the title's document order, at search length. 0 returns the provision alone.

Output Schema

TableJSON Schema

Name	Required	Description
`after`	Yes	Up to neighbours provisions after the cited one in document order, nearest first, at search length.
`before`	Yes	Up to neighbours provisions before the cited one in document order, nearest last, at search length.
`corpus`	Yes	Corpus-level source, retrieval date and licence terms from the operator's configured corpus; empty when the corpus ships no manifest.
`notice`	Yes
`section`	Yes

Schema Changelog

Changes observed during successful MCP inspections.

Addedv0.1.13Sep 21, 2026

TDQS

A4.5/5.0

Behavior5/5

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

Annotations already declare readOnlyHint, idempotentHint, and non-destructive behavior, so the description adds meaningful context beyond them: truncation at 12000 characters, total_chars reporting the whole length, the caveat naming the register page, neighbours behavior, and the 'not a confirmation of current law' warning. This is substantial behavioral disclosure.

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?

The description is compact and front-loaded with the core operation, then layers in truncation, neighbours, and legal caveats without wasted words. Every sentence adds useful information.

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?

Given the presence of an output schema and safety annotations, the description covers the necessary behavioral details: truncation, total length reporting, neighbours semantics, and the legal status of the content. An agent has enough information to invoke the tool correctly.

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%, with row_id and neighbours both well documented, including an example for row_id. The description restates neighbours behavior but adds little beyond the schema. This matches the baseline for fully documented parameters.

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 description states a specific verb and resource: 'Read one cited provision in full from the configured corpus.' This clearly distinguishes it from search_tax_legislation, which likely returns citations rather than full text. The scope and outcome are unambiguous.

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?

The description implies the intended workflow by noting the row_id comes from search_tax_legislation, so an agent can infer it is used after finding a citation. It also gives an important usage caveat: 'Local reads only, not a confirmation of current law.' It does not explicitly name alternatives, but the read-after-search context is clear.

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

Deploy Server