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NZXplorer (Remote)

get_remuneration_compliance

Read-onlyIdempotent

Get the Remuneration Disclosure Compliance Scorecard for an NZX company. Scores against 8 NZX Corporate Governance Code v1.7 criteria: individual fee disclosure, CEO compensation breakdown, STI/LTI hurdle disclosure, remuneration policy, committee independence, peer benchmarking, AGM say-on-pay vote, and termination payment disclosure. Returns 0-100 score with A-F grade. Use when asked about remuneration compliance, disclosure quality, pay transparency, or governance code alignment.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
tickerYesNZX ticker symbol (e.g. FPH)

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
dataYesThe tool payload. Null when the call did not produce one — read meta.availability_status to find out why, and do not treat null as zero, empty or "none found".
metaYes
toolYesTool that produced this result.
schema_versionYesEnvelope contract version. Bumps only on a breaking shape change.

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A4/5.0
Behavior4/5

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

Annotations already declare readOnlyHint, idempotentHint, destructiveHint=false and openWorldHint=false, so the safety profile is covered. The description adds genuine behavioral context beyond them: the exact scoring basis (8 governance criteria) and the numeric/letter-grade output, which tells the agent what kind of result to expect.

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?

Four sentences that are well front-loaded: purpose, methodology, output, then usage. The enumeration of all eight criteria is the longest element but it does explain the scoring, so it largely earns its place rather than padding.

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?

With an output schema present, return values need not be described, and annotations cover the safety profile. The description supplies purpose, scoring methodology, output shape and usage triggers, leaving nothing an agent needs to invoke it 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?

Only one parameter (ticker) and schema description coverage is 100%, so the schema fully documents it with an example ('NZX ticker symbol (e.g. FPH)'). The description adds no extra constraint or format detail about the parameter, so the baseline 3 applies.

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

Purpose4/5

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

Specific verb+resource ('Get the Remuneration Disclosure Compliance Scorecard for an NZX company') with a detailed statement of what is scored (8 named NZX Code v1.7 criteria) and the output form (0-100 score with A-F grade). It is unambiguous, though it never explicitly differentiates itself from close siblings like get_remuneration_benchmarks or get_executive_compensation.

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?

'Use when asked about remuneration compliance, disclosure quality, pay transparency, or governance code alignment' gives clear triggering contexts. No when-not conditions or named alternatives are provided, so it stops short of the explicit routing the top score requires.

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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