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mambaventures

NZXplorer MCP Server

get_governance_scorecard

Retrieve a governance scorecard for NZX-listed companies with RAG ratings across 15 policy areas, including board independence, diversity, and remuneration. Get overall score 0-100 and detailed assessments aligned with NZSA policies.

Instructions

Get a per-company governance scorecard with RAG (red/amber/green) ratings across 15 policy areas aligned with NZSA governance policies and the NZX Corporate Governance Code v1.7. Covers: remuneration disclosure, CEO rem structure, board independence, audit independence (non-audit >25% flag), director tenure (9yr threshold), board diversity (30% target), shareholder voting dissent (<75% threshold), ESG profile, capital management, takeover vulnerability, management credibility, succession readiness, audit firm tenure, director share ownership, whistleblowing. Returns overall score 0-100, individual policy assessments with scores and data. Use for 'governance scorecard for [company]', 'governance assessment', 'board governance quality', 'NZSA-aligned governance report'.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
tickerYesNZX ticker symbol (e.g. 'FPH', 'AIR', 'SPK')
Behavior2/5

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

No annotations are provided, so the description must cover behavioral aspects. It mentions return structure (overall score and individual assessments) but omits any mention of side effects, authentication needs, rate limits, or whether it is read-only. The description focuses on output content rather than behavioral traits.

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?

The description is well-structured: main purpose first, then detailed list of policy areas, return format, and usage examples. It is informative without being verbose. Minor improvement could be shortening the policy list, but each item adds context.

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 tool's complexity (15 policy areas, 0-100 score, no output schema), the description provides sufficient detail: lists all covered areas, explains the RAG rating system, and describes return structure. Usage examples further complete the picture.

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?

The schema covers the single parameter (ticker) with a clear description. The tool description reinforces the per-company nature but adds no additional semantic detail beyond the schema. With 100% schema coverage, the baseline of 3 is appropriate.

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 clearly states the tool retrieves a per-company governance scorecard with RAG ratings across 15 specific policy areas. It distinguishes itself from siblings like get_governance_scores by providing an exhaustive list of covered topics and aligning with NZSA/NZX standards.

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 explicitly lists example queries ('governance scorecard for [company]', 'governance assessment', etc.) and gives clear use cases. While it does not state when not to use, the examples effectively guide appropriate usage.

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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