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NZXplorer (Remote)

search_semantic

Read-onlyIdempotent

Hybrid semantic + keyword search across NZX announcements. Uses AI embeddings to find conceptually related filings, even if exact keywords differ. Better than search_announcements for: vague queries ("companies discussing AI strategy"), conceptual searches ("climate risk disclosures"), finding similar announcements, and queries where exact keyword matches miss relevant results. Combines BM25 keyword matching with vector similarity and Cohere reranking for best results.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
qYesNatural language search query (e.g. "companies discussing supply chain disruption")
toNoEnd date (YYYY-MM-DD)
fromNoStart date (YYYY-MM-DD)
typeNoAnnouncement type filter
limitNoMax results (default 10)
tickerNoFilter by company ticker

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

A4.3/5.0
Behavior4/5

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

Annotations already declare read-only, idempotent, non-destructive behavior, so the description is not required to cover the safety profile. It does add useful mechanism context (BM25 keyword matching + vector similarity + Cohere reranking), which explains why results may differ from a literal keyword search, though it omits latency/rate-limit or result-cap behavior.

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 and differentiator are front-loaded, and the comparative list maps directly to routing decisions. The closing sentence on BM25/reranking is implementation detail that is slightly less essential for an agent, keeping it just short of a 5.

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?

With an output schema present, return-value documentation is unnecessary, and all six parameters are covered by the schema. The description supplies routing guidance and search semantics; only minor operational details (pagination/results behavior, latency) are absent, which is a small gap.

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 description coverage is 100%, so every parameter's meaning is already documented in the schema. The description adds only a conceptual example query, no extra syntax or format guidance beyond what the schema provides, so the baseline 3 applies.

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 and resource ('hybrid semantic + keyword search across NZX announcements') and immediately distinguishes itself from the sibling search_announcements by naming it. An agent can tell the two apart without opening either schema.

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

Usage Guidelines5/5

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

Explicitly enumerates when this tool wins: vague queries, conceptual searches, similarity lookups, and cases where exact keyword matches miss. It names the alternative (search_announcements) and the condition that selects it, leaving nothing to inference.

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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