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Glama

Gets Nz

by io.github.pipeworx-io

Nz Tender Detail

nz_tender_detail
Read-onlyIdempotent

Fetch full detail for a single New Zealand government tender from GETS by its RFx ID (the numeric id from nz_tender_open / nz_tender_search results, e.g. 32705858). Returns tender name, reference number, buying agency, department/business unit, tender type (RFP, RFT, RFQ, etc.), coverage, open and close dates, UNSPSC categories, regions, required pre-qualifications, contact, full overview text, and the human GETS page URL.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
idYesGETS RFx ID, e.g. "32705858".

Schema Changelog

Changes observed during successful MCP inspections. Dates show when Glama detected each change.

  1. Changed1 schema field changed
    • addedInput schema / examples
      Added value: +[
+  {
+    "id": "32705858"
+  }
+]
  2. First observed

TDQS

A4.4/5.0
Behavior4/5

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

Annotations already declare readOnlyHint, idempotentHint, and destructiveHint, so the description's behavioral disclosure is less critical. However, the description adds useful context by listing the specific fields returned, such as tender name, dates, and URL, which aids agent understanding.

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 a single, well-structured sentence that front-loads the purpose, then provides the ID source and example, and lists returned fields. Every part adds value without redundancy.

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?

For a simple tool with one parameter and no output schema, the description is fairly complete. It details the returned data extensively. Lacking explicit error handling or validation messages is acceptable given the simplicity and rich annotations.

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

Parameters4/5

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

The input schema has 100% coverage, but the description adds meaning by explaining that the ID is numeric and comes from sibling tools, providing an example (32705858). This clarifies the parameter's origin and format beyond the schema's brief description.

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 uses a specific verb ('Fetch') and identifies the resource ('full detail for a single New Zealand government tender from GETS'), with a unique identifier (RFx ID). It implicitly distinguishes from siblings like nz_tender_open and nz_tender_search by referencing them as sources for the ID.

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 clearly states when to use this tool: when you have an RFx ID from the sibling search tools. It does not explicitly list when not to use or provide alternative tools, but the context is clear and practical.

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

A3.8/5.0
Disambiguation2/5

Multiple tools overlap significantly: ask_pipeworx, ask_pipeworx_beta, and ask_pipeworx_grounded serve nearly identical purposes, and deep_research further duplicates. Polymarket tools (bet_research, polymarket_arbitrage, polymarket_edges, etc.) also have overlapping scopes, making it hard for an agent to select the correct one without deep inspection.

Naming Consistency3/5

Tool names use a mix of patterns: some are descriptive phrases (ai_visibility_check, generate_llms_txt), others are domain-prefixed (nz_tender_*, polymarket_*) but lack a uniform verb_noun structure. The ask_pipeworx series diverges from the rest, and verb choices are inconsistent (compare_entities vs scan_competitor_ai_presence).

Tool Count2/5

With 34 tools, the surface is large and feels bloated. The server covers multiple distinct domains (NZ tenders, Polymarket, memory, subscriptions) that could be separate servers. Many tools are variants of the same core functionality (e.g., four ask_pipeworx variants), inflating the count without clear necessity.

Completeness3/5

For a general-purpose data query server, the tool set covers a broad range of sources (SEC, FDA, FRED, etc.) and includes CRUD for memory and subscriptions. However, obvious gaps exist: no dedicated web search tool (ask_pipeworx is for structured data), and NZ coverage is limited to tenders only. Missing update/delete for some resources (e.g., no way to modify a subscription beyond unsubscribe).

Resources