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extract_gebiz

Read-only

Singapore Government procurement opportunities (GeBIZ via data.gov.sg). Search by keyword, agency name, or empty for all recent tenders.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
urlYesKeyword, agency, or empty for latest tenders

Schema Changelog

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

  1. Added

TDQS

A4/5.0
Behavior3/5

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

Annotations already declare readOnlyHint=true and openWorldHint=true, covering the safety profile. The description adds minimal behavioral context, such as the ability to pass an empty query for all recent tenders, but it does not disclose return format, pagination, or rate limits. No contradiction with annotations.

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 one efficient sentence, front-loaded with the core purpose and followed by parameter usage. Every word contributes, with no fluff or repetition.

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?

Given the simple tool (one parameter, no output schema, safe read-only annotations), the description is largely sufficient. It covers the purpose and usage modes. It does not describe the returned structure, but openWorldHint and the straightforward nature of a search tool make that acceptable.

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%, with the single parameter 'url' described as 'Keyword, agency, or empty for latest tenders'. The tool description adds no new meaning beyond the schema; it essentially repeats the same usage guidance. The parameter name 'url' is slightly misleading, but the description clarifies it is not a URL.

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's function: 'Singapore Government procurement opportunities (GeBIZ via data.gov.sg)'. It uses a specific verb ('Search') and resource (procurement opportunities from GeBIZ/data.gov.sg), and the mention of Singapore distinguishes it from sibling tools like extract_govcontracts.

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 provides clear usage context by specifying search modes: 'Search by keyword, agency name, or empty for all recent tenders'. This tells the agent how to invoke the tool, but it does not explicitly contrast with alternatives such as extract_govcontracts, though the Singapore scope implies that.

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

A3.9/5.0
Disambiguation5/5

Each tool targets a distinct data source (finance, GitHub, Hacker News, etc.), with clear separation and no overlap. An agent can easily distinguish which tool to use for a given source.

Naming Consistency4/5

Tools use a consistent verb_noun pattern with 'extract_' for data extraction and 'search_' for search functions. The outlier 'package_trends' is still descriptive and fits the theme, so the pattern is mostly predictable.

Tool Count5/5

11 tools is well-scoped for a data aggregation server. Each tool serves a clear purpose and the count is neither too sparse nor overwhelming.

Completeness4/5

The server covers a broad range of sources (finance, code, news, social, academia, jobs, packages). Minor gaps like missing Twitter or general news are acceptable given the breadth already provided.