Record
recordFetch full details for one DigitalNZ item by id — a DigitalNZ record id (the "id" field from search).
Input Schema
| Name | Required | Description | Default |
|---|---|---|---|
| id | Yes | e.g. "1234567". | |
| _apiKey | No | DigitalNZ API key (optional). |
recordFetch full details for one DigitalNZ item by id — a DigitalNZ record id (the "id" field from search).
| Name | Required | Description | Default |
|---|---|---|---|
| id | Yes | e.g. "1234567". | |
| _apiKey | No | DigitalNZ API key (optional). |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint, idempotentHint, and destructiveHint=false, so the description does not need to repeat safety. The description adds that the tool fetches 'full details' and uses a specific id, which is consistent with annotations and provides additional behavioral context.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single sentence with no wasted words, front-loaded with the verb 'Fetch', and every phrase is meaningful.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the simple nature of fetching one record and rich annotations, the description is largely complete. It explains what the tool does, what input is needed, and how to get the id. The lack of output schema is not a major issue as 'full details' is a common expectation.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100%, so baseline is 3. The description adds meaning by explaining that the 'id' parameter comes from the 'id' field of search results, which helps the agent understand the parameter's origin beyond the schema description.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description states the specific verb 'Fetch' and resource 'full details for one DigitalNZ item by id', clearly distinguishing from sibling tools like 'search' which return lists.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implicitly guides usage by specifying the input is a DigitalNZ record id from the 'id' field of search results, indicating when to use after a search. No explicit alternatives or exclusions are given, but the context is clear.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Add one secure layer between your agents and this server.
Several tools are difficult to distinguish: ask_pipeworx and ask_pipeworx_beta are currently identical, and ask_pipeworx_grounded, deep_research, and ask_pipeworx have fuzzy boundaries. The polymarket_* family plus bet_research also overlap heavily, requiring agents to carefully parse long descriptions to avoid misselection.
Naming is predominantly snake_case with a verb-first pattern (ask_, search, subscribe, unsubscribe, list_) and clear prefix families like polymarket_ and pipeworx_. Minor deviations like ai_visibility_check and entity_profile use noun-first phrasing, but the overall pattern is still predictable and readable.
33 tools is heavy for any single server, and the count is especially inappropriate given the server is named Digitalnz but only two tools (search, record) serve that domain. The rest form an unrelated grab-bag of data research, prediction-market, AI-visibility, memory, and utility tools.
The research workflow is fairly well covered: ask/grounded/deep modes, entity resolution, comparisons, claim validation, subscriptions, and alerts all exist. However, the DigitalNZ surface is nearly absent—just search and record—which is a significant gap for the declared server name, while other domains like AI visibility and npm dependencies are isolated one-offs.