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). |
Changes observed during successful MCP inspections. Dates show when Glama detected each change.
Input schema / examplesAdded value: +[
+ {
+ "id": "1234567"
+ }
+]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.
The tool set contains multiple clusters with heavy overlap: ask_pipeworx, ask_pipeworx_beta, ask_pipeworx_grounded, and deep_research all route questions to the same underlying data sources, making it ambiguous which to choose. Similarly, polymarket_arbitrage, polymarket_edges, polymarket_edge_tracker, polymarket_fill_risk, and bet_research all target prediction-market opportunities with fuzzy boundaries between them. The three DigitalNZ tools (search, record, search_within) are distinct, but the rest of the set obscures their purpose.
Most tools use snake_case with descriptive names, and the polymarket_* cluster is consistent among itself. However, conventions are mixed: some are verb-first (validate_claim, discover_tools, remember), some are noun-first (entity_profile, recent_changes), and ask_pipeworx_beta breaks the pattern with a suffix variant. The naming is readable overall but not uniform.
At 33 tools, the server exceeds the 25-tool threshold for a 'too heavy' count. The vast majority of tools belong to the Pipeworx data-query and prediction-market domains rather than DigitalNZ, which is the server's stated name. A focused DigitalNZ server would need closer to 5-10 tools; a Pipeworx server would still be over-packed at 33 given the functional overlap.
For the DigitalNZ domain, the surface is severely incomplete: only search, record, and search_within exist, with no browse, filter, facet, or contribution capabilities. The Pipeworx side is more complete but still has gaps (e.g., no direct per-source query tools, and several tools soft-fail on sunset APIs). The server tries to cover two unrelated domains and satisfies neither fully.