Every enricher (YouTube videos, Wikipedia, repo stats, downloads, company profiles, TL;DRs) and which collections turn it on by default. Items carry their results under enrichment.
| Name | Required | Description | Default |
|---|---|---|---|
No arguments | |||
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Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden. It discloses a meaningful behavioral detail: items carry their results under the `enrichment` field. It also conveys that the output is scoped to enrichers and their default collection configuration. It does not mention rate limits or auth, but for a simple listing tool this is acceptable.
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 compact, two sentences, and front-loaded with the core purpose. It provides useful examples and one key structural detail about the result payload without wasting words.
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?
For a parameterless listing tool, the description is largely complete. It names the domain, the scope, and where results live. The only minor gap is that it does not explicitly state the return shape (e.g., 'returns a list' or pagination behavior), but the wording strongly implies a list and no output schema is provided.
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?
The tool accepts no parameters, so the schema already covers everything. The description adds value by explaining what the returned items will contain, which is the relevant semantic context for an empty-parameter operation.
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 clearly states a specific verb ('list') and resource ('enrichers'), and enumerates concrete examples that disambiguate the tool from sibling list tools like list_adapters, list_collections, or list_sources. It also explains what the listing contains beyond the names — which collections enable each enricher by default.
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 purpose is clear enough that an agent can infer when to use it: when information about enrichers and their default collection associations is needed. However, it does not explicitly state when not to use it or name alternatives, though the sibling list provides such context implicitly.
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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The tools are mostly distinct: list_* tools cover different metadata resources, and item queries are separated into recent_items, search_items, upcoming, and feed_items. Some overlap exists among the item-retrieval tools, but descriptions clarify their different filters and use cases.
Most tools follow a verb_noun pattern such as add_source, create_feed, list_* and search_items. A few exceptions like feed_items, stats, and upcoming break the pattern, but the overall naming is still predictable and readable.
Fifteen tools is well within the expected range and each tool maps to a distinct part of the domain: adapters, sources, collections, enrichers, feeds, items, and stats. The count feels appropriate for the breadth of NicheDB without obvious bloat.
The read and query surface is strong, covering items, feeds, sources, collections, and enrichers. However, lifecycle management is incomplete: sources and feeds can be created but not updated or deleted, and feeds can be followed but not unfollowed, which leaves notable admin workflow gaps.