List data sources for the authenticated application. Optionally filter by data source type(s). Returns paginated results ordered by last update.
| Name | Required | Description | Default |
|---|---|---|---|
| page | No | ||
| limit | No | ||
| data_source_types | No | Filter by data source type(s): 'website_crawler', 'pdf_upload', 'open_api', 'helpspace', 'custom_webcrawler', 'webhook'. Returns all when omitted. |
| Name | Required | Description | Default |
|---|---|---|---|
No arguments | |||
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint=true, so the safety profile is covered. The description adds beyond that by stating pagination, ordering by last update, and the authenticated-application scope, which are useful behavioral details not present in annotations.
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?
Two sentences with no filler. The core action, scope, optional filter, and result ordering are all conveyed efficiently and front-loaded.
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 simple read-only listing tool with an output schema and readOnly annotation, the description covers scope, optional filtering, pagination, and ordering. It is not penalized heavily for missing return details since an output schema exists, but it could benefit from clarifying the available data source type values.
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 description coverage is only 33%, and the description does little to compensate. It mentions that filtering by data source type is optional but does not clarify the page/limit parameter meanings, and the data_source_types parameter's schema description contains values that partly mismatch the enum ('pdf_upload', 'open_api', 'custom_webcrawler' vs. the actual enums). The tool description adds minimal semantic value for parameters.
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 uses a specific verb and resource ('List data sources') and clearly states scope ('for the authenticated application'). It does not explicitly call out sibling distinctions, but the resource noun naturally differentiates it from list_nodes, list_prompts, and list_tools.
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 mentions optional filtering by data source type, which implies a common use case, but it does not explain when to prefer this over alternative listing tools or when filtering is necessary versus when to retrieve all. The guidance is implied rather than explicit.
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.
Each tool targets a distinct resource or metric, and even the closely related analytics tools (e.g. get_top_languages vs get_top_locales, get_top_interaction_sources vs get_top_clicked_urls) are explicitly differentiated in their descriptions. There is no real overlap that would cause an agent to misselect.
The verb prefixes create_, get_, list_, read_, and update_ are used predictably, and there is no mixing of camelCase or other conventions. The main inconsistency is that read_sessions is actually a list operation while list_nodes is the equivalent pattern for nodes, and read_session_detail is the singular read.
At 33 tools, this set is well beyond the 16-25 'heavy' range and far above the typical well-scoped 3-15 range. Many of the get_top_* analytics endpoints are individually distinct but could likely be consolidated into fewer parameterized tools to reduce agent selection overhead.
The read and analytics side is comprehensive, but the management lifecycle has notable gaps: knowledge nodes support create/read/update but no delete, and data sources/tools lack create/delete operations. Agents can work around some gaps, but content deletion is a clear dead end for a knowledge-base management surface.