List tools configured for the authenticated application. Optionally filter by active status. Returns all matching tools.
| Name | Required | Description | Default |
|---|---|---|---|
| active | No | true = active only, false = inactive only, omit = all. |
| Name | Required | Description | Default |
|---|---|---|---|
No arguments | |||
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
The annotations already establish read-only behavior (readOnlyHint: true), and the description adds the authenticated-application scope and 'returns all matching tools' with optional active filtering. It does not contradict the annotations, but it does not disclose ordering, pagination, or what the default active filter resolves to when omitted.
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?
Three short, direct sentences are front-loaded with the core purpose and contain no filler. Every sentence earns its place.
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 single-optional-parameter list tool with an output schema and read-only annotations, the description is nearly complete: it states scope, optional filtering, and that all matches are returned. The only notable gap is that it does not clarify the behavior when the active parameter is omitted, especially given the schema's default/omit ambiguity.
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 for the only parameter is 100%, so the schema carries the semantic weight; the description merely restates that active filtering is optional. It does not resolve the ambiguity between the active property's default (true) and its schema text ('omit = all'), so the description adds little beyond the schema.
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 the specific verb 'List' with a clear resource ('tools configured for the authenticated application') and names the filtering dimension. This naturally separates it from read_tool (single-tool retrieval) and list_nodes/list_data_sources (different resources), so an agent can identify it among siblings.
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?
Usage is implied: use this tool to enumerate tools and filter by active status, while read_tool is available for individual lookup. However, the description does not explicitly state when to prefer list_tools over alternatives or mention any exclusions, so it relies on inference.
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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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.