list_sourcesList available data sources with their names, types, query languages, dialect hints, options, limits, and active read-only layers so you can choose where to run queries.
Lists the data sources you may query: name, type, query language, dialect hints, options, limits and the active read-only layers.
| Name | Required | Description | Default |
|---|---|---|---|
No arguments | |||
Changes observed during successful MCP inspections.
v0.0.0Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnly/idempotent/non-destructive/closed-world, so the safety profile is covered. The description adds real context beyond that by naming what is returned, including dialect hints, limits and active read-only layers, which tells the agent what it can learn before querying.
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?
One sentence, front-loaded with the verb, followed by an enumerated payload list. Slightly list-heavy but every item conveys what the agent can extract.
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?
With no parameters, no output schema and fully covered annotations, the description carries the remaining burden and does so by describing the returned content. Minor gaps: no mention of ordering, permissions or whether results are scoped to the caller's workspace.
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 takes zero parameters, so the baseline is 4; the description correctly implies no filtering arguments are needed.
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?
States a specific verb and resource ('Lists the data sources you may query') and enumerates the fields returned, which makes it distinguishable from query/get_result. It does not explicitly contrast itself with the sibling 'describe', but the discovery framing is clear.
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?
'you may query' hints that this is a pre-query discovery step, but there is no explicit when-to-use or when-not-to-use guidance, and no routing against the sibling 'describe' tool.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.