list_sources
List where the AI governance tool data comes from, with the license and refresh of each source.
Input Schema
| Name | Required | Description | Default |
|---|---|---|---|
No arguments | |||
List where the AI governance tool data comes from, with the license and refresh of each source.
| Name | Required | Description | Default |
|---|---|---|---|
No arguments | |||
Changes observed during successful MCP inspections.
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint, idempotentHint, destructiveHint=false and a closed-world scope, so safety is covered. The description adds real value beyond them by disclosing the shape of each returned record (license and refresh per source), which no output schema provides.
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 and resource, with the returned fields appended where they add the most value. Nothing is wasted and nothing is buried.
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 no-parameter, closed-world list with no output schema, the description covers both what is enumerated and what each entry contains. A note on ordering or whether the source list is fixed would close the last gap.
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 there is nothing to disambiguate and baseline 4 applies; the description correctly makes no parameter claims.
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?
Specific verb ('List') plus resource ('where the AI governance tool data comes from') and the fields returned (license, refresh). It reads clearly against siblings like get_stats and list_places, though it never names them to reinforce separation.
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 only implied: an agent can infer this is the provenance/attribution lookup, but there is no statement of when to prefer it over get_stats or search_listings, nor any prerequisite or exclusion.
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.