list_sources
List where the peptide provider data comes from, with the license and refresh of each source.
Input Schema
| Name | Required | Description | Default |
|---|---|---|---|
No arguments | |||
List where the peptide provider 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 readOnly, idempotent, non-destructive, and closed-world, so the safety profile is fully covered. The description adds return-content context (each source comes with a license and refresh value), which is useful since no output schema exists, but it says nothing about pagination, ordering, or result size.
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?
A single front-loaded sentence with no filler; the verb, resource, and returned fields all appear before any trailing detail.
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 zero-parameter, read-only enumeration tool with no output schema, the description covers what is returned at a high level and the annotations cover the safety profile. Only pagination/ordering behavior is left unstated, which is a minor 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 for the description to disambiguate; the baseline of 4 applies. The description correctly implies a no-argument listing call.
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 ('List where the peptide provider data comes from') and clarifies the payload each entry carries (license and refresh). The resource is clearly distinct from siblings like list_categories, list_places, and get_stats, though no sibling is named explicitly.
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 discovery call for provenance/licensing metadata, but the description offers no when-to-use condition, no prerequisites, and no pointer to alternatives such as get_stats for aggregate questions.
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.