List existing backups in newest-first order. Choose detail level and response format (YAML or JSON) for output.
List existing backups, newest-first.
detail (str | None): full (default) | summary (long lists cut to 25 + count) | minimal (top-level scalars only).
response_format (str | None): yaml (default, token-cheap) | json.
| Name | Required | Description | Default |
|---|---|---|---|
| detail | No | ||
| response_format | No |
Changes observed during successful MCP inspections.
v0.4.0Input schema / properties / detailAdded value: +{
+ "anyOf": [
+ {
+ "type": "string"
+ },
+ {
+ "type": "null"
+ }
+ ],
+ "default": null,
+ "title": "Detail"
+}Input schema / properties / response_formatAdded value: +{
+ "anyOf": [
+ {
+ "type": "string"
+ },
+ {
+ "type": "null"
+ }
+ ],
+ "default": null,
+ "title": "Response Format"
+}v0.2.0Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the transparency burden and does well: it discloses ordering (newest-first), truncation behavior for long lists (cut to 25 + count), and format defaults (yaml, token-cheap). It does not explicitly state that listing is read-only, but that is strongly implied by 'List.'
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?
The description is three short, front-loaded lines: the purpose comes first, then each parameter in a compact form. Every sentence carries useful information with no filler or repetition.
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?
Given there is no output schema, the description covers the main invocation decisions: what will be listed, ordering, detail levels, and response formats. It does not enumerate the exact output fields for full/summary detail, but the format options and truncation rule give enough context to select and call the tool successfully.
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 is 0%, so the description is the only source of parameter meaning. It fully compensates by explaining each parameter: detail's allowed values (full, summary, minimal) and response_format's allowed values (yaml, json), plus their defaults. This is excellent beyond-schema guidance.
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 opens with a specific verb and resource: 'List existing backups, newest-first.' This clearly distinguishes bridge_snapshots from singular create/restore siblings like bridge_snapshot and bridge_restore, so an agent can tell exactly what it does.
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 gives clear context: use this tool when you need to see available backups, and it explains the available list-detail modes. It does not explicitly name alternatives or state when not to use it, but the verb and resource make the intended usage obvious.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.