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list_repositories

List repositories accessible to your account on the Laserfiche server. Returns full enumeration when available, or a fallback with the configured repository if the endpoint is disabled.

Instructions

List the repositories this account can reach on the server.

Useful for confirming which repository the server is pointed at and for discovering alternate repositories the same account can access.

Endpoint variability: some self-hosted Laserfiche builds disable the /Repositories endpoint entirely. When the call fails, this tool does NOT raise — it returns the configured repo as a fallback so downstream tools can still run. Branch on mode == "fallback" if you need to distinguish a partial answer from a full enumeration.

Returns: On a healthy build, the server's raw OData listing with value: [{repoId, displayName, ...}, ...]. On endpoint failure: {"mode": "fallback", "warning": <str>, "server_error": <classified error>, "value": [{"repoId": "<LF_REPOSITORY_ID>", "displayName": null, "is_configured": true}]}.

On failure: this tool never raises and never returns mode: "error" — see the fallback shape above.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Behavior5/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

With no annotations provided, the description fully discloses behavioral traits: endpoint variability, fallback behavior on failure, non-raising nature, and output shape including 'mode' field to distinguish full vs fallback responses.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is well-structured with sections for purpose, usage, endpoint variability, return shape, and failure behavior. Every sentence adds value, and it is appropriately front-loaded.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness5/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given zero parameters, an output schema, and no annotations, the description fully covers the tool's behavior, return format, error handling, and edge cases, making it highly complete.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters5/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The input schema has no parameters, so the description does not need to add parameter information. It is sufficient and complete.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the tool lists repositories accessible by the account, with a specific verb ('List') and resource ('repositories'). It also distinguishes itself from sibling search tools by detailing its unique fallback behavior.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines4/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description provides context for when to use the tool (confirming the current repository and discovering alternate ones), but does not explicitly exclude scenarios or contrast with sibling tools like 'laserfiche_repository_list'.

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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