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get_audit_reasons

Retrieve audit-reason codes grouped by operation type to supply required audit reasons for Laserfiche delete or export actions.

Instructions

Return the audit-reason codes the authenticated user is allowed to supply.

Use before delete_entry or get_document_edoc (with export auditing) when LF_REQUIRE_AUDIT_REASON=true or when the user is asking for an audited delete. The response is grouped by operation type — pick an ID from the correct group.

Returns: Dict shaped roughly as {"deleteEntry": [{id, name, ...}], "exportDocument": [...], ...}. Each item has id, name, and description. The id is what you pass to delete_entry as audit_reason_id.

On failure: returns {"mode": "error", "error": <slug>, ...}. Common slugs: auth_failed if the account isn't permitted to audit.

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 behavior: it returns a dict grouped by operation type, details each item's fields, and describes failure responses including common error slugs like 'auth_failed'.

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-organized with distinct sections for purpose, usage, return value, and failure cases. Every sentence earns its place without redundancy.

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 and the presence of an output schema, the description explains the return shape, error handling, and provides enough context for an agent to use the tool correctly.

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

Parameters4/5

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

No input parameters exist (empty schema), so baseline is 4. The description adds value by explaining the output structure and how to use the returned IDs, which is more than the schema provides.

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 'Return the audit-reason codes the authenticated user is allowed to supply.' It specifies the exact verb and resource, and distinguishes from sibling tools by focusing on audit reasons.

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

Usage Guidelines5/5

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

Explicitly instructs to use before 'delete_entry' or 'get_document_edoc' under specific conditions (LF_REQUIRE_AUDIT_REASON=true or audited delete). It tells the agent which IDs to pick from the response groups.

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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