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Get the audit log

bunny_get_audit_log
Read-only

Who changed what on one day: the account audit log (timestamp, product, resource, action, actor and a diff). Paginate with continuation_token. bunny.net: GET /user/audit/{date}.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
dateYesThe day to read, YYYY-MM-DD.
limitNoMax entries, 1-10000. Default 100.
orderNoSort by time.
productNoOnly these products.
actor_idNoOnly changes by these actors.
resource_idNoOnly these resource IDs.
resource_typeNoOnly these resource types.
continuation_tokenNoContinuationToken from the previous page.

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed1 schema field changed
    • changedInput schema / $schema
      Previous value: -"http://json-schema.org/draft-07/schema#"New value: +"https://json-schema.org/draft/2020-12/schema"
  2. First observed

TDQS

A4.1/5.0
Behavior4/5

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

Annotations only declare readOnlyHint=true; the description goes further by disclosing the returned record shape (timestamp, product, resource, action, actor, diff) and the pagination mechanism. There is no output schema, so this return-content detail is genuinely additive. It omits auth/permission requirements and any rate or retention limits.

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

Conciseness4/5

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

Three short, front-loaded clauses: purpose first, pagination second, endpoint mapping last. Every sentence carries information, though citing the raw endpoint path is marginally redundant with the tool name and endpoint convention.

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

Completeness4/5

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

With 8 parameters but only 1 required and 100% schema coverage, plus no output schema, the description fills the important gap by describing the returned fields and pagination flow. The filter parameters (product, actor_id, resource_id, resource_type) are never mentioned, but the schema covers them adequately.

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

Parameters3/5

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

Schema description coverage is 100%, so every parameter including date, limit, order, and the filter arrays is already documented in the schema. The description only meaningfully echoes the date scoping and continuation_token paging, adding little beyond the structured data. Baseline 3 is appropriate.

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 opens with a specific verb+resource framing ("Who changed what on one day: the account audit log") and enumerates exactly what the log contains (timestamp, product, resource, action, actor, diff). No sibling tool covers audit history, so it is trivially distinguishable from bunny_get_statistics, bunny_get_billing, and the DNS/storage tools.

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?

It clearly scopes usage to a single day and notes pagination via continuation_token, which tells the agent how to iterate results. It does not state any exclusions or when-not conditions, but with no competing audit-log sibling there is little ambiguity to resolve.

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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