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Read the audit log

get_audit_log
Read-only

Fetch the append-only audit log of sensitive WordPress actions—writes, deletes, SQL, WP-CLI—with timestamps, sites, and outcomes. Use filters to view recent entries per site or all sites.

Instructions

Read the append-only local audit log of every sensitive action this server has taken — writes, deletes, SQL, WP-CLI, theme publishes — with timestamp, site, tool, target and outcome. Useful for answering "what did the AI actually change?".

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
limitNoHow many of the most recent entries to return.
site_idNoWhich configured WordPress site to act on. Optional — with a single site configured it is used automatically; with several, the default site is used unless you name one. Run list_sites for valid ids.
all_sitesNoInclude entries for every site rather than just one.
Behavior3/5

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

Annotations already declare readOnlyHint=true and destructiveHint=false, covering the safety profile. The description adds behavioral context by noting the log is 'append-only' and detailing the types of actions recorded, which goes beyond the annotations. It does not disclose auth requirements or rate limits, but given the annotation coverage, a modest score is appropriate.

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 a single, information-dense sentence that front-loads the purpose and includes a practical use case. Every phrase earns its place, with no redundant wording.

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?

With no output schema, the description fills the gap by specifying the return fields (timestamp, site, tool, target, outcome) and the scope of actions logged. It also hints at pagination via the limit parameter, covered in the schema. An agent has everything needed to call this tool correctly.

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 all three parameters (limit, site_id, all_sites) are already documented in the schema. The description does not add any parameter-specific semantics beyond the schema; it focuses on the tool's output and purpose. Per the calibration, baseline 3 is correct when the schema carries the parameter documentation.

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 states a precise verb ('Read') and a specific resource ('the append-only local audit log'), and enumerates the log's contents (writes, deletes, SQL, WP-CLI, theme publishes) with fields (timestamp, site, tool, target, outcome). This clearly distinguishes it from sibling tools like audit_content and audit_media, which target content/media rather than the system action log.

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 gives explicit usage context: 'Useful for answering "what did the AI actually change?"', which tells an agent when to reach for this tool. However, it does not name alternatives or state when not to use it. Since there are no closely competing siblings, this is adequate but not fully explicit.

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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