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get_audit_logs

Retrieve MCP audit logs for accountability, debugging, and compliance. View tool call history by date or limit results.

Instructions

Retrieve MCP audit logs for accountability and debugging.

USE FOR: viewing tool call history, debugging issues, compliance audits.

Examples: get_audit_logs() - Today's logs get_audit_logs(date='2026-05-29') - Specific date get_audit_logs(limit=10) - Last 10 entries

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
dateNoDate in YYYY-MM-DD format (default: today)
limitNoMax entries to return
formatNoOutput format: 'markdown' or 'json'markdown

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes
Behavior4/5

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

No annotations are provided, so the description carries the burden of behavioral disclosure. It explains the default behavior (today's logs) and how parameters affect output (limit and format). It does not mention authentication or rate limits, but for a simple retrieval tool, it provides sufficient transparency beyond the schema.

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 very concise: two clear sentences plus a 'USE FOR' line and three examples. Every sentence earns its place with no redundancy or fluff.

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 the tool's simplicity (3 optional params, no required fields) and the presence of an output schema (not shown but indicated by context signals), the description provides complete context. It covers purpose, use cases, parameter behavior, and examples, leaving no obvious gaps.

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?

Schema coverage is 100%, so baseline is 3. The description adds value by providing usage examples that demonstrate how each parameter is used (e.g., get_audit_logs(date='2026-05-29') for specific date). This clarifies parameter semantics beyond the schema descriptions.

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 retrieves MCP audit logs for accountability and debugging. It lists specific use cases (viewing tool call history, debugging, compliance audits) and provides examples, making the purpose distinct from sibling tools like list_audit_files.

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 explicitly states when to use the tool (viewing tool call history, debugging, compliance audits) but does not mention when not to use it or provide alternatives. It implies no usage restrictions, which is adequate but could be improved by noting that list_audit_files may be used for file listing.

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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