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by io.github.BigRedCloud
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List Audit Log

brc_list_audit_log
Read-only

Returns current-session audit entries scoped to currently connected companies. Entries from other sessions, connections or companies are excluded.

Tool call template

This tool declares no required parameters. Add optional parameters from the input schema as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {},
    "name": "brc_list_audit_log"
  }
}

Input Schema

NameRequiredDescriptionDefault
connectionRefNoOpaque Red connection reference returned by brc_confirm_company_connection. Pass this exact value on every later tool call when the MCP client rotates session ids (for example Vibe/Mistral). Keep reusing the same connectionRef after successful tool calls — do not start a new connection because a lookup returned empty or partial data. It is not an API key and does not contain credentials.
includeTechnicalDetailsNoOnly set this to true if the user asks for technical details. Sensitive values are still redacted.

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A4/5.0
Behavior3/5

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

Annotations already provide readOnlyHint=true and destructiveHint=false, so the safety profile is covered. The description adds session and company scoping, but does not disclose return format, pagination behavior, or any operational limits. This matches a read-only list tool whose annotations carry the core safety context.

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?

Two concise sentences with the primary action and scope front-loaded and no redundant wording. Every sentence earns its place: the first states what is returned, the second clarifies exclusions.

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?

The description is sufficient for a low-complexity list tool with two optional, fully documented parameters and read-only annotations. It does not mention return shape or pagination, but for this tool's advertised behavior that is a minor gap rather than a blocking omission.

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%, and both parameters have rich descriptions in the schema. The tool description itself adds no parameter-level detail, but none is needed because the schema already fully documents connectionRef and includeTechnicalDetails.

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 uses a specific verb ('Returns') plus a clear resource ('current-session audit entries') and an explicit scope ('scoped to currently connected companies'). It also states what is excluded, which differentiates it from other list and clear tools like brc_clear_audit_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 makes clear this is for current-session audit entries and explicitly excludes other sessions, connections, or companies. It does not name an alternative tool or state when not to use it, but the scope itself is strong enough contextual guidance for an agent.

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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