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WYRE-AI
by WYRE-AI

umbrella_activity

Retrieve raw request-level activity logs from Cisco Umbrella for a specified time range, with optional breakdown by traffic type such as DNS, proxy, or firewall.

Instructions

Raw activity (request-level) log over a time range, optionally broken down by traffic type.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
toYesRange end, epoch milliseconds.
fromYesRange start, epoch milliseconds.
limitNoMaximum number of records to return.
offsetNoNumber of records to skip, for paging.
trafficTypeNoOptional traffic-type breakdown. Omit for the all-traffic-types view.
additionalParamsNoEscape hatch for any documented Cisco Reports/Investigate query parameter not modeled explicitly above (e.g. categories, identityids, verdict, domains), passed through verbatim as query string key/value pairs.

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

C2.9/5.0
Behavior2/5

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

With no annotations, the description carries full responsibility for behavioral disclosure, but it only states that this is a raw activity log. It does not mention pagination behavior, default limits, potential result size, ordering, or authorization requirements. This is a meaningful gap for a tool that likely returns large log datasets.

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, focused sentence with no filler. It front-loads the core meaning (raw request-level activity) and then specifies the two main axes: time range and traffic type. Every word contributes to comprehension.

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

Completeness2/5

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

Given no output schema and no annotations, this description is not complete enough for safe invocation. An agent would not know what fields are returned, how pagination behaves, whether a limit is required, or what the default result size is. Additional context about the raw log's shape and volume is missing.

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 the schema already documents all parameters, including additionalParams and trafficType. The description adds only high-level context about time range and traffic-type breakdown, which is adequate but not substantial beyond the schema.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly identifies this as a raw, request-level activity log over a time range with an optional traffic-type breakdown. This distinguishes it from aggregate sibling tools like umbrella_total_requests, though it does not explicitly name any sibling. The phrasing could use a verb, but the resource and scope are clear.

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

Usage Guidelines2/5

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

The description gives no explicit guidance about when to use this tool versus alternatives such as umbrella_total_requests, umbrella_api_usage_requests, or umbrella_domain_volume. The word "raw" implies it is for request-level logs rather than summaries, but no when-to-use or when-not-to-use guidance is provided.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.