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knowbe4_reporting_training_summary

Get a summary of all training campaigns with total enrollments, completion counts, and overall completion rate. Track training progress to identify gaps and measure program effectiveness.

Instructions

Get a summary of all training campaigns including total enrollments, completion counts, and overall completion rate.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
pageNoPage number for pagination (default: 1)
per_pageNoNumber of results per page (default: 500, max: 500)
Behavior2/5

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

No annotations are provided, so the description carries the full burden of behavioral disclosure. While 'get a summary' implies a read-only operation, the description doesn't disclose whether pagination is required for full data (despite the page/per_page params), what the response format looks like, or any rate-limit or data-completeness caveats. For a reporting tool with pagination parameters, the behavior around data completeness across pages is relevant but undocumented.

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?

Single sentence, zero waste, front-loads the core purpose. Efficiently conveys the aggregates being returned. No redundant information.

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

Completeness3/5

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

The tool is relatively simple (2 optional parameters, no output schema, no nested objects), so the description covers the core functionality adequately. However, without annotations and without any return-format description, the agent has limited understanding of what the 'summary' actually contains beyond the three named metrics. Given the simplicity of the tool, this is adequate but not exemplary.

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 coverage is 100%, so the parameters (page, per_page) are already documented with defaults and max values in the schema. The description adds no additional parameter meaning beyond what the schema provides. Baseline 3 is appropriate since the schema handles the heavy lifting.

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 states the verb (get), the resource (training campaigns summary), and the specific data returned (total enrollments, completion counts, completion rate). It's distinguishable from siblings like knowbe4_training_campaigns_list (which lists campaigns individually) and knowbe4_reporting_phishing_summary (which covers phishing). While it doesn't explicitly name alternatives, the specific resource+metric (completion rate) makes the aggregation purpose clear.

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

Usage Guidelines3/5

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

The description implies this is for aggregate training reporting across all campaigns, contrasting with per-campaign tools like knowbe4_training_campaigns_get. However, it doesn't explicitly state when to choose this vs. the sibling reporting tools (phishing_summary, risk_overview) or the campaign list tools. The pagination parameters hint at when to use this for large datasets, but no explicit guidance on when this aggregation is appropriate vs. alternatives.

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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