get_network_summary
Get the network summary
Current host verdict counts, open incidents and anomalies in the last 24h.
Input Schema
| Name | Required | Description | Default |
|---|---|---|---|
No arguments | |||
Get the network summary
Current host verdict counts, open incidents and anomalies in the last 24h.
| Name | Required | Description | Default |
|---|---|---|---|
No arguments | |||
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint=true, and the description adds the last-24h temporal scope and the included data categories. However, it does not disclose return format, pagination, or whether counts reflect live or cached data.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is very brief and front-loaded, but the first sentence 'Get the network summary' largely restates the tool name. The second sentence carries the substantive value and is concise.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a zero-parameter read-only summary tool, the description conveys the main output categories and time window. It lacks precise output shape or field details, but the simplicity of the tool makes this adequate.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The tool has zero parameters and the schema coverage is 100% (empty properties), so the baseline 4 applies. The description adds no parameter details, but none are needed.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool retrieves a network summary and enumerates its contents: host verdict counts, open incidents, and anomalies in the last 24 hours. This distinguishes it from sibling detail-oriented tools like list_incidents and list_anomalies.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies use for a high-level aggregate network overview, but it does not explicitly state when to prefer this tool over sibling list/get tools or when not to use it. No alternatives are named.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Add one secure layer between your agents and this server.
Most tools are cleanly separated by resource type: participants, access points, hosts, providers, incidents, anomalies, and SLA each have their own get/list vocabulary. The main ambiguous pairs are get_provider_sla vs get_provider_sla_by_key, list_providers vs list_public_providers, and get_summary vs get_network_summary.
The overall get_/list_ verb_noun pattern is consistent and readable, and plural/singular resource names are mostly clear. There are a few exceptions: get_provider_sla and get_country_providers return collections despite using get_, and list_provider_certs is more of an aggregate posture endpoint than a simple list.
43 tools is well beyond the typical well-scoped MCP surface and will make the tool set harder for an agent to navigate defensibly. The tools are systematically grouped, but this looks like a broad REST API surface rather than a compact, purpose-fit MCP server.
For a read-only monitoring and directory domain, the coverage is unusually complete: list/detail endpoints, histories, SLA tables, churn breakdowns, anomalies, incidents, adoption aggregates, software landscape, and quality checks are all represented. The drill-down routes such as churn totals to churn participants also avoid dead ends.