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Netmon (demo)

by com.netmon
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alerts_list

Read-onlyIdempotent

List configured alert definitions across both axes of the rule engine. Modern alerts (table alerts, class-scoped: syslog_log / event_log / eve_log / device_down / storage) and legacy alerts (per-device tracker thresholds, surfaced via the _hell view) are fetched, normalized, merged, filtered, and paginated.

Wraps GET /api/alerts (modern) and POST /api/getAlerts (legacy). Both endpoints return their full catalog; this tool applies the filters and pagination client-side, so the LLM doesn't need to know which axis a filter applies to.

Output rows carry a source discriminator and a synthetic id string (e.g. "modern:42" / "legacy:17") so dedup is unambiguous; the original numeric id is on raw_id. Modern rows carry class, severity, and last-evaluated stats. Legacy rows carry type (tracker kind), device_id, and tracker_name.

Modern rows carry NO throttle / renotify fields, on purpose: since 21.93 no modern class consults them (log-stream classes are one-fire and edge-triggered per event key; device_down and storage are stateful and diff open incidents), so they explain nothing about when a modern alert re-fires. Do not claim a modern alert is flap-damped or on a renotify timer — it isn't. Legacy trackers DO still renotify on a timer, but that config lives on the trigger and is not returned here either.

last_result_count is NOT the same measure across classes. For syslog_log / event_log / eve_log it is the raw match count from the last evaluation BEFORE edge-trigger dedup — a steady nonzero means the pattern keeps matching, NOT that anything was notified (repeat matches of an already-seen occurrence are suppressed). For device_down it is a level: devices currently down and in scope, so nonzero means an outage is open right now. For storage it is likewise a level: volumes currently low (or held open because their reading is unreadable/stale) and in scope. Never sum or compare the two. last_evaluated_at is the last scheduler tick that touched the alert; legacy rows have no equivalent. For what actually fired and was delivered, use alerts_history.

Filters (all optional, AND-combined): scope (modern|legacy|all, default all), class (modern only — silently ignored on legacy rows), severity (int or array), enabled (bool), device_id (legacy only — modern alerts are class-wide), search (case-insensitive substring on label).

Pagination: per_page defaults to 50 (max 200), page is 1-indexed. meta.total is the post-filter count; meta.has_more flags more pages. tag-scoped server-side at the legacy axis (legacy rows for devices outside the user's slug set are filtered by Laravel before this tool sees them).

Permission: alerts. Example: alerts_list({severity: 1, enabled: true, search: "router", per_page: 20})

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
pageNo1-indexed page number (default 1).
classNoModern-only filter on the alert class (silently ignored on legacy rows).
scopeNoWhich axis to query: 'modern' (alerts table), 'legacy' (_hell view), or 'all' (default).
searchNoCase-insensitive substring match on label.
enabledNoRestrict to enabled (true) or disabled (false) alerts.
per_pageNoRows per page (default 50, max 200).
severityNoSeverity int or array of ints. Modern uses 1-5 (lower=worse). Legacy varies by tracker type; passing an int filters both axes.
device_idNoLegacy-only: restrict to a single device id. Ignored on modern rows.

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A4.7/5.0
Behavior5/5

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

The description goes well beyond the read-only/idempotent annotations, disclosing client-side filtering/pagination, the source discriminator and synthetic id, the absence of throttle/renotify semantics for modern alerts, and class-dependent meaning of last_result_count and last_evaluated_at. It even warns against incorrect claims such as flap-damping, which is a valuable behavioral guardrail.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is long but front-loaded: purpose, endpoints, output shape, behavioral caveats, filters, pagination. Given 8 optional parameters, two alert axes, and no output schema, the length is justified; slight redundancy and prose density keep it from a perfect score.

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?

With no output schema, the description carries the full burden of explaining return values, and it does: row shape, id/raw_id, discriminator, class-specific fields, meta pagination fields, permission requirement, and a concrete example. An agent has enough context to invoke and interpret results correctly.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters5/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Even though schema coverage is 100%, the description adds critical semantics: filters are AND-combined, scope defaults to 'all', class/device_id are silently ignored on the opposite axis, severity meaning differs by axis/class, and pagination is client-side with post-filter meta fields. This transforms parameter definitions into an operational contract.

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 states a specific action (list alert definitions) and scopes it to both axes of the rule engine, naming all modern classes and the legacy view. It clearly distinguishes this from alerts_history by noting the latter covers what actually fired, preventing confusion with the sibling tool.

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 explains when to use this tool versus alerts_history ('For what actually fired and was delivered, use alerts_history') and provides an example call. It also clarifies filter scoping (class ignored on legacy, device_id ignored on modern) so an agent can select appropriate filters, though it does not enumerate all alternative tools or exclusions.

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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