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AIops-tools

Monitoring AIops

swql_canned

Run pre-defined SWQL queries to retrieve network monitoring data such as down nodes or flapping interfaces. Specify query parameters and row limits for targeted results.

Instructions

[READ] Run a named canned SWQL query (e.g. nodes_down, flapping_interfaces).

Returns the same envelope as swql_query: {"rows": [...], "returned": N, "limit": L, "truncated": bool}. truncated is measured against the full result set — do not treat a capped result as the complete answer.

Args: name: Canned query name (from swql_library). params: Optional query params (e.g. {"min": 90} for a threshold). target: SolarWinds target name from config; omit for the default. limit: Maximum rows to return. Default 1000.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
nameYes
limitNo
paramsNo
targetNo

Schema Changelog

Changes observed during successful MCP inspections. Dates show when Glama detected each change.

  1. First observedv0.9.0

TDQS

A4.2/5.0
Behavior4/5

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

With no annotations provided, the description takes on the full burden. It clearly marks the operation as [READ], specifies the exact return envelope, and warns that 'truncated' is measured against the full result set so a capped result should not be treated as complete. This is valuable behavioral context beyond the schema.

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 compact, front-loaded with the core purpose, and every line earns its place. The return envelope and truncation warning are important caveats, and the Args block is clearly structured. No filler or redundancy.

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?

There is no output schema, so the description appropriately explains the return envelope and truncation semantics. It also covers all parameters, including the source of valid names. It is complete enough for an agent to invoke correctly, though it does not discuss error behavior or enumerate available canned queries.

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

Parameters4/5

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

Schema description coverage is 0%, so the description must compensate for all four parameters. It does so: name is tied to swql_library, params is illustrated with an example, target is explained as config-based with a default, and limit is given with its default. This adds real meaning beyond the schema's bare titles and defaults.

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 verb and resource: 'Run a named canned SWQL query,' with concrete examples like 'nodes_down, flapping_interfaces.' It distinguishes this tool from siblings by emphasizing 'canned' and deriving names from swql_library, separating it from ad-hoc swql_query.

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?

Usage context is implied through 'canned SWQL query' and 'name from swql_library,' but there is no explicit statement about when to prefer this over swql_query or other alternatives. It does not provide exclusions or direct routing guidance.

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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