search_monitors_by_nameCase-insensitive substring search across monitor names and URLs.
| Name | Required | Description | Default |
|---|---|---|---|
| query | Yes | Case-insensitive substring matched against monitor names or URLs. |
Changes observed during successful MCP inspections. Dates show when Glama detected each change.
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations provided; description only states case-insensitive substring matching but omits return format, pagination, or any side effects. Behavioral traits beyond the basic operation are absent.
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?
Single sentence, 8 words, completely front-loaded with no wasted words. Ideal conciseness for the information conveyed.
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?
Despite low complexity (1 param, no output schema), the description lacks details on output format, sorting, limits, or default behavior, which are important for a search tool.
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?
Schema description coverage is 100% and the parameter description is already clear. The tool description adds marginal value by confirming the search scope (names and URLs) beyond the schema.
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 it performs a case-insensitive substring search across monitor names and URLs, distinguishing it from sibling tools like get_monitor (specific monitor) and list_monitors (all monitors).
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?
No guidance on when to use this tool vs alternatives (e.g., list_monitors, get_monitor). Missing explicit context for when substring search is appropriate.
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.
Each tool targets a specific resource or action (monitor, outage, escalation policy, etc.) with clear naming. No two tools could be easily confused; even similar ones like get_monitor_outages and get_monitor_anomalies serve distinct purposes.
All tools follow a consistent verb_noun pattern (create_, get_, list_, pause_, resume_, search_, update_) and use snake_case uniformly. This makes the tool set predictable and easy to navigate.
With 26 tools, the set is slightly above the typical well-scoped range of 3-15, but each tool serves a distinct monitoring function (monitors, outages, escalations, integrations, schedules, alerts, team members). The count is reasonable for the domain.
The tool surface is heavily read-oriented, lacking create/update/delete for most resource types (escalation policies, integrations, on-call schedules, outages). Even monitors lack a delete tool. This leaves significant gaps for administrative workflows.