Autocomplete values for a segmentation criterion. Useful for discovering valid values when building segment definitions.
| Name | Required | Description | Default |
|---|---|---|---|
| search | No | Optional search string to filter matching values | |
| criterion_id | Yes | Criterion ID from nevent_segmentation_criteria, e.g. "country", "event_attended" |
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?
Annotations already cover the safety profile (readOnlyHint=true, destructiveHint=false), lowering the burden on the description. The description adds the autocomplete/search-filtering behavior, but does not disclose return format, result limits, or matching semantics. For a simple read-only lookup these are minor gaps given annotation coverage.
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?
Two sentences with the core function front-loaded in the first sentence. The second sentence is slightly redundant ('discovering valid values' restates 'autocomplete values') but earns its place by adding the segment-building context. No wasted words overall.
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 simple two-parameter, read-only tool with fully described schema properties and safety annotations, the description adequately covers purpose and usage context. The main omission is the return format, but with no output schema and self-explanatory autocomplete semantics, this is a modest gap.
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 coverage is 100%: both parameters are well documented, with criterion_id referencing its source ('from nevent_segmentation_criteria') and giving concrete examples like 'country' and 'event_attended'. The description adds no parameter-level meaning beyond what the schema already provides, so the baseline of 3 applies.
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 first sentence, 'Autocomplete values for a segmentation criterion,' names a specific verb and resource clearly. The second sentence anchors it to segment definition building, which implicitly separates it from analytics-filter siblings like nevent_analytics_filter_values, though that differentiation is not explicit.
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?
'Useful for discovering valid values when building segment definitions' gives an implied usage context but does not state when to prefer this tool over similar discovery tools such as nevent_analytics_filter_values, nor does it mention exclusions. The guidance is present but left to inference.
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 domain groups are distinct, but the campaign reporting cluster has three tools returning overlapping engagement metrics (get_campaign, get_campaign_metrics, campaign_report), and paid_ads_status vs paid_ads_health have fuzzy boundaries. The detailed descriptions mitigate but do not eliminate the risk of an agent calling the wrong tool.
All names use the nevent_ prefix and snake_case, and most CRUD operations follow verb_noun. However, several tools reverse the order or drop the verb entirely (segment_preview, segment_execute, campaign_report, paid_ads_status, analytics_query), making the convention mixed but still readable.
With 59 tools, this is far above the 25+ 'too many' threshold and falls into the 50+ extreme range. The broad domain coverage explains some of the size, but for an agent the set is likely to be overwhelming and harder to navigate than a more focused server.
The core marketing workflow (segments, templates, campaign creation, quote, schedule, metrics) is covered, but there is no way to update, cancel, or delete a campaign, and templates and segments lack delete operations. These are notable lifecycle gaps that agents will hit when users want to change or clean up resources.
