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Glama

KrystalView Analytics

by io.github.KrystalView

Get Anomalies

get_anomalies
Read-onlyIdempotent

List detected traffic, friction, bounce, and conversion anomalies for the site.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
limitNoMaximum results to return.
unacknowledged_onlyNoOnly include unacknowledged anomalies.

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
dataYesDetected traffic, bounce, friction, and conversion anomalies for the site.
metaYesSite and rate-limit metadata for the current MCP call.

Schema Changelog

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

  1. First observed

TDQS

A4.1/5.0
Behavior4/5

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

Annotations already declare readOnlyHint and idempotentHint, so the description adds value by specifying the types of anomalies returned (traffic, friction, bounce, conversion). No contradictory information.

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?

A single, focused sentence that is immediately actionable and contains no extraneous information.

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?

Given the presence of an output schema and fully described parameters in the schema, the description is complete. It conveys the essential purpose without needing to repeat structured details.

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

Parameters3/5

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

Schema description coverage is 100% with both parameters (limit, unacknowledged_only) already described in the schema. The tool description does not add any additional parameter semantics beyond the schema.

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 clearly states it 'List[s] detected traffic, friction, bounce, and conversion anomalies for the site,' specifying both the verb and the resource types, and it distinguishes from sibling tools like get_errors.

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?

No explicit guidance is provided on when to use this tool versus alternatives like get_errors or get_notifications. The usage is implied but lacks exclusions or context.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

All KrystalView Analytics toolsInspect
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TDQS

A4/5.0
Disambiguation5/5

Each tool targets a distinct analytics dimension (anomalies, campaigns, errors, funnels, live visitors, notifications, scroll depth, sessions, site stats) with clear boundaries. Even overlapping concepts (sessions list vs detail vs live) are separated by distinct functionality.

Naming Consistency5/5

All tool names follow the consistent 'get_<resource>' pattern in snake_case, making it predictable for an agent to infer the purpose of each tool from the name alone.

Tool Count5/5

13 tools is well-scoped for an analytics server covering site stats, sessions, funnels, campaigns, errors, and real-time data. Each tool earns its place without redundancy or unnecessary complexity.

Completeness4/5

The set covers the major analytics domains (traffic, engagement, campaigns, errors, funnels, real-time). Minor gaps exist, such as missing tools for goal/conversion tracking beyond funnels, but core workflows are well supported.

Resources