Skip to main content
Glama

create_pa_indicator

Create a Performance Analytics indicator by defining source facts table, aggregation function, and conditions. Use a PA job to collect data afterward.

Instructions

Create a Performance Analytics (PA) indicator / KPI on pa_indicators (requires WRITE_ENABLED=true). Define the source facts table, aggregation and conditions; collect data via a PA job afterward.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
nameYesIndicator name (e.g. "Open P1 incidents")
unitNoUnit (pa_units name or sys_id)
fieldNoField to aggregate (required for sum/average/max/min; ignored for count)
activeNoActivate immediately (default: true)
aggregateNoAggregation function
directionNoDesired trend
conditionsNoEncoded query on the facts table (e.g. "active=true^priority=1")
descriptionNoWhat the indicator measures
facts_tableNoSource/facts table the indicator counts (e.g. "incident")
Behavior4/5

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

Annotations already indicate readOnlyHint=false, making clear this is a write operation. The description adds valuable behavioral context: it notes the WRITE_ENABLED requirement and the need for a subsequent PA job to collect data, which annotations do not cover. No contradictions.

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?

Two sentences, front-loaded with the primary purpose and requirement. Every clause adds value: action, resource, condition, what to define, and post-creation step. No wasted words.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness3/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

No output schema exists, so the description should cover what the tool returns. It mentions the need for a PA job but does not state what the response contains (e.g., sys_id). For a creation tool with 9 parameters, this is a gap, though the core concept is explained adequately.

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 coverage is 100% with detailed parameter descriptions (e.g., field, aggregate, conditions). The description mentions 'source facts table, aggregation and conditions', but adds little beyond the schema. For a tool with full schema coverage, baseline 3 is appropriate.

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 specifies the action ('Create'), the resource ('Performance Analytics indicator / KPI'), and includes context like the table name and a required configuration setting (WRITE_ENABLED=true). It distinguishes from sibling tools like create_pa_breakdown by focusing on indicator creation.

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?

The description provides some usage context (requires WRITE_ENABLED=true and mentions post-creation job), but lacks explicit guidance on when to use this tool vs. alternatives like create_pa_breakdown or create_kpi. No exclusions or when-not-to-use are stated.

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

Install Server

Other Tools

Latest Blog Posts

MCP directory API

We provide all the information about MCP servers via our MCP API.

curl -X GET 'https://glama.ai/api/mcp/v1/servers/aartiq/nowaikit'

If you have feedback or need assistance with the MCP directory API, please join our Discord server