Skip to main content
Glama

investigate_campaign

Build an auditable campaign investigation packet with performance metrics, drivers, and evidence to explain results and support decisions.

Instructions

Build an auditable campaign investigation packet with metrics, drivers, and evidence.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
recordsYes
campaign_nameYes
compare_period_recordsNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

C2.4/5.0
Behavior2/5

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

With no annotations provided, the description carries the full behavioral burden. "Auditable" hints that output is meant to be evidence-grade, but nothing is said about whether the tool is read-only or writes anything, how it handles the supplied records, or any limits/determinism concerns.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

A single front-loaded sentence with no filler or redundancy. It is efficient, though the terseness is arguably under-specification rather than disciplined concision for a 3-parameter tool.

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

Completeness2/5

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

An output schema exists, so return values need not be explained, but with no annotations, 0% parameter coverage, and no routing guidance relative to near-identical siblings, an agent lacks the information needed to call this confidently.

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

Parameters2/5

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

Schema description coverage is 0% and the description never mentions campaign_name, records, or compare_period_records. It gives no clue what shape "records" should take or how the optional comparison period changes results, so an agent cannot construct a correct call from the description alone.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose3/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description names a verb ("Build") and a product ("auditable campaign investigation packet") with a hint of contents ("metrics, drivers, and evidence"). It does not, however, distinguish this from the sibling build_evidence_packet, which sounds like the same artifact, so the purpose remains fuzzy at the level an agent needs.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines2/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

There is no statement of when to use this tool versus build_evidence_packet, investigate_growth_issue, compare_campaign_metrics, or analyze_growth_query, and no mention of prerequisites or expected input conditions. The agent is left to guess from the name alone.

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