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forge_metric_create

Define a new metric to assess conversations by specifying name, description, linked services, notes, tags, and metric value type.

Instructions

Create a new metric for evaluating conversations.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
nameYesUnique metric name within the organization
descriptionYesDescription of the metric
applied_to_servicesYesService IDs this metric applies to
additional_notesYesAdditional notes about the metric (null if none)
tagsYesTags (alphanumeric keys and values, no hyphens or special characters)
metric_valueYesMetric value definition. Must include "type" discriminator: "boolean", "numerical", or "categorical"
org_idNoOrg ID (uses active org if omitted)
Behavior2/5

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

With no annotations, the description bears full responsibility for behavioral disclosure. It only states the action without detailing side effects, permissions, error handling, or return behavior. Significant gaps exist.

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?

The description is a single, concise sentence without superfluous words. It is front-loaded and efficient, though it could benefit from additional substance without losing conciseness.

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?

Given the tool's complexity (7 parameters, nested objects, no output schema or annotations), the description is too minimal. It omits return values, error conditions, and other contextual details needed for complete understanding.

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%, so the schema adequately documents parameters. The description does not add extra meaning beyond what is in the schema, resulting in a baseline score of 3.

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 the tool's action: 'Create a new metric for evaluating conversations.' It uses a specific verb (create) and resource (metric) and specifies the domain (evaluating conversations), distinguishing it from sibling tools like forge_metric_update.

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?

The description provides no guidance on when to use this tool versus alternatives like forge_metric_update or other creation tools. It does not mention prerequisites, when not to use, or any exclusions.

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

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