filterRun()

Creates a prepareRun function from declarative options. Pass the result to createScorer() to filter messages, limit context size, and drop unnecessary fields before the scorer pipeline runs.

Use filterRun() for declarative filtering. Write a custom prepareRun function directly when you need imperative logic that filterRun() doesn't cover. See Custom scorers: input filtering for more.

Usage example

The following example creates a scorer that only sees tool invocations and text messages, limited to the 20 most recent context messages:

src/mastra/scorers/tool-scorer.ts

import { createScorer, filterRun } from '@mastra/core/evals'

const toolScorer = createScorer({
  id: 'tool-usage',
  description: 'Evaluates tool usage patterns',
  type: 'agent',
  prepareRun: filterRun({
    partTypes: ['tool-invocation', 'text'],
    maxRememberedMessages: 20,
  }),
}).generateScore(({ run }) => {
  // run.input.rememberedMessages contains only tool and text messages
  // run.output contains only tool and text messages
  return 1
})

Filter by tool name

Keep only messages involving specific tools:

import { createScorer, filterRun } from '@mastra/core/evals'

const fileEditScorer = createScorer({
  id: 'file-edit-quality',
  description: 'Evaluates file editing patterns',
  type: 'agent',
  prepareRun: filterRun({
    toolNames: ['write_file', 'string_replace_lsp', 'view'],
  }),
}).generateScore(({ run }) => {
  // Only messages with these tool calls remain
  return 1
})

Drop fields

Remove fields the scorer doesn't need:

import { createScorer, filterRun } from '@mastra/core/evals'

const simpleScorer = createScorer({
  id: 'response-length',
  description: 'Checks response length',
  type: 'agent',
  prepareRun: filterRun({
    dropRequestContext: true,
    dropExpectedTrajectory: true,
    dropGroundTruth: true,
    maxOutputMessages: 5,
  }),
}).generateScore(({ run }) => {
  return run.output.length > 0 ? 1 : 0
})

Parameters

options:

FilterRunOptions

Configuration object that controls what data the scorer receives.

object

partTypes?:

MastraPartType[]

Keep only messages whose parts match these types. Each entry is prefix-matched against the message part's type. Plain text messages (no tool invocations) are always kept unless explicitly excluded. System messages and tagged system messages are never filtered.

toolNames?:

string[]

Keep only tool-invocation messages for these specific tools. Each entry is prefix-matched against the tool name. Non-tool messages (text, data) are unaffected.

maxRememberedMessages?:

number

Maximum number of messages to keep in remembered messages (context). Takes from the end (most recent). Applied after type and tool filtering.

maxOutputMessages?:

number

Maximum number of messages to keep in the output. Takes from the end. Applied after type and tool filtering.

dropRequestContext?:

boolean

Remove request context from the run entirely.

dropExpectedTrajectory?:

boolean

Remove expected trajectory from the run.

dropGroundTruth?:

boolean

Remove ground truth from the run.

Returns: (run: ScorerRun) => ScorerRun — A function suitable for the prepareRun option on createScorer().

Part types

The partTypes option accepts MastraPartType values. Each value is prefix-matched, so 'data-' matches all data part types.

Type	Description
'text'	Text content parts
'tool-invocation'	Tool call and result parts
'reasoning'	Chain-of-thought reasoning parts
'step-start'	Step marker parts
'image'	Image parts
'file'	File parts
'source'	Source reference parts
'source-document'	Source document parts
'data-'	All data parts (matches any data-* prefix)
'data-om-'	Observational memory data parts
'data-workspace-'	Workspace data parts
'data-sandbox-'	Sandbox data parts
'data-tool-'	Tool-related data parts

Filtering behavior

• Part type filtering applies to both input.rememberedMessages and output when they contain agent message arrays.
• Tool name filtering only affects messages that contain tool invocations. Text-only messages pass through.
• System messages (systemMessages, taggedSystemMessages) are never filtered, regardless of partTypes or toolNames.
• Message limits (maxRememberedMessages, maxOutputMessages) apply after type and tool filtering, taking the most recent messages.
• When both partTypes and toolNames are set, a message must satisfy both filters to be kept.