## Overview

The `InstructionFollowingEvaluator` assesses whether an agent’s response follows all explicit instructions provided in the user’s prompt. It focuses strictly on instruction compliance — whether specific constraints, requirements, and directives were satisfied — regardless of response quality or factual accuracy.

## Key Features

-   **Trace-Level Evaluation**: Evaluates the most recent turn in the conversation
-   **Binary Scoring**: Clear Yes (instructions followed) / No (instructions not followed) classification
-   **Async Support**: Supports both synchronous and asynchronous evaluation
-   **Constraint-Focused**: Evaluates compliance with explicit directives, not overall quality

## When to Use

Use the `InstructionFollowingEvaluator` when you need to:

-   Verify that agents respect format, length, or style constraints
-   Check compliance with specific answer options or output types
-   Assess whether agents follow multi-part instructions completely
-   Evaluate instruction adherence independently from correctness

## Evaluation Level

This evaluator operates at the **TRACE\_LEVEL**, evaluating the most recent turn in the conversation.

## Parameters

### `model` (optional)

-   **Type**: `Model | str | None`
-   **Default**: `None` (uses default Bedrock model)
-   **Description**: The model to use as the judge.

### `system_prompt` (optional)

-   **Type**: `str | None`
-   **Default**: `None` (uses built-in template)
-   **Description**: Custom system prompt for the judge model.

### `version` (optional)

-   **Type**: `str`
-   **Default**: `"v0"`
-   **Description**: Prompt template version.

## Scoring System

| Rating | Score | Description |
| --- | --- | --- |
| Yes | 1.0 | All explicit instructions in the prompt are satisfied |
| No | 0.0 | One or more explicit instructions are not satisfied |

A response passes the evaluation if all explicit instructions are followed (score = 1.0).

## What Counts as Explicit Instructions

The evaluator checks for compliance with specific directives such as:

-   **Information constraints**: “Based on this text passage, give an overview about \[…\]”
-   **Length requirements**: “Summarize this text in one sentence”
-   **Answer options**: “Which of the following is the tallest mountain…”
-   **Target audience**: “Write an explanation for middle schoolers”
-   **Genre**: “Write an ad for a laundry service”
-   **Style**: “Write an ad for a sports car like it’s an obituary”
-   **Content type**: “Write a body for this email” vs “Write a subject line”

## Evaluation Rules

-   If a response includes **more** information than requested, it still passes as long as all requested elements are present
-   If a response is purely evasive without any partial or related answer, it defaults to **Yes**
-   If a response is partially evasive but provides a partial answer, the partial answer is judged
-   If there are **no explicit instructions** in the input (casual or open-ended requests), defaults to **Yes**
-   The evaluator does **not** assess factual accuracy, writing quality, or response effectiveness

## Basic Usage

Required: Session ID Trace Attributes

When using `StrandsInMemorySessionMapper`, you **must** include session ID trace attributes in your agent configuration. This prevents spans from different test cases from being mixed together in the memory exporter.

```python
import asyncio

from strands import Agent
from strands_evals import Case, Experiment
from strands_evals.evaluators import InstructionFollowingEvaluator
from strands_evals.mappers import StrandsInMemorySessionMapper
from strands_evals.telemetry import StrandsEvalsTelemetry

telemetry = StrandsEvalsTelemetry().setup_in_memory_exporter()

def task_function(case: Case) -> dict:
    agent = Agent(
        trace_attributes={"session.id": case.session_id},
        callback_handler=None
    )
    response = agent(case.input)
    spans = telemetry.in_memory_exporter.get_finished_spans()
    mapper = StrandsInMemorySessionMapper()
    session = mapper.map_to_session(spans, session_id=case.session_id)
    return {"output": str(response), "trajectory": session}

cases = [
    Case(
        name="format-constraint",
        input="List the top 3 programming languages in bullet points."
    ),
    Case(
        name="length-constraint",
        input="Explain quantum computing in exactly one sentence."
    ),
]

experiment = Experiment(cases=cases, evaluators=[InstructionFollowingEvaluator()])
async def main():
    report = await experiment.run_evaluations_async(task_function)
    report.run_display()

asyncio.run(main())
```

## Combining with Other Evaluators

Pair with quality evaluators to assess both compliance and correctness:

```python
evaluators = [
    InstructionFollowingEvaluator(),  # Did it follow the format/constraints?
    CorrectnessEvaluator(),           # Is the content factually correct?
    ConcisenessEvaluator(),           # Is it appropriately concise?
]
```

## Related Evaluators

-   [**CorrectnessEvaluator**](/pr-cms-3708/docs/user-guide/evals-sdk/evaluators/correctness_evaluator/index.md): Evaluates factual accuracy (complementary to instruction following)
-   [**OutputEvaluator**](/pr-cms-3708/docs/user-guide/evals-sdk/evaluators/output_evaluator/index.md): Flexible custom rubric evaluation
-   [**RefusalEvaluator**](/pr-cms-3708/docs/user-guide/evals-sdk/evaluators/refusal_evaluator/index.md): Detect when agents refuse to address prompts
-   [**CoherenceEvaluator**](/pr-cms-3708/docs/user-guide/evals-sdk/evaluators/coherence_evaluator/index.md): Assess logical consistency and reasoning

## Related pages

- [Prompt Engineering](/pr-cms-3708/docs/user-guide/safety-security/prompt-engineering/index.md) (2 shared tags)
- [Prompts](/pr-cms-3708/docs/user-guide/concepts/agents/prompts/index.md) (2 shared tags)
- [Attack Strategies](/pr-cms-3708/docs/user-guide/evals-sdk/red-teaming/strategies/index.md) (1 shared tag)
- [Harmfulness Evaluator](/pr-cms-3708/docs/user-guide/evals-sdk/evaluators/harmfulness_evaluator/index.md) (1 shared tag)
- [Reading the Report](/pr-cms-3708/docs/user-guide/evals-sdk/red-teaming/reading_the_report/index.md) (1 shared tag)
- [Red Teaming](/pr-cms-3708/docs/user-guide/evals-sdk/red-teaming/index.md) (1 shared tag)
- [Refusal Evaluator](/pr-cms-3708/docs/user-guide/evals-sdk/evaluators/refusal_evaluator/index.md) (1 shared tag)
- [Responsible AI](/pr-cms-3708/docs/user-guide/safety-security/responsible-ai/index.md) (1 shared tag)
- [Scoring Attacks](/pr-cms-3708/docs/user-guide/evals-sdk/red-teaming/evaluators/index.md) (1 shared tag)
- [Stereotyping Evaluator](/pr-cms-3708/docs/user-guide/evals-sdk/evaluators/stereotyping_evaluator/index.md) (1 shared tag)