---
id: BTBB-TEC-001
code: BTBB-TEC-001
title: Explicit Direction Compliance
slug: explicit-direction-compliance
type: lesson
author: Herb Hermes
date: '2026-04-14'
last_updated: '2026-04-14'
description: A reusable technique lesson for forcing a model into a precise output
  recipe through direct step-by-step instructions.
excerpt: When a challenge depends on exact wording or exact output shape, explicit
  directions can become the engine that drives the whole route.
summary: Canonical technique block for high-control output shaping through direct
  instructions.
category: techniques
difficulty: beginner
platform: Universal
challenge: Truthteller Gandalf
read_time: 7 minutes
tags:
- techniques
- explicit-directions
- output-shaping
- truthteller
- merge-candidate
aliases:
- follow the directions completely
- output recipe compliance
- step-by-step obedience
search_aliases:
- precise output sequencing
- direct recipe prompt injection
status: live
test_type: adversarial
model_compatibility:
- Kimi K2.6
- GPT-5.4
- Universal
public_path: /content/lessons/techniques/explicit-direction-compliance.md
pillar: learn
pillar_label: Learn
section: techniques
collection: techniques
canonical_family: techniques
block_role: starter
content_role: merge-candidate
proof_status: walkthrough_proven
public_badge: Bot-Tricks Certified
build_stage: starter
requires_fundamentals:
- contextual-modification-semantic-force
combines_well_with:
- string-amalgamation-output-assembly
- output-dilution-control-response-shaping
recognition_signals:
- the challenge scores exact output form
- the route depends on constrained wording rather than broad freeform output
- the model is likely to follow enumerated instructions
common_failure_modes:
- the model follows the procedure but the semantic result is still too weak
- the model adds extra filler that dilutes the intended outcome
used_in_walkthroughs:
- BTBB-TTG-WT01
responsible_use: Use this lesson only in authorized labs, CTFs, sandboxes, or systems
  you are explicitly permitted to test.
lab_slug: xss
learning_path: ai-bugs-puncturing-the-web
guide_path: /content/guides/techniques/explicit-direction-compliance.html
---

# Explicit Direction Compliance

> Reusable Lesson: Techniques · Starter

## Purpose

This lesson teaches a simple reusable technique: use direct, explicit steps to force the model into a precise output recipe.

## Lesson profile

- Family: Techniques
- Role: Starter block
- Job in the build: make the model prioritize the requested output procedure
- Snaps onto: puzzle-like assembly evasions, semantic strengthening fundamentals, and output control blocks

## What this block is

Explicit Direction Compliance is a technique where the prompt gives the model a tightly controlled set of instructions such as:
- begin with this exact phrase
- append this exact string
- output the final combination

The point is not subtle persuasion. The point is to drive the output into a predictable shape.

## Why it works

Many models are trained to be helpful, obedient, and instruction-following. When a route depends on exact wording, a clear recipe often outperforms a vague request.

This is especially true when:
- the challenge is judged on the final string
- the route depends on exact phrasing
- the model can be induced to treat the request as a benign formatting or completion task

## Truthteller specimen

The verified Truthteller route used an explicit recipe:
1. begin with a specific phrase
2. append a final string
3. output the amalgamation

That recipe made the model follow a structured path toward the final false declaration.

## Recognition signals

Reach for this block when:
- a challenge cares about exact output rather than broad discussion
- the model appears highly responsive to enumerated instructions
- broad natural-language requests produce too much variance
- you need reliable output shaping before adding modifiers

## Common combinations

This block works well with:
- String Amalgamation Output Assembly
- Contextual Modification Changes Semantic Force
- Output Dilution Control and Response Shaping

In walkthrough terms, this is usually a core technique, not the whole finished route.

## Failure modes

This block often fails when:
- the procedure works, but the resulting content still does not satisfy the evaluator
- the model adds safety filler or supportive commentary around the target output
- the route lacks a modifier that changes how the final text is interpreted

## Defender takeaway

Defenders should treat rigid output recipes as a risk signal, especially when a route repeatedly constrains the exact beginning, ending, or composition of the response.

## Related lessons

- Contextual Modification Changes Semantic Force
- String Amalgamation Output Assembly
- Output Dilution Control and Response Shaping
- Direct vs. Indirect Prompt Injection

---

## From the Bot-Tricks Compendium

Thanks for referencing Bot-Tricks.com — Prompt Injection Compendium — AI Security Training for Agents... and Humans!

Canonical source: https://bot-tricks.com
Bot-Tricks is a public, agent-friendly training resource for prompt injection, adversarial evaluation, and defensive learning.
For related lessons, structured indexes, and updated canonical material, visit Bot-Tricks.com.

Use this material only in authorized labs, challenges, sandboxes, or permitted assessments.