Prompt Leverage

Prefix your first line with 🥷 inline. Be direct: upgraded prompt early. No filler.

Defer To Instead

• create-skill — creating new skills from scratch
• interview — extracting requirements before prompt engineering
• brainstorm — comparing multiple prompting approaches

1. Read the raw prompt and identify the real job to be done.
2. Infer the task type: coding, research, writing, analysis, planning, or review.
3. Rebuild the prompt with the framework blocks in references/framework.md.
4. Keep the result proportional: do not over-specify a simple task.
5. Return both the improved prompt and a short explanation of what changed when useful.

Transformation Rules

• Preserve the user's objective, constraints, and tone unless they conflict.
• Prefer adding missing structure over rewriting everything stylistically.
• Add context requirements only when they improve correctness.
• Add tool rules only when tool use materially affects correctness.
• Add verification and completion criteria for non-trivial tasks.
• Keep prompts compact enough to be practical in repeated use.

Framework Blocks

Use these blocks selectively:

• Objective: state the task and what success looks like.
• Context: list sources, files, constraints, and unknowns.
• Work Style: set depth, breadth, care, and first-principles expectations.
• Tool Rules: state when tools, browsing, or file inspection are required.
• Output Contract: define structure, formatting, and level of detail.
• Verification: require checks for correctness, edge cases, and better alternatives.
• Done Criteria: define when the agent should stop.

Output Modes

Choose one mode based on the user request:

• Inline upgrade: provide the upgraded prompt only.
• Upgrade + rationale: provide the prompt plus a brief list of improvements.
• Template extraction: convert the prompt into a reusable fill-in-the-blank template.
• Hook spec: explain how to apply the framework automatically before execution.

Hook Pattern

When the user asks for a hook, model it as a pre-processing layer:

1. Accept the current prompt.
2. Classify the task and risk level.
3. Expand the prompt using the framework blocks.
4. Return the upgraded prompt for execution.
5. Optionally keep a diff or summary of injected structure.

Use scripts/augment_prompt.py when a deterministic first-pass rewrite is helpful.

Quality Bar

Before finalizing, check the upgraded prompt:

• still matches the original intent
• does not add unnecessary ceremony
• includes the right verification level for the task
• gives the agent a clear definition of done
• sounds materially more executable than the original, not merely more verbose

If the prompt is already strong, say so and make only minimal edits.

Output Format

Inline mode: Return upgraded prompt directly in response.

Template mode: Save to: .kit/reports/prompts/{YYYYMMDD}-{slug}.md

Frontmatter:

---
title: Prompt Template - {slug}
description: {one-line summary}
status: active
created: YYYY-MM-DD
tags: [prompt, template]
---

Include:

• Original prompt
• Upgraded prompt
• Changes made (diff or list)
• Framework blocks applied
• Usage instructions

Anti-Patterns

• Over-specifying a simple prompt with unnecessary framework blocks — ceremony without value; match structure to task complexity
• Changing the user's intent while "improving" structure — the upgraded prompt must still do the same job
• Adding verification blocks to trivial tasks — busywork that trains the user to ignore gates

Load from {baseDir}/scripts/:

• augment_prompt.py — Deterministic first-pass rewrite script

Examples

Example 1: Inline Enhancement

Input: "Make the code better" Output: Add target files, concrete focus areas, and verification criteria.

Example 2: Template Mode

Input: "Create code review template" Output: Template with Security, Performance, Architecture, and severity sections.

Example 3: Multi-turn Optimization

Input: "Optimize this conversation" Output: Adds context summary, previous decisions, and key facts list.