| name | prompt-leverage |
| description | Upgrade raw prompts into execution-ready instructions. Use when asked to improve a prompt, add context, tool, verification, or done rules, extract a template, or design an enhancement hook. |
Prompt Leverage
Turn the user's current prompt into a stronger working prompt without changing the underlying intent. Preserve the task, fill in missing execution structure, and add only enough scaffolding to improve reliability.
Workflow
- Read the raw prompt and identify the real job to be done.
- Infer the task type: coding, research, writing, analysis, planning, or review.
- Rebuild the prompt with the framework blocks in
references/framework.md.
- Keep the result proportional: do not over-specify a simple task.
- 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:
- Accept the current prompt.
- Classify the task and risk level.
- Expand the prompt using the framework blocks.
- Return the upgraded prompt for execution.
- 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
If the prompt is already strong, say so and make only minimal edits.
