Prompt leverage
Strengthen a raw user prompt into an execution-ready instruction set for Amp, Claude Code, Codex, or another AI agent. Use when the user wants to improve an existing prompt, build a reusable prompting framework, wrap the current request with better structure, add clearer tool rules, or create a hook that upgrades prompts before execution.From its SKILL.md
npx -y skills add ReinaMacCredy/maestro --skill prompt-leverageAssembled from the repository path, not quoted from the project. Check it against their README if it does not work.
One thing to look at
- runs commandsInstructs the agent to run 1 command, including `maestro skill maestro:prompt-leverage`.
SKILL.md
0.7 KB, 80 tokens by cl100k_base, as published. Nobody here has run it
Prompt Leverage -- Redirect
This skill is maintained in the maestro built-in skills registry. Load the full version:
maestro skill maestro:prompt-leverage
The built-in version includes the framework blocks, provider-specific references (Anthropic Claude, OpenAI GPT), and output mode templates. Loading it from maestro ensures you always get the latest version.
What ships with it: 2 files
4.9 KB alongside SKILL.md, 1 of them executable
agents/
- openai.yaml305 B
scripts/
- augment_prompt.pyruns4.7 KB
Gives 0 of the 12 instructions most prompt engineering skills give in 80 tokens
Counted across 542 of the 575 authors here whose files we hold, read 2026-09-06
- Provide few-shot examples for complex tasksin 17 of 542, across 16 files
- Ask clarifying questions if information is ambiguousin 16 of 542, across 14 files
- Output a complete optimized prompt for the userin 15 of 542, across 9 files
- Validate structured outputs against schemasin 15 of 542, across 13 files
- Analyze the draft prompt for intent and gapsin 14 of 542, across 8 files
- Detect project tech stack from local filesin 14 of 542, across 8 files
- Recommend a model based on task scopein 13 of 542, across 7 files
- Present results in the specified output formatin 13 of 542, across 7 files
- Match intent and scope to ECC componentsin 13 of 542, across 7 files
- Ask one question at a timein 13 of 542, across 12 files
- Respond in the same language as the user inputin 12 of 542, across 6 files
- Ask up to three clarification questions if context is missingin 11 of 542, across 5 files
Said here and by no other author read
- Load the full version using maestro
- Use the built-in framework blocks
- Include provider-specific references
- Apply output mode templates
Grouped from the skills themselves: near-identical wordings counted once, and counted by distinct author, so one author publishing three of these counts once. Length counted with cl100k_base; the agent that loads this file may tokenize it differently.