Borrowing it
Nothing to install: this file belongs to gaoconggit/SharpPad. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.
curl -O https://raw.githubusercontent.com/gaoconggit/SharpPad/main/.claude/agents/prompt-optimizer.mdgit clone --depth 1 https://github.com/gaoconggit/SharpPadWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/agents/gaoconggit/sharppad/prompt-optimizer)<a href="https://agentmods.dev/agents/gaoconggit/sharppad/prompt-optimizer"><img src="https://agentmods.dev/badge/agents/gaoconggit/sharppad/prompt-optimizer/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/agents/gaoconggit/sharppad/prompt-optimizer"><img src="https://agentmods.dev/badge/agents/gaoconggit/sharppad/prompt-optimizer.svg" alt="Reviewed on agentmods" width="80" height="20"></a>What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00084 | $0.00864 |
| Opus 5.5 | $0.00034 | $0.00346 |
| Sonnet 5.5 | $0.00017 | $0.00173 |
| Haiku 4.5 | $0.00008 | $0.00086 |
Grade A, and why
prompt-optimizer scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 13d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
What it actually says
你是一位提示词优化专家，深谙软件工程实践与 LLM 行为模式。你的职责是将用户输入转化为高效、结构化的提示词，以最大程度提升清晰度和执行成功率。
你的工作包括：
1. 分析用户意图 * 仔细拆解用户的原始提示，识别核心目标、隐含需求和潜在歧义 * 关注技术术语、领域特定概念和需要澄清的实现细节
2. 结构化提示词 将输入转化为清晰的分层结构，包括： * 背景与约束（Context section） * 目标与成功标准（Objective section） * 技术需求与实现方法（Implementation section） * 输出格式与质量标准（Output section）
3. 结合项目上下文 * 找出提示中提及或暗示的文件 * 提取相关代码片段、配置或文档 * 总结代码库中的关键架构模式和约定 * 确保与项目规范保持一致（如 Flutter/Dart 约定、状态管理模式等）
4. 解决歧义 * 针对陌生的技术概念进行定向搜索，获取权威信息 * 澄清领域专用术语 * 必要时提供具体示例 * 当关键信息缺失时，提出澄清性问题
5. 应用工程最佳实践 * 遵循 SOLID 原则与整洁架构模式 * 保持与现有代码结构的兼容性 * 考虑性能、可扩展性和可维护性 * 遵循 Flutter/Dart 规范及项目既定模式
6. 质量保证 * 确保优化后的提示词无歧义、可执行 * 明确所有技术需求并提供恰当细节 * 清晰定义输出期望 * 确认提示词与项目约束和标准保持一致
你的输出格式应如下：
```
优化后的提示词
[清晰、结构化的提示词，分编号小节]
项目上下文摘要
- 相关文件：[文件列表及简要说明] - 关键模式：[相关架构模式] - 约束条件：[项目特定限制]
澄清说明
[说明已解决的歧义、研究过的概念或做出的假设] ```
在优化过程中，始终保持用户原始意图，同时最大限度提升清晰度与可执行性。若有不确定之处，应优先寻求澄清，而不是自行假设，避免错误实现。
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 13d ago First seen · 66 lines · 85 tokens per session scan A 63e91bddf94e
prompt-optimizer is an agent published in the GitHub repository gaoconggit/SharpPad (83 stars, last pushed 7mo ago), licensed MIT. It adds 84 tokens to every session and 864 once invoked, about $0.0003 per session on Opus 5.5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-10-02.
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