Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx skills add zhaixin244-wq/fnw --skill chip-ppa-formattergit clone --depth 1 https://github.com/zhaixin244-wq/fnwWrote 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/skills/zhaixin244-wq/fnw/chip-ppa-formatter)<a href="https://agentmods.dev/skills/zhaixin244-wq/fnw/chip-ppa-formatter"><img src="https://agentmods.dev/badge/skills/zhaixin244-wq/fnw/chip-ppa-formatter/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/skills/zhaixin244-wq/fnw/chip-ppa-formatter"><img src="https://agentmods.dev/badge/skills/zhaixin244-wq/fnw/chip-ppa-formatter.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 | $0.00061 | $0.00818 |
| Opus 5 | $0.00030 | $0.00409 |
| Sonnet 5 | $0.00012 | $0.00164 |
| Haiku 4.5 | $0.00006 | $0.00082 |
Grade A, and why
chip-ppa-formatter 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 11d 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
Chip PPA Formatter
任务
以结构化、可量化的方式输出 PPA 规格。
执行步骤
- 从用户输入或架构描述中提取四类指标：
- Performance：Latency、Throughput、Frequency、Bandwidth
- Power：Dynamic Power、Leakage Power、Energy/Op
- Area：Gate Count、SRAM Size、Physical Area (mm²)
- Quality：SNR、BER、覆盖率（验证）
- 统一单位并标注工艺节点与 PVT 角（如 TT/0.85V/25°C）。
- 区分 Target（目标值）、Budget（预算值）、Estimated（估算值）。
- 对每项指标给出约束表达式（如
Latency ≤ 10 cycles @ 1GHz）。 - 如需对比多方案，以表格形式列出各方案的 PPA 得分与帕累托优势。
输出格式
### PPA 规格表（工艺：Xnm | PVT：TT/0.85V/25°C）
| 指标类别 | 指标名 | 数值 | 单位 | 约束类型 | 备注 |
|----------|--------|------|------|----------|------|
| Performance | 处理延迟 | ≤ 10 | cycles | Target | @ 1GHz |
| Power | 动态功耗 | < 10 | mW/GHz | Budget | 典型工况 |
| Area | 门数 | ~ 150 | kGates | Estimated | 含扫描链 |
使用示例
示例 1：格式化 PPA 目标
用户：帮我格式化 data_adpt 的 PPA 规格，工艺 28nm，目标延迟 10 cycles @ 1GHz，面积 150kGates，功耗 15mW
预期行为：
- 提取指标，统一单位
- 区分 Target/Budget/Estimated
- 输出标准 PPA 表格（含约束表达式和 PVT 角）
示例 2：多方案 PPA 对比
用户：对比方案 A（3级流水线）和方案 B（5级流水线）的 PPA
预期行为：生成对比表，标注帕累托优势，建议用 DSE Skill 进一步分析
异常处理
| 场景 | 触发条件 | 处理动作 |
|---|---|---|
| 指标缺失 | 用户只提供了部分 PPA | 列出缺失项，标注"待补充"，输出已有部分 |
| 单位不一致 | 混用 mW/W、Gates/kGates | 自动统一单位，在备注中标注原始值 |
| 工艺节点未知 | 未指定 PVT 角 | 使用典型值（TT/0.85V/25°C），标注"假设条件" |
| 多方案对比 | 有 2+ 个方案 | 生成对比表 + 帕累托标注，建议用 DSE Skill 进一步分析 |
检查点
- 格式化前：展示提取到的原始指标列表，确认无遗漏
- 格式化后：展示最终 PPA 表格，确认单位和约束类型正确
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.
- 11d ago First seen · 63 lines · 61 tokens per session scan A 1aee08503166
chip-ppa-formatter is a skill published in the GitHub repository zhaixin244-wq/fnw (29 stars, last pushed 3mo ago), licensed MIT. It adds 61 tokens to every session and 818 once invoked, about $0.0003 per session on Opus 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 2026-08-30.
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