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-spyglass-rdc-chkgit 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-spyglass-rdc-chk)<a href="https://agentmods.dev/skills/zhaixin244-wq/fnw/chip-spyglass-rdc-chk"><img src="https://agentmods.dev/badge/skills/zhaixin244-wq/fnw/chip-spyglass-rdc-chk/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-spyglass-rdc-chk"><img src="https://agentmods.dev/badge/skills/zhaixin244-wq/fnw/chip-spyglass-rdc-chk.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 | $0.00078 | $0.02220 |
| Opus 5 | $0.00039 | $0.01110 |
| Sonnet 5 | $0.00016 | $0.00444 |
| Haiku 4.5 | $0.00008 | $0.00222 |
Grade A, and why
chip-spyglass-rdc-chk 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 9d 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.
How it starts
The opening of the file, as written. The whole thing — 225 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Chip SpyGlass RDC Checker
使用 SpyGlass 工具对 RTL 执行 RDC（Reset Domain Crossing）检查。
When to Use
- 多复位域设计的 RTL 完成后
- 需要验证跨复位域信号是否正确处理
- RDC 签核（sign-off）前的检查
- 子模块交付前的 RDC 验证
- CDC 检查完成后，补充 RDC 检查
工具路径
| 工具 | 路径 |
|---|---|
| SpyGlass | 系统 PATH（需安装 Synopsys SpyGlass） |
目录约定
| 项目 | 路径 |
|---|---|
| RDC 脚本 | {module}_work/ds/run/run_rdc.sh |
| RDC 约束 | {module}_work/ds/run/{module}.rdc.tcl |
| 报告目录 | {module}_work/ds/report/rdc/ |
| Waiver 文件 | {module}_work/ds/run/{module}.rdc.waiver |
| 模板目录 | .claude/skills/chip-spyglass-rdc-chk/templates/ |
核心工作流
Phase 0: 输入确认
├─ 确认顶层模块名和 RTL 文件列表
├─ 确认复位域信息（来自 FS/微架构文档）
├─ 确认复位释放顺序
└─ 确认 Black Box 模块列表
Phase 1: 生成 RDC 约束
├─ 基于复位域信息生成 reset 定义
├─ 生成 set_rdc_define_assertion_sequence（复位释放顺序）
├─ 生成 set_reset_groups（复位分组）
├─ 生成 rdc_qualifier（阻断信号）
└─ 复用 CDC 的时钟/常量/准静态约束
Phase 2: 执行 RDC Setup
├─ 运行 rdc_setup Goal
├─ 检查复位定义完整性
└─ 修复所有 Setup Error
Phase 3: 执行 RDC Verify
├─ 运行 rdc_verify（亚稳态检查）
├─ 运行 rdc_verify_corrupt（数据损坏检查）
└─ 按优先级分类违例
Phase 4: 报告汇总
├─ 生成 rdc_summary.log
└─ 输出违例分类统计
Phase 0：输入确认
-
从微架构文档或用户指定提取：
- 顶层模块名
- RTL 文件列表
- 复位域信息（复位名、极性、同步/异步、所属功耗域）
- 复位释放顺序（哪个复位先释放、哪个后释放）
- 复位分组（哪些复位属于同一组）
- RDC Qualifier 信号列表（阻断 RDC 路径的信号）
- Black Box 模块列表
-
用
Glob验证 RTL 文件存在 -
检查是否已有 CDC 约束（SGDC），RDC 可复用时钟/常量/准静态约束
Phase 1：生成 RDC 约束
根据输入信息生成 {module}.rdc.tcl，参考模板 templates/template_rdc_setup.sh。
RDC 约束必须包含
# 1. 复用 CDC 约束（时钟/复位/常量/准静态）
source {module}.sgdc
# 2. RDC 复位定义
create_reset -name rst_n -active_low -async
create_reset -name rst_sw -active_high -sync
# 3. 复位释放顺序（最重要）
set_rdc_define_assertion_sequence \
-from_reset {rst_sw} \
-to_reset {rst_n}
# 4. 复位分组
set_reset_groups -name grp_por -group {rst_n}
set_reset_groups -name grp_func -group {rst_sw rst_dbg}
# 5. RDC Qualifier（阻断信号）
rdc_qualifier -signal cfg_rdc_gate -value 1
# 6. Scenario-Based（降噪）
configure_rdc_scenario -name func_mode \
-active_resets {rst_sw rst_dbg} \
-inactive_resets {rst_n}
# 7. Reset-less Flop 处理
configure_rdc_corrupt -skip_resetless_flops true
What ships with it
3 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
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.
- 9d ago First seen · 225 lines · 78 tokens per session scan A fd2fdbbdb542
chip-spyglass-rdc-chk is a skill published in the GitHub repository zhaixin244-wq/fnw (29 stars, last pushed 3mo ago), licensed MIT. It adds 78 tokens to every session and 2,220 once invoked, about $0.0004 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 2026-09-03.
Other skills, from other repositories
gke-ai-troubleshooting-tpu-dynamic-slices-monitoring
Monitors, troubleshoots, and manages GKE TPU Dynamic Slices custom resources. Use when checking TPU slice lifecycle states, troubleshooting slice provisioning failures, validating single-slice or multi-slice (JobSet) workload manifests, or safely patching stuck finalizers and disabling the slice controller. Don't use…
gke-ai-troubleshooting-tpu-vbar-oom
Diagnoses and prevents vbarcontrolagent segfaults, out-of-memory (OOM) errors, and TPU device initialization failures on TPU v6e nodes in GKE caused by race conditions during TPU device resets or high-frequency metrics polling. Use when troubleshooting vbarcontrolagent crashes, memory cgroup OOMs in serial console…
competition-firmware-layout
Internal downstream skill for ctf-sandbox-orchestrator. CTF-sandbox workflow for firmware images, partition tables, boot chains, update packages, extracted filesystems, embedded configs, and device-facing trust boundaries. Use when the user asks to unpack firmware, map partition layout, inspect bootloader or init…
doca-flow
Build and debug DOCA Flow applications on supported NVIDIA NICs/DPUs: define match/action pipes, initialize ports and representors, choose forwarding targets, validate pipes before hardware programming, read counters, match the Flow version to the installed DOCA release, and diagnose Flow API errors. Trigger on DOCA…
diagnose-driver-install
Diagnose NVIDIA driver installation failures on DeepOps-managed nodes — nvidia-smi errors, "No devices were found", DKMS build failures, or GPU pods crash-looping. Use before reinstalling anything.
catc-troubleshoot
Catalyst Center troubleshooting workflows - device unreachable investigation, client connectivity issues, interface down analysis, site-wide outage triage, wireless roaming problems, integration with pyATS for CLI-level diagnostics. Use when a device is unreachable, a user reports connectivity problems, an interface…