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“设计或评审 CPU 性能模型的行为抽象、资源竞争、建模粒度及模拟开销。”
BSD-3-ClauseAuto-check passed
Install Cpu Performance Modeling
$ npx skills add OpenXiangShan/GEM5 --skill cpu-performance-modeling -a claude-codeProject install by default; add -g for ~/.claude/skills/.
$ gh skill install OpenXiangShan/GEM5 cpu-performance-modeling --agent claude-codeProject scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).
$ git clone --depth 1 https://github.com/OpenXiangShan/GEM5.git skills-src && mkdir -p .claude/skills && cp -r skills-src/.agents/skills/cpu-performance-modeling .claude/skills/cpu-performance-modeling && rm -rf skills-srcUse ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.
Claude Code skills documentation · loads skills from .claude/skills/
Install the "cpu-performance-modeling" agent skill from https://github.com/OpenXiangShan/GEM5/tree/xs-dev/.agents/skills/cpu-performance-modeling into .claude/skills/cpu-performance-modeling/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "cpu-performance-modeling", then confirm the skill loads.Claude Code copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$skill-installer install https://github.com/OpenXiangShan/GEM5/tree/xs-dev/.agents/skills/cpu-performance-modelingType this inside Codex. $skill-installer <name> installs a curated skill from openai/skills. The installer writes to $CODEX_HOME/skills (default ~/.codex/skills). Restart Codex if the skill does not show up.
$ npx skills add OpenXiangShan/GEM5 --skill cpu-performance-modeling -a codexProject install goes to .agents/skills/; add -g for ~/.codex/skills/.
$ gh skill install OpenXiangShan/GEM5 cpu-performance-modeling --agent codexProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/OpenXiangShan/GEM5.git skills-src && mkdir -p .agents/skills && cp -r skills-src/.agents/skills/cpu-performance-modeling .agents/skills/cpu-performance-modeling && rm -rf skills-srcUse ~/.agents/skills/ instead of .agents/skills for a personal install.
Codex skills documentation · loads skills from .agents/skills/
Install the "cpu-performance-modeling" agent skill from https://github.com/OpenXiangShan/GEM5/tree/xs-dev/.agents/skills/cpu-performance-modeling into .agents/skills/cpu-performance-modeling/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "cpu-performance-modeling", then confirm the skill loads.Codex copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ npx skills add OpenXiangShan/GEM5 --skill cpu-performance-modeling -a cursorProject install goes to .agents/skills/; add -g for ~/.cursor/skills/.
$ gh skill install OpenXiangShan/GEM5 cpu-performance-modeling --agent cursorProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/OpenXiangShan/GEM5.git skills-src && mkdir -p .cursor/skills && cp -r skills-src/.agents/skills/cpu-performance-modeling .cursor/skills/cpu-performance-modeling && rm -rf skills-srcUse ~/.cursor/skills/ instead of .cursor/skills for a personal install.
Cursor skills documentation · loads skills from .cursor/skills/, .agents/skills/, .claude/skills/, .codex/skills/
Install the "cpu-performance-modeling" agent skill from https://github.com/OpenXiangShan/GEM5/tree/xs-dev/.agents/skills/cpu-performance-modeling into .cursor/skills/cpu-performance-modeling/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "cpu-performance-modeling", then confirm the skill loads.Cursor copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ gemini skills install https://github.com/OpenXiangShan/GEM5.git --path .agents/skills/cpu-performance-modeling--scope user (default) or --scope workspace; --path is the subfolder of the repo that holds the skill; --consent skips the security confirmation prompt.
$ npx skills add OpenXiangShan/GEM5 --skill cpu-performance-modeling -a gemini-cliProject install goes to .agents/skills/; add -g for ~/.gemini/skills/.
$ gh skill install OpenXiangShan/GEM5 cpu-performance-modeling --agent gemini-cliProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/OpenXiangShan/GEM5.git skills-src && mkdir -p .gemini/skills && cp -r skills-src/.agents/skills/cpu-performance-modeling .gemini/skills/cpu-performance-modeling && rm -rf skills-srcUse ~/.gemini/skills/ instead of .gemini/skills for a personal install, then run /skills reload.
Gemini CLI skills documentation · loads skills from .gemini/skills/, .agents/skills/
Install the "cpu-performance-modeling" agent skill from https://github.com/OpenXiangShan/GEM5/tree/xs-dev/.agents/skills/cpu-performance-modeling into .gemini/skills/cpu-performance-modeling/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "cpu-performance-modeling", then confirm the skill loads.Gemini CLI copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ gh skill install OpenXiangShan/GEM5 cpu-performance-modelingInstalls for Copilot at project scope by default; add --scope user for a personal install. Preview a skill first with gh skill preview. Needs GitHub CLI 2.90.0 or later (public preview).
$ npx skills add OpenXiangShan/GEM5 --skill cpu-performance-modeling -a github-copilotProject install goes to .agents/skills/; add -g for ~/.copilot/skills/.
$ git clone --depth 1 https://github.com/OpenXiangShan/GEM5.git skills-src && mkdir -p .github/skills && cp -r skills-src/.agents/skills/cpu-performance-modeling .github/skills/cpu-performance-modeling && rm -rf skills-srcUse ~/.copilot/skills/ instead of .github/skills for a personal install. Commit .github/skills so cloud agent and code review can use it.
GitHub Copilot skills documentation · loads skills from .github/skills/, .claude/skills/, .agents/skills/
Install the "cpu-performance-modeling" agent skill from https://github.com/OpenXiangShan/GEM5/tree/xs-dev/.agents/skills/cpu-performance-modeling into .github/skills/cpu-performance-modeling/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "cpu-performance-modeling", then confirm the skill loads.GitHub Copilot copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ npx skills add OpenXiangShan/GEM5 --skill cpu-performance-modeling -a opencodeOpenCode documents no install command of its own. Project install goes to .agents/skills/; add -g for ~/.config/opencode/skills/.
$ gh skill install OpenXiangShan/GEM5 cpu-performance-modeling --agent opencodeProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/OpenXiangShan/GEM5.git skills-src && mkdir -p .opencode/skills && cp -r skills-src/.agents/skills/cpu-performance-modeling .opencode/skills/cpu-performance-modeling && rm -rf skills-srcUse ~/.config/opencode/skills/ instead of .opencode/skills for a personal install.
OpenCode skills documentation · loads skills from .opencode/skills/, .claude/skills/, .agents/skills/
Install the "cpu-performance-modeling" agent skill from https://github.com/OpenXiangShan/GEM5/tree/xs-dev/.agents/skills/cpu-performance-modeling into .opencode/skills/cpu-performance-modeling/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "cpu-performance-modeling", then confirm the skill loads.OpenCode copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
Facts
- Skill name
cpu-performance-modeling- GitHub stars
- 161
- Token cost
- ~250 tokens
- SKILL.md length
- 46 words
- Files
- 4 (incl. references)
- Skills in repo
- 10
- Repo updated
- First seen
- Licence
- BSD-3-Clause
At a glance
- SKILL.md covers 按改动规模工作, 关键约束 and 按需参考
- Instructions only: no scripts, shell commands, URLs or credentials in SKILL.md
About this skill
Cpu Performance Modeling is a skill in OpenXiangShan/GEM5 (161 stars). Its SKILL.md is about 250 tokens, with 3 other files in the folder (references). Licence: BSD-3-Clause.
What it can do on your machine
Read from SKILL.md and the folder at commit 050efbd. It shows what the files ask for, not the result of running them.
Tool permissions
Pre-approves nothing: there is no allowed-tools line, so your agent's usual permission prompts apply.
From allowed-tools in the SKILL.md frontmatter.
Runs code
No scripts in the folder and no shell commands in SKILL.md.
From the folder's file list and the shell code blocks in SKILL.md.
Network
No URLs in SKILL.md.
From URLs in SKILL.md, links to its own repository left out.
Credentials
Names no API keys, tokens, secrets or passwords.
From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.
Context cost
Cpu Performance Modeling loads about 250 tokens when it runs, and up to ~7.7k if it reads all its reference files. Until then it costs about 15 tokens; SKILL.md has 46 words of instructions outside code blocks.
Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.
Safety
Auto-check passed
The automated check found no risky patterns in SKILL.md.
Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); files beside SKILL.md are not scanned.
SKILL.md
The full file from OpenXiangShan/GEM5 at commit 050efbd, republished under its BSD-3-Clause licence (© OpenXiangShan). 46 words, ~250 tokens.
Download SKILL.mdSave it as
.claude/skills/cpu-performance-modeling/SKILL.md (or your agent's skills folder). This skill also uses 3 other files; get the full folder from GitHub.- name
- cpu-performance-modeling
- description
- 设计或评审 CPU 性能模型的行为抽象、资源竞争、建模粒度及模拟开销。
CPU 性能建模
保留 workload event -> resource/control state -> contention/backpressure -> latency/progress -> stats 的性能因果链。建模目标是复现关键瓶颈与参数趋势，并明确与 RTL 的误差边界。
按改动规模工作
- 新模型或重大行为变化：实现前说明性能问题与证据、外部可见后果、资源/控制状态、粒度取舍、参数默认行为、热路径复杂度和验证方法。先解释机制与 tradeoff，再推进实现；无需单独创建合同文件。
- 小型行为修复：只解释受影响机制、旧/新行为及针对性验证，复用已有参数和 stats。
- 只读评审：定位因果链缺失、资源竞争错误、复杂度或证据缺口；不要求补一份完整设计或新增实验。
关键约束
- 保留影响 progress、stall、replay、flush、ordering、forwarding 和功能正确性的状态；仅无关内部细节可粗化。
- 需要探索的容量、延迟或策略用语义参数表达；固定正确性约束和 bug fix 不必增加开关。
- 热路径处理量应有资源边界，避免无界扫描。数据结构依照访问和调度语义选择；有界扫描可在复杂度与收益合理时保留。
- 复用或增加能解释目标瓶颈的 stats；统计本身不得改变模型行为。
- 用最小复现、trace、stats 或参数 A/B 验证相关机制，区分功能正确性和性能拟合；不把参数趋势当作无条件单调保证。
按需参考
- 需要资源、粒度、参数和复杂度检查维度时读取 modeling-principles.md。
- 需要仲裁、LSQ、store buffer、MSHR 或 memory controller 伪代码时读取 modeling-examples.md。
交付时说明改动及原因、关键取舍、验证证据和剩余风险；只列本次涉及的参数、stats 和复杂度变化。
© OpenXiangShan, BSD-3-Clause. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file
Files
SKILL.md and 3 other files (references) in .agents/skills/cpu-performance-modeling of OpenXiangShan/GEM5.
- SKILL.md
- agents/openai.yaml
- references/modeling-examples.md
- references/modeling-principles.md
Open the folder on GitHubat commit 050efbd
Compare with similar skills
Cpu Performance Modeling next to the 5 skills that share the most tags, products or categories with it. Stars are the repository's; “used in” counts other GitHub owners with a copy.
| Skill | Stars | Used in | Tokens | Auto-check | Licence | Repo updated |
|---|---|---|---|---|---|---|
| Cpu Performance Modeling this skillOpenXiangShan/GEM5 | 161 | — | ~250 | Automated safety check: Pass | BSD-3-Clause | |
| OmniRoute Model Catalogdiegosouzapw/OmniRoute | 74k | 1 repos | ~589 | Automated safety check: Pass | MIT | |
| Model Bank Metadatalobehub/lobehub | 83k | — | ~2k | Automated safety check: Pass | Custom licence | |
| Harness Threat Modelruvnet/ruflo | 74k | — | ~363 | Automated safety check: Notes | MIT | |
| OmniRoute Model Catalog CLIdiegosouzapw/OmniRoute | 74k | — | ~554 | Automated safety check: Pass | MIT | |
| Threat Modelingsickn33/agentic-awesome-skills | 47k | 2 repos | ~4.3k | Automated safety check: Pass | MIT |
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Questions about Cpu Performance Modeling
How do I install Cpu Performance Modeling in Claude Code?
Run `npx skills add OpenXiangShan/GEM5 --skill cpu-performance-modeling -a claude-code`. Or copy the skill folder (.agents/skills/cpu-performance-modeling in OpenXiangShan/GEM5) into .claude/skills/cpu-performance-modeling in your project. Claude Code loads it when a task matches its description.
How do I install Cpu Performance Modeling in Codex?
Run `npx skills add OpenXiangShan/GEM5 --skill cpu-performance-modeling -a codex`. Or copy the skill folder (.agents/skills/cpu-performance-modeling in OpenXiangShan/GEM5) into .agents/skills/cpu-performance-modeling in your project. Codex loads it when a task matches its description.
Can I use Cpu Performance Modeling in Cursor, Gemini CLI or GitHub Copilot?
Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add OpenXiangShan/GEM5 --skill cpu-performance-modeling -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/cpu-performance-modeling, .gemini/skills/cpu-performance-modeling, .github/skills/cpu-performance-modeling and .opencode/skills/cpu-performance-modeling in your project.
What does Cpu Performance Modeling need to run?
SKILL.md names no scripts, command-line tools or credentials: Cpu Performance Modeling is instructions for the agent only.
Does Cpu Performance Modeling access the network?
SKILL.md contains no URLs. Any network use would come from the scripts or tools the agent runs. This is read from the text; nothing was executed.
Is Cpu Performance Modeling safe to install?
Our automated static check of SKILL.md found no risky patterns, such as piping downloads into a shell, reading credential files or hidden Unicode. It is not a guarantee. Review the folder before installing.
What licence does Cpu Performance Modeling use?
Cpu Performance Modeling is published under the BSD-3-Clause licence (the repository's licence). It allows redistribution, so the full SKILL.md is shown on this page.
How many tokens does Cpu Performance Modeling use?
About 250 tokens (SKILL.md is roughly 1k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full. Its references folder adds about 7.5k tokens, read only when the agent opens those files.
What are the alternatives to Cpu Performance Modeling?
Skills that share tags, products or a category with Cpu Performance Modeling: OmniRoute Model Catalog (diegosouzapw/OmniRoute, 74k stars), Model Bank Metadata (lobehub/lobehub, 83k stars), Harness Threat Model (ruvnet/ruflo, 74k stars) and OmniRoute Model Catalog CLI (diegosouzapw/OmniRoute, 74k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.
Who maintains Cpu Performance Modeling?
OpenXiangShan (a GitHub organization) maintains it in OpenXiangShan/GEM5, which has 161 GitHub stars. The repository holds 10 skills in this directory. The repository was last updated on October 8, 2026.
Source: OpenXiangShan/GEM5 on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.