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elvismdev/claude-wordpress-skills
WordPress performance code review and optimization analysis.
Agent skill
Sigcomm Artifact Evaluation
by brycewang-stanford in brycewang-stanford/Awesome-Journal-Skills
A skill your agent uses when packaging an ACM SIGCOMM paper's code, traces, topologies, and configuration for the artifact-evaluation committee — choosing ACM badges (Artifacts Available, Evaluated…
Install Sigcomm Artifact Evaluation
$ npx skills add brycewang-stanford/Awesome-Journal-Skills --skill sigcomm-artifact-evaluation -a claude-codeProject install by default; add -g for ~/.claude/skills/.
$ gh skill install brycewang-stanford/Awesome-Journal-Skills sigcomm-artifact-evaluation --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/brycewang-stanford/Awesome-Journal-Skills.git skills-src && mkdir -p .claude/skills && cp -r skills-src/SIGCOMM-Skills/skills/sigcomm-artifact-evaluation .claude/skills/sigcomm-artifact-evaluation && 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 "sigcomm-artifact-evaluation" agent skill from https://github.com/brycewang-stanford/Awesome-Journal-Skills/tree/main/SIGCOMM-Skills/skills/sigcomm-artifact-evaluation into .claude/skills/sigcomm-artifact-evaluation/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "sigcomm-artifact-evaluation", 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/brycewang-stanford/Awesome-Journal-Skills/tree/main/SIGCOMM-Skills/skills/sigcomm-artifact-evaluationType 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 brycewang-stanford/Awesome-Journal-Skills --skill sigcomm-artifact-evaluation -a codexProject install goes to .agents/skills/; add -g for ~/.codex/skills/.
$ gh skill install brycewang-stanford/Awesome-Journal-Skills sigcomm-artifact-evaluation --agent codexProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/brycewang-stanford/Awesome-Journal-Skills.git skills-src && mkdir -p .agents/skills && cp -r skills-src/SIGCOMM-Skills/skills/sigcomm-artifact-evaluation .agents/skills/sigcomm-artifact-evaluation && rm -rf skills-srcUse ~/.agents/skills/ instead of .agents/skills for a personal install.
Codex skills documentation · loads skills from .agents/skills/
Install the "sigcomm-artifact-evaluation" agent skill from https://github.com/brycewang-stanford/Awesome-Journal-Skills/tree/main/SIGCOMM-Skills/skills/sigcomm-artifact-evaluation into .agents/skills/sigcomm-artifact-evaluation/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "sigcomm-artifact-evaluation", 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 brycewang-stanford/Awesome-Journal-Skills --skill sigcomm-artifact-evaluation -a cursorProject install goes to .agents/skills/; add -g for ~/.cursor/skills/.
$ gh skill install brycewang-stanford/Awesome-Journal-Skills sigcomm-artifact-evaluation --agent cursorProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/brycewang-stanford/Awesome-Journal-Skills.git skills-src && mkdir -p .cursor/skills && cp -r skills-src/SIGCOMM-Skills/skills/sigcomm-artifact-evaluation .cursor/skills/sigcomm-artifact-evaluation && 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 "sigcomm-artifact-evaluation" agent skill from https://github.com/brycewang-stanford/Awesome-Journal-Skills/tree/main/SIGCOMM-Skills/skills/sigcomm-artifact-evaluation into .cursor/skills/sigcomm-artifact-evaluation/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "sigcomm-artifact-evaluation", 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/brycewang-stanford/Awesome-Journal-Skills.git --path SIGCOMM-Skills/skills/sigcomm-artifact-evaluation--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 brycewang-stanford/Awesome-Journal-Skills --skill sigcomm-artifact-evaluation -a gemini-cliProject install goes to .agents/skills/; add -g for ~/.gemini/skills/.
$ gh skill install brycewang-stanford/Awesome-Journal-Skills sigcomm-artifact-evaluation --agent gemini-cliProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/brycewang-stanford/Awesome-Journal-Skills.git skills-src && mkdir -p .gemini/skills && cp -r skills-src/SIGCOMM-Skills/skills/sigcomm-artifact-evaluation .gemini/skills/sigcomm-artifact-evaluation && 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 "sigcomm-artifact-evaluation" agent skill from https://github.com/brycewang-stanford/Awesome-Journal-Skills/tree/main/SIGCOMM-Skills/skills/sigcomm-artifact-evaluation into .gemini/skills/sigcomm-artifact-evaluation/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "sigcomm-artifact-evaluation", 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 brycewang-stanford/Awesome-Journal-Skills sigcomm-artifact-evaluationInstalls 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 brycewang-stanford/Awesome-Journal-Skills --skill sigcomm-artifact-evaluation -a github-copilotProject install goes to .agents/skills/; add -g for ~/.copilot/skills/.
$ git clone --depth 1 https://github.com/brycewang-stanford/Awesome-Journal-Skills.git skills-src && mkdir -p .github/skills && cp -r skills-src/SIGCOMM-Skills/skills/sigcomm-artifact-evaluation .github/skills/sigcomm-artifact-evaluation && 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 "sigcomm-artifact-evaluation" agent skill from https://github.com/brycewang-stanford/Awesome-Journal-Skills/tree/main/SIGCOMM-Skills/skills/sigcomm-artifact-evaluation into .github/skills/sigcomm-artifact-evaluation/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "sigcomm-artifact-evaluation", 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 brycewang-stanford/Awesome-Journal-Skills --skill sigcomm-artifact-evaluation -a opencodeOpenCode documents no install command of its own. Project install goes to .agents/skills/; add -g for ~/.config/opencode/skills/.
$ gh skill install brycewang-stanford/Awesome-Journal-Skills sigcomm-artifact-evaluation --agent opencodeProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/brycewang-stanford/Awesome-Journal-Skills.git skills-src && mkdir -p .opencode/skills && cp -r skills-src/SIGCOMM-Skills/skills/sigcomm-artifact-evaluation .opencode/skills/sigcomm-artifact-evaluation && 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 "sigcomm-artifact-evaluation" agent skill from https://github.com/brycewang-stanford/Awesome-Journal-Skills/tree/main/SIGCOMM-Skills/skills/sigcomm-artifact-evaluation into .opencode/skills/sigcomm-artifact-evaluation/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "sigcomm-artifact-evaluation", 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
sigcomm-artifact-evaluation- GitHub stars
- 1.2k
- Token cost
- ~1.1k tokens
- SKILL.md length
- 425 words
- Files
- 1
- Skills in repo
- 2,387
- Repo updated
- First seen
- Licence
- MIT
At a glance
A skill your agent uses when packaging an ACM SIGCOMM paper's code, traces, topologies, and configuration for the artifact-evaluation committee — choosing ACM badges (Artifacts Available, Evaluated…
- Packaging an ACM SIGCOMM papers code
- SKILL.md covers Badge selection is claim…, The networking-specific hard…, What evaluators open first and Vignette: packaging a…, plus 1 more section
- Instructions only: no scripts, shell commands, URLs or credentials in SKILL.md
- Configuration for the artifact-evaluation committee — choosing ACM badges (Artifacts Available
What it does
Sigcomm Artifact Evaluation is an agent skill from brycewang-stanford/Awesome-Journal-Skills. Use when packaging an ACM SIGCOMM paper's code, traces, topologies, and configuration for the artifact-evaluation committee — choosing ACM badges (Artifacts Available, Evaluated, Results Reproduced) as claim calibration, building downscaled topologies and trace substitutes, and making a networking testbed result rebuildable by a reviewer.
Its SKILL.md is about 1.1k tokens, which your agent loads only when the skill is triggered. It is a single SKILL.md file with no bundled scripts.
It sits in Business, Finance & HR, covering Performance reviews. The repository describes itself as: Journal-specific Claude Code/Codex skill packs covering mainstream journals — AER, QJE, Nature, Cell, 管理世界, 经济研究 & 200+ more — your fast track to getting published. ｜ 覆盖主流期刊的… The licence is MIT.
When your agent uses it
- Packaging an ACM SIGCOMM papers code
- Configuration for the artifact-evaluation committee — choosing ACM badges (Artifacts Available
- Results Reproduced) as claim calibration
- Building downscaled topologies and trace substitutes
Example prompts
- “/sigcomm-artifact-evaluation”
What it can do on your machine
Read from SKILL.md and the folder at commit 932eb23. 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
Sigcomm Artifact Evaluation loads about 1.1k tokens when it runs. Until then it costs about 92 tokens; SKILL.md has 425 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 brycewang-stanford/Awesome-Journal-Skills at commit 932eb23, republished under its MIT licence (© brycewang-stanford). 425 words, ~1,050 tokens.
Download SKILL.mdSave it as
.claude/skills/sigcomm-artifact-evaluation/SKILL.md (or your agent's skills folder).- name
- sigcomm-artifact-evaluation
- description
- Use when packaging an ACM SIGCOMM paper's code, traces, topologies, and configuration for the artifact-evaluation committee — choosing ACM badges (Artifacts Available, Evaluated, Results Reproduced) as claim calibration, building downscaled topologies and trace substitutes, and making a networking testbed result rebuildable by a reviewer.
SIGCOMM Artifact Evaluation
Use this for the post-acceptance artifact submission. SIGCOMM helped establish artifact evaluation in networking, and the venue's "runnable papers" culture sets a high bar: a committee attempts to build and, where a badge requires it, reproduce your headline result. Reopen the current Call for Artifacts for this edition's exact badge set and dates (待核实 for 2026).
Badge selection is claim calibration
Choose the badges you can honestly support; the badge is a promise about what a stranger can verify, not a participation ribbon.
| ACM badge | What it promises | What the AEC will do |
|---|---|---|
| Artifacts Available | Permanent public retrieval via an archival DOI | Confirm the archive resolves and is complete |
| Artifacts Evaluated (Functional) | The artifact builds and runs as documented | Follow your README end to end on their setup |
| Results Reproduced | The paper's main results follow from the artifact | Re-run to obtain the headline numbers within tolerance |
Aim the highest badge at the result you most want believed, and be candid where hardware or scale makes full reproduction infeasible.
The networking-specific hard part
Generic artifact tooling cannot judge what SIGCOMM evaluators care about most: a result measured on a rack of switches or a wide-area testbed rarely rebuilds on a laptop. Plan for the gap:
- Downscale the topology. Ship a small emulated or Mininet-style topology that reproduces the mechanism's behavior, with a documented map from the downscaled run to the paper's full-scale figure.
- Substitute the trace legally. If the production trace cannot ship, provide a synthetic or public-trace substitute with the same statistical character, and state exactly which figures used which input.
- Pin the environment. Kernel and NIC features, switch firmware or programmable-data-plane toolchain versions, and clock/timestamp sources all move results; record them.
- Expose the run count. Every reported percentile needs its replication count and the seed or workload driver, or the tail cannot be reproduced.
Show full SKILL.md (117 more words)Show less
What evaluators open first
artifact/
README # 5-minute smoke run FIRST, then the full path
smoke/ # one command -> one small figure that proves it runs
topology/ # downscaled + a map to the paper's full-scale setup
traces/ # substitute inputs + provenance + which-figure-uses-what
configs/ # exact parameters per experiment
scripts/ # regenerate each figure from logged results
results/ # logged raw outputs the plots are built from
ENVIRONMENT.md # kernel/NIC/switch/toolchain versions, hardwareAssume the evaluator runs the smoke path first and stops if it fails, so make one command produce one convincing small figure before anything else is polished.
Vignette: packaging a data-center transport result
A paper reports a tail-FCT win on a 128-server testbed. Turnkey plan: a Mininet topology that reproduces the incast dynamic at small scale; a synthetic RPC workload matching the trace's flow-size distribution; a driver that emits the FCT distribution over 20 replays; and a script that plots the 99th percentile directly from logged results so the artifact figure and the paper figure cannot diverge. The README states plainly which numbers are full-scale (paper) and which are downscaled (artifact).
Output format
[Badges sought] available / functional / reproduced — each justified
[Smoke path] one command -> one figure? yes/no
[Topology] full-scale -> downscaled map documented
[Trace handling] shipped / substituted (+ provenance) / described
[Environment] kernel/NIC/switch/toolchain pinned
[Fixes before AEC upload] <ordered list>© brycewang-stanford, MIT. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file
Files
Just SKILL.md in SIGCOMM-Skills/skills/sigcomm-artifact-evaluation of brycewang-stanford/Awesome-Journal-Skills.
Open the folder on GitHubat commit 932eb23
Compare with similar skills
Sigcomm Artifact Evaluation 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 |
|---|---|---|---|---|---|---|
| Sigcomm Artifact Evaluation this skillbrycewang-stanford/Awesome-Journal-Skills | 1.2k | — | ~1.1k | Automated safety check: Pass | MIT | |
| Wp Performance Reviewelvismdev/claude-wordpress-skills | 235 | 1 repos | ~4.5k | Automated safety check: Pass | MIT | |
| Align Humanagentscope-ai/OpenJudge | 871 | — | ~3.1k | Automated safety check: Pass | Apache-2.0 | |
| Run Mv Hoi Reconstructionnvidia-isaac/video_to_data | 861 | — | ~1.5k | Automated safety check: Pass | Custom licence | |
| Company Analysiszhu1090093659/dsh-trading | 236 | — | ~4.2k | Automated safety check: Pass | Custom licence | |
| Windbg Diagnostic Methodmicrosoft/win-dev-skills | 466 | — | ~1.9k | Automated safety check: Pass | MIT |
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Questions about Sigcomm Artifact Evaluation
What does Sigcomm Artifact Evaluation do?
A skill your agent uses when packaging an ACM SIGCOMM paper's code, traces, topologies, and configuration for the artifact-evaluation committee — choosing ACM badges (Artifacts Available, Evaluated…. Sigcomm Artifact Evaluation is an agent skill from brycewang-stanford/Awesome-Journal-Skills. Use when packaging an ACM SIGCOMM paper's code, traces, topologies, and configuration for the artifact-evaluation committee — choosing ACM badges (Artifacts Available, Evaluated, Results Reproduced) as claim calibration, building downscaled topologies and trace substitutes, and making a networking testbed result rebuildable by a reviewer.
When should I use Sigcomm Artifact Evaluation?
Sigcomm Artifact Evaluation fits situations like: packaging an ACM SIGCOMM papers code; configuration for the artifact-evaluation committee — choosing ACM badges (Artifacts Available; results Reproduced) as claim calibration; building downscaled topologies and trace substitutes.
How do I install Sigcomm Artifact Evaluation in Claude Code?
Run `npx skills add brycewang-stanford/Awesome-Journal-Skills --skill sigcomm-artifact-evaluation -a claude-code`. Or copy the skill folder (SIGCOMM-Skills/skills/sigcomm-artifact-evaluation in brycewang-stanford/Awesome-Journal-Skills) into .claude/skills/sigcomm-artifact-evaluation in your project. Claude Code loads it when a task matches its description.
How do I install Sigcomm Artifact Evaluation in Codex?
Run `npx skills add brycewang-stanford/Awesome-Journal-Skills --skill sigcomm-artifact-evaluation -a codex`. Or copy the skill folder (SIGCOMM-Skills/skills/sigcomm-artifact-evaluation in brycewang-stanford/Awesome-Journal-Skills) into .agents/skills/sigcomm-artifact-evaluation in your project. Codex loads it when a task matches its description.
Can I use Sigcomm Artifact Evaluation 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 brycewang-stanford/Awesome-Journal-Skills --skill sigcomm-artifact-evaluation -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/sigcomm-artifact-evaluation, .gemini/skills/sigcomm-artifact-evaluation, .github/skills/sigcomm-artifact-evaluation and .opencode/skills/sigcomm-artifact-evaluation in your project.
What does Sigcomm Artifact Evaluation need to run?
SKILL.md names no scripts, command-line tools or credentials: Sigcomm Artifact Evaluation is instructions for the agent only.
Does Sigcomm Artifact Evaluation 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 Sigcomm Artifact Evaluation 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 Sigcomm Artifact Evaluation use?
Sigcomm Artifact Evaluation is published under the MIT licence (the repository's licence). It allows redistribution, so the full SKILL.md is shown on this page.
How many tokens does Sigcomm Artifact Evaluation use?
About 1.1k tokens (SKILL.md is roughly 4.2k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full.
What are the alternatives to Sigcomm Artifact Evaluation?
Skills that share tags, products or a category with Sigcomm Artifact Evaluation: Wp Performance Review (elvismdev/claude-wordpress-skills, 235 stars), Align Human (agentscope-ai/OpenJudge, 871 stars), Run Mv Hoi Reconstruction (nvidia-isaac/video_to_data, 861 stars) and Company Analysis (zhu1090093659/dsh-trading, 236 stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.
Who maintains Sigcomm Artifact Evaluation?
brycewang-stanford (a GitHub user) maintains it in brycewang-stanford/Awesome-Journal-Skills, which has 1,231 GitHub stars. The repository holds 2,387 skills in this directory. The repository was last updated on September 27, 2026.
Source: brycewang-stanford/Awesome-Journal-Skills on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.