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Agent skill
Sigmetrics Topic Selection
by brycewang-stanford in brycewang-stanford/Awesome-Journal-Skills
A skill your agent uses when deciding whether a computer-systems performance project belongs at ACM SIGMETRICS or should be routed to IMC, SIGCOMM/NSDI/OSDI, INFOCOM, a learning venue…
MITAuto-check passed
Install Sigmetrics Topic Selection
$ npx skills add brycewang-stanford/Awesome-Journal-Skills --skill sigmetrics-topic-selection -a claude-codeProject install by default; add -g for ~/.claude/skills/.
$ gh skill install brycewang-stanford/Awesome-Journal-Skills sigmetrics-topic-selection --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/SIGMETRICS-Skills/skills/sigmetrics-topic-selection .claude/skills/sigmetrics-topic-selection && 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 "sigmetrics-topic-selection" agent skill from https://github.com/brycewang-stanford/Awesome-Journal-Skills/tree/main/SIGMETRICS-Skills/skills/sigmetrics-topic-selection into .claude/skills/sigmetrics-topic-selection/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "sigmetrics-topic-selection", 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/SIGMETRICS-Skills/skills/sigmetrics-topic-selectionType 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 sigmetrics-topic-selection -a codexProject install goes to .agents/skills/; add -g for ~/.codex/skills/.
$ gh skill install brycewang-stanford/Awesome-Journal-Skills sigmetrics-topic-selection --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/SIGMETRICS-Skills/skills/sigmetrics-topic-selection .agents/skills/sigmetrics-topic-selection && rm -rf skills-srcUse ~/.agents/skills/ instead of .agents/skills for a personal install.
Codex skills documentation · loads skills from .agents/skills/
Install the "sigmetrics-topic-selection" agent skill from https://github.com/brycewang-stanford/Awesome-Journal-Skills/tree/main/SIGMETRICS-Skills/skills/sigmetrics-topic-selection into .agents/skills/sigmetrics-topic-selection/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "sigmetrics-topic-selection", 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 sigmetrics-topic-selection -a cursorProject install goes to .agents/skills/; add -g for ~/.cursor/skills/.
$ gh skill install brycewang-stanford/Awesome-Journal-Skills sigmetrics-topic-selection --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/SIGMETRICS-Skills/skills/sigmetrics-topic-selection .cursor/skills/sigmetrics-topic-selection && 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 "sigmetrics-topic-selection" agent skill from https://github.com/brycewang-stanford/Awesome-Journal-Skills/tree/main/SIGMETRICS-Skills/skills/sigmetrics-topic-selection into .cursor/skills/sigmetrics-topic-selection/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "sigmetrics-topic-selection", 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 SIGMETRICS-Skills/skills/sigmetrics-topic-selection--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 sigmetrics-topic-selection -a gemini-cliProject install goes to .agents/skills/; add -g for ~/.gemini/skills/.
$ gh skill install brycewang-stanford/Awesome-Journal-Skills sigmetrics-topic-selection --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/SIGMETRICS-Skills/skills/sigmetrics-topic-selection .gemini/skills/sigmetrics-topic-selection && 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 "sigmetrics-topic-selection" agent skill from https://github.com/brycewang-stanford/Awesome-Journal-Skills/tree/main/SIGMETRICS-Skills/skills/sigmetrics-topic-selection into .gemini/skills/sigmetrics-topic-selection/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "sigmetrics-topic-selection", 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 sigmetrics-topic-selectionInstalls 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 sigmetrics-topic-selection -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/SIGMETRICS-Skills/skills/sigmetrics-topic-selection .github/skills/sigmetrics-topic-selection && 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 "sigmetrics-topic-selection" agent skill from https://github.com/brycewang-stanford/Awesome-Journal-Skills/tree/main/SIGMETRICS-Skills/skills/sigmetrics-topic-selection into .github/skills/sigmetrics-topic-selection/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "sigmetrics-topic-selection", 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 sigmetrics-topic-selection -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 sigmetrics-topic-selection --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/SIGMETRICS-Skills/skills/sigmetrics-topic-selection .opencode/skills/sigmetrics-topic-selection && 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 "sigmetrics-topic-selection" agent skill from https://github.com/brycewang-stanford/Awesome-Journal-Skills/tree/main/SIGMETRICS-Skills/skills/sigmetrics-topic-selection into .opencode/skills/sigmetrics-topic-selection/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "sigmetrics-topic-selection", 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
sigmetrics-topic-selection- GitHub stars
- 1.2k
- Token cost
- ~1.5k tokens
- SKILL.md length
- 582 words
- Files
- 1
- Skills in repo
- 2,387
- Repo updated
- First seen
- Licence
- MIT
At a glance
A skill your agent uses when deciding whether a computer-systems performance project belongs at ACM SIGMETRICS or should be routed to IMC, SIGCOMM/NSDI/OSDI, INFOCOM, a learning venue…
- Deciding whether a computer-systems performance project belongs at ACM SIGMETRICS
- SKILL.md covers The routing question that…, Sibling-venue routing table, Contribution shapes SIGMETRICS… and The rigor and validation tests, plus 3 more sections
- Instructions only: no scripts, shell commands, URLs or credentials in SKILL.md
- Should be routed to IMC
What it does
Sigmetrics Topic Selection is an agent skill from brycewang-stanford/Awesome-Journal-Skills. Use when deciding whether a computer-systems performance project belongs at ACM SIGMETRICS or should be routed to IMC, SIGCOMM/NSDI/OSDI, INFOCOM, a learning venue (NeurIPS/ICML), or a performance journal (Performance Evaluation/TON/QUESTA), and when picking the right SIGMETRICS track (Theory / Measurement & Applied Modeling / Learning / Operational Systems).
Its SKILL.md is about 1.5k tokens, which your agent loads only when the skill is triggered. It is a single SKILL.md file with no bundled scripts.
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
- Deciding whether a computer-systems performance project belongs at ACM SIGMETRICS
- Should be routed to IMC
- SIGCOMM/NSDI/OSDI
- A learning venue (NeurIPS/ICML)
Example prompts
- “/sigmetrics-topic-selection”
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
Sigmetrics Topic Selection loads about 1.5k tokens when it runs. Until then it costs about 97 tokens; SKILL.md has 582 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). 582 words, ~1,480 tokens.
Download SKILL.mdSave it as
.claude/skills/sigmetrics-topic-selection/SKILL.md (or your agent's skills folder).- name
- sigmetrics-topic-selection
- description
- Use when deciding whether a computer-systems performance project belongs at ACM SIGMETRICS or should be routed to IMC, SIGCOMM/NSDI/OSDI, INFOCOM, a learning venue (NeurIPS/ICML), or a performance journal (Performance Evaluation/TON/QUESTA), and when picking the right SIGMETRICS track (Theory / Measurement & Applied Modeling / Learning / Operational Systems).
SIGMETRICS Topic Selection
Decide the venue and track before drafting. SIGMETRICS — the ACM flagship for performance measurement, modeling, and evaluation of computer systems — rewards a rigorous performance-evaluation contribution: a stochastic/queueing model with a proven bound, a principled measurement study, or a learning-for-systems algorithm with guarantees. A technically strong paper whose real lesson is a built system (route to NSDI/OSDI), a pure network measurement (route to IMC), or a learning-theory result with no systems payoff (route to NeurIPS/COLT) is respected and then rejected as out of scope.
The routing question that matters most
The decisive question is rarely "is this about systems performance?" but "is the contribution an analyzed/measured performance result, or is it something else with performance numbers attached?" SIGMETRICS wants the why — a model, a proof, a validated methodology — not only a faster system or a bigger dataset.
Sibling-venue routing table
| Signal in your project | Better home | Why |
|---|---|---|
| A model/policy with a proven performance bound, or a principled measurement/modeling study | ACM SIGMETRICS | Its center: rigorous performance evaluation published in POMACS |
| The contribution is a built system; the design/implementation is the point | NSDI / OSDI / SIGCOMM | Systems-building venues; SIGMETRICS wants analysis, not a system artifact |
| The whole paper is network measurement (Internet, CDN, topology, traffic) | IMC | The dedicated network-measurement venue; single annual deadline |
| Networking with a systems/protocol contribution | SIGCOMM / NSDI / INFOCOM | Networking-systems scope |
| A learning-theory result with no systems performance payoff | NeurIPS / ICML / COLT | Learning venues; SIGMETRICS Learning track wants a systems angle or systems-relevant guarantees |
| A study too long/deep for 20 pages, or wanting multiple revision rounds | Performance Evaluation / TON / QUESTA | Journals with no conference page ceiling and open-ended revision |
Contribution shapes SIGMETRICS rewards
- Stochastic / queueing / scheduling theory — a model of a system's performance with a proven bound, stability condition, or optimality result, validated numerically (the SOAP lineage).
- Measurement & applied modeling — a principled measurement or simulation methodology and the characterization it yields about a real system (the Google-Play-study lineage).
- Learning for systems — an online-learning/bandit/RL/control algorithm for a systems problem, with regret/convergence/sample-complexity guarantees (the learning-to-rank lineage).
- Operational systems — a deployed system in significant real-world use, analyzed with principled measurement and metrics (the Operational Systems Track; may name the system/org).
Show full SKILL.md (224 more words)Show less
The rigor and validation tests
Two quick tests sharpen a borderline verdict:
- Rigor test: does the contribution carry a checkable claim — a theorem, a stated-assumption bound, a measurement methodology a skeptic would accept — or only "it is faster on our setup"? If the latter, it is a systems-building paper (NSDI/OSDI), not SIGMETRICS.
- Model-swap / methodology test: if your paper leans on a learner or a specific system, ask whether the performance-evaluation lesson survives — a guarantee, a validated model, a general methodology. If the only result is a benchmark score, it is an ML or systems paper wearing a SIGMETRICS title.
Picking the track (do this at abstract registration)
- Theory: the core is a proof (queueing, scheduling, caching, algorithms, control).
- Measurement & Applied Modeling: the core is data from a real system + a methodology/model.
- Learning: the core is a learning algorithm with analysis, applied to or for systems.
- Operational Systems: the core is a deployed, in-use system; you may reveal its name/org.
Pick one; a second only for genuinely interdisciplinary work (e.g. a learning-theoretic result validated by measurement). The wrong track routes you to the wrong reviewers.
Cheap reconnaissance before committing
[Scope] scan the last few POMACS issues (dblp, ACM DL) for your subarea and track
-> several recent papers = a reviewer pool exists; none = opening or mismatch
[Rigor] does your headline claim reduce to a theorem, a validated model, or a principled
measurement? -> if not, reconsider SIGMETRICS vs. a systems venue
[Calendar] the next rolling deadline (summer/fall/winter) is ~a quarter away -> route to the
nearest honest fit rather than forcing a rushed proof/measurementDecision procedure
[Audience] who acts differently if the claim holds? -> systems designers/operators/theorists?
[Claim type] queueing/theory / measurement / learning-with-guarantees / operational
[Rigor gate] is there a checkable performance claim (proof / validated model / methodology)?
[Sibling check] built system -> NSDI/OSDI; pure net-measurement -> IMC; learning-theory-only -> NeurIPS
[Verdict] SIGMETRICS <track> / sibling venue / performance journal, with a one-line reasonRun this before the writing skills; a wrong venue or track decision wastes every later step. When
the verdict is SIGMETRICS, continue with sigmetrics-workflow for the deadline choice and
sigmetrics-writing-style for the paper shape.
© 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 SIGMETRICS-Skills/skills/sigmetrics-topic-selection of brycewang-stanford/Awesome-Journal-Skills.
Open the folder on GitHubat commit 932eb23
Compare with similar skills
Sigmetrics Topic Selection 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 |
|---|---|---|---|---|---|---|
| Sigmetrics Topic Selection this skillbrycewang-stanford/Awesome-Journal-Skills | 1.2k | — | ~1.5k | Automated safety check: Pass | MIT | |
| Ito Computeaffaan-m/ECC | 276k | 1 repos | ~1.7k | Automated safety check: Pass | MIT | |
| Senior Computer Visiondavila7/claude-code-templates | 32k | 2 repos | ~1.4k | Automated safety check: Pass | MIT | |
| Senior Computer Visionalirezarezvani/claude-skills | 28k | 1 repos | ~3.2k | Automated safety check: Pass | MIT | |
| GCP Computesickn33/agentic-awesome-skills | 47k | 2 repos | ~2.6k | Automated safety check: Pass | MIT | |
| Computer UseQwenLM/qwen-code | 28k | — | ~3.6k | Automated safety check: Pass | Apache-2.0 |
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Questions about Sigmetrics Topic Selection
What does Sigmetrics Topic Selection do?
A skill your agent uses when deciding whether a computer-systems performance project belongs at ACM SIGMETRICS or should be routed to IMC, SIGCOMM/NSDI/OSDI, INFOCOM, a learning venue…. Sigmetrics Topic Selection is an agent skill from brycewang-stanford/Awesome-Journal-Skills. Use when deciding whether a computer-systems performance project belongs at ACM SIGMETRICS or should be routed to IMC, SIGCOMM/NSDI/OSDI, INFOCOM, a learning venue (NeurIPS/ICML), or a performance journal (Performance Evaluation/TON/QUESTA), and when picking the right SIGMETRICS track (Theory / Measurement & Applied Modeling / Learning / Operational Systems).
When should I use Sigmetrics Topic Selection?
Sigmetrics Topic Selection fits situations like: deciding whether a computer-systems performance project belongs at ACM SIGMETRICS; should be routed to IMC; SIGCOMM/NSDI/OSDI; A learning venue (NeurIPS/ICML).
How do I install Sigmetrics Topic Selection in Claude Code?
Run `npx skills add brycewang-stanford/Awesome-Journal-Skills --skill sigmetrics-topic-selection -a claude-code`. Or copy the skill folder (SIGMETRICS-Skills/skills/sigmetrics-topic-selection in brycewang-stanford/Awesome-Journal-Skills) into .claude/skills/sigmetrics-topic-selection in your project. Claude Code loads it when a task matches its description.
How do I install Sigmetrics Topic Selection in Codex?
Run `npx skills add brycewang-stanford/Awesome-Journal-Skills --skill sigmetrics-topic-selection -a codex`. Or copy the skill folder (SIGMETRICS-Skills/skills/sigmetrics-topic-selection in brycewang-stanford/Awesome-Journal-Skills) into .agents/skills/sigmetrics-topic-selection in your project. Codex loads it when a task matches its description.
Can I use Sigmetrics Topic Selection 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 sigmetrics-topic-selection -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/sigmetrics-topic-selection, .gemini/skills/sigmetrics-topic-selection, .github/skills/sigmetrics-topic-selection and .opencode/skills/sigmetrics-topic-selection in your project.
What does Sigmetrics Topic Selection need to run?
SKILL.md names no scripts, command-line tools or credentials: Sigmetrics Topic Selection is instructions for the agent only.
Does Sigmetrics Topic Selection 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 Sigmetrics Topic Selection 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 Sigmetrics Topic Selection use?
Sigmetrics Topic Selection 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 Sigmetrics Topic Selection use?
About 1.5k tokens (SKILL.md is roughly 5.9k 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 Sigmetrics Topic Selection?
Skills that share tags, products or a category with Sigmetrics Topic Selection: Ito Compute (affaan-m/ECC, 276k stars), Senior Computer Vision (davila7/claude-code-templates, 32k stars), Senior Computer Vision (alirezarezvani/claude-skills, 28k stars) and GCP Compute (sickn33/agentic-awesome-skills, 47k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.
Who maintains Sigmetrics Topic Selection?
brycewang-stanford (a GitHub user) maintains it in brycewang-stanford/Awesome-Journal-Skills, which has 1,228 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.