Individual skill
sigmetrics-topic-selection
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-Skills/skills/sigmetrics-topic-selection/SKILL.md
Source commit 932eb23331721b16e967c59f093781be1928b498
What was checked
- Matches the observed repository HEAD
- Yes
- Scanner rules are current
- Yes
- Repository scan complete
- No
- Skill scan complete
- Yes
- Observed behavior
- Network or broad shell
- Last checked
- Nov 9, 2026
These are observations at the recorded commit, not a guarantee of safety. Review the source before running it.
Install this skill
Choose an agent in your Stack or copy a command below. Commands fetch the pinned commit and copy only this skill directory. Existing destinations are refused. Copying a command does not install anything.
An install command is unavailable: current rules, complete repository and skill scans, an eligible behavior level and a permitted license are required.
Repository context
- Repository stars (not skill ratings)
- 1,405
- Repository last updated
- Sep 27, 2026
- License
- MIT
Observed agent integration: No specific integration evidence. Standard SKILL.md installation does not imply verified compatibility.
- academic-writing Repository topic
- agent-skills Repository topic
- journal Repository topic
- academic-research Repository topic
- ai-agents Repository topic
- anthropic Repository topic
- awesome-list Repository topic
- claude Repository topic
- claude-code Repository topic
- economics Repository topic
- education Derived category
Files and excerpt
File metadata and permitted, redacted excerpts come from the recorded scan. Source links are pinned to that commit.
Browse files
SKILL.mdcore · 5,941 bytes
Read excerpt
# 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?"**