Individual skill
conext-experiments
Use when designing or auditing the evaluation of an ACM CoNEXT paper — matching evidence to claim shape with real testbeds and deployments, honest and tuned baselines, measurement statistics and uncertainty, trace and config provenance, and contamination-aware ablations for ML-for-networking work.
CoNEXT-Skills/skills/conext-experiments/SKILL.md
Source commit 932eb23331721b16e967c59f093781be1928b498
What was checked
- Matches the observed repository HEAD
- Yes
- Scanner rules are current
- No
- Repository scan complete
- No
- Skill scan complete
- Yes
- Observed behavior
- Not checked yet
- 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)
- 1,411
- 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
- data 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 · 5,467 bytes
Read excerpt
# CoNEXT Experiments
Build the evaluation a networking reviewer will actually interrogate. CoNEXT's evidence culture is
**systems-and-measurement**: claims are backed on the **real target platform** — a testbed,
deployment, or trace — with honest baselines and reported uncertainty, not simulation standing in
for hardware or a single number with no variance. Because a one-shot major revision is decided on a
list of **minimum necessary changes**, an evaluation gap you leave now often becomes a mandatory fix
under a tight window later.
## Match evidence to claim shape
| Claim shape | Evidence CoNEXT expects |
|---|---|
| A mechanism is faster/cheaper on real hardware | A run on the **real target** (switch, NIC, kernel, testbed) under its real constraints, vs. a tuned baseline, with effect sizes |