Individual skill
colt-experiments
Use when deciding whether a COLT (Conference on Learning Theory) paper needs numerical content at all — COLT has no experiments requirement — and, when numerics genuinely help, designing small illustrative simulations that visualize a proved bound, a separation, or a phase transition without diluting the theory.
COLT-Skills/skills/colt-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)
- 1,410
- 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
- research 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 · 6,777 bytes
Read excerpt
# COLT Experiments
Start from the venue truth: **COLT imposes no experiments requirement, and most COLT
papers contain no experiments.** The 2026 CFP (checked 2026-07-08) asks for
theoretical machine-learning contributions and mentions no empirical-evaluation
expectation; papers are accepted on theorems. The decision this skill supports is
therefore *whether* to include numerics, and only then *how*.
## Should this paper contain numerics at all?
| Situation | Include numerics? | Rationale |
|---|---|---|
| Clean upper/lower bound pair, standard model | No | Plots add length, not belief |
| New algorithm whose practicality is part of the pitch | Small illustration | Shows the constants are not absurd |