colt-reproducibility
Use when strengthening the reproducibility of a COLT (Conference on Learning Theory) paper, where reproducing means re-deriving — complete proofs, explicit assumptions, tracked constants, correctly invoked external results, self-contained notation — plus seeds and scripts for any numerical illustration the paper carries.
Profile →npx skills add brycewang-stanford/Awesome-Journal-Skills --skill colt-reproducibility --agent claude-code
Same command for any agent — swap --agent for codex, cursor, copilot.
Weekly change comes from our own snapshots, not the repository page — it measures attention, not adoption.
# COLT Reproducibility At COLT, reproducibility means a competent reader can *re-derive* every claim from the PDF alone. There is no reproducibility checklist form in the COLT 2026 CFP (checked 2026-07-08) — the venue enforces the property the hard way, through referees who attempt the re-derivation during review. This skill is the pre-submission audit that makes that attempt succeed. ## The re-derivability standard A theorem is reproducible when all of the following hold: - Its statement is formally complete: every symbol quantified, every assumption named in the statement itself or cited by an explicit assumption label, the probability space and adversary model unambiguous. - Its proof exists in full inside the submitted PDF — COLT's unlimited appendix removes every excuse for "omitted for lack of space." - Each proof step is locally checkable: an expert reading line k needs only lines 1..k-1, cited external results, and standard background — never your unpublished intuition. - Constants and parameter regimes survive the chain: if Theorem 1 needs n ≥ C·d·log(1/δ), the reader can trace what C is or where it was declared absolute. ## Audit table: where re-derivation fails | Failure
- The re-derivability standard
- Audit table: where re-derivation fails
- Assumption bookkeeping pattern
- Numerical illustrations, when present
- Vignette: the spine of a lower-bound paper
- Pre-submission re-derivation drill
- Cycle-volatility warnings
- Output format
What does the colt-reproducibility skill do?
Use when strengthening the reproducibility of a COLT (Conference on Learning Theory) paper, where reproducing means re-deriving — complete proofs, explicit assumptions, tracked constants, correctly invoked external results, self-contained notation — plus seeds and scripts for any numerical illustration the paper carries.
How do I install it?
Run `npx skills add brycewang-stanford/Awesome-Journal-Skills --skill colt-reproducibility --agent claude-code` — it drops the skill into your project so the agent can pick it up. Swap the --agent value for codex, cursor or copilot if you use one of those.
Where does this skill come from?
From brycewang-stanford/Awesome-Journal-Skills, a repository with 909 stars. We read it straight from the repository tree rather than a submitted listing, so what you see here is what is actually published.
Is a popular skill a good skill?
Not necessarily. Stars measure attention, not adoption — a repository can trend for a week and be abandoned. That is why we show the weekly change from our own snapshots next to the total, instead of a single flattering number.