itcs-experiments
Use when deciding what counts as evidence for an ITCS theory claim — proofs as the primary evidence, worked examples and separations that make a model concrete, and the rare, well-scoped illustrative computation or simulation — and how to keep any computational content checkable and subordinate to the mathematics.
Profile →npx skills add brycewang-stanford/Awesome-Journal-Skills --skill itcs-experiments --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.
# ITCS Experiments ITCS is a **pure-theory** venue: the primary — usually the only — evidence for a claim is a **proof**. There is no experiments requirement, no benchmark, no leaderboard, and no reviewer expectation of an empirical section. Bringing an ML-conference or SE reflex here (a table of numbers "showing" the method works) misreads the venue: at ITCS a theorem is proved, not measured. This skill is about matching **evidence to a theory claim** and about the *rare* case where a small computation genuinely helps. ## Proofs are the evidence - **Every central claim is settled by a complete proof**, not by examples. A pattern that "holds in all cases we tried" is a conjecture, not a theorem — label it as such and prove or drop it. - **Match the claim shape to the argument shape:** an upper bound needs a construction + analysis; a lower bound needs an adversary/reduction; a separation needs a witness object; an impossibility needs a contradiction from the assumption. Reviewers check that the *kind* of argument fits the *kind* of claim. - **A new model needs an anchoring result** (see [`itcs-writing-style`](../itcs-writing-style/SKILL.md)) — a separation or a surprising possibili
- Proofs are the evidence
- Worked examples and separations as evidence
- The rare, well-scoped computation
- What NOT to import from empirical venues
- Decision procedure
- Output format
What does the itcs-experiments skill do?
Use when deciding what counts as evidence for an ITCS theory claim — proofs as the primary evidence, worked examples and separations that make a model concrete, and the rare, well-scoped illustrative computation or simulation — and how to keep any computational content checkable and subordinate to the mathematics.
How do I install it?
Run `npx skills add brycewang-stanford/Awesome-Journal-Skills --skill itcs-experiments --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.