icalp-experiments
Use when matching the argument of an ICALP (EATCS) theory paper to its claim — choosing the proof strategy for an upper or lower bound, deciding when supporting computation (SAT/SMT-verified base cases, computer-assisted case analysis, exhaustive small-case checks) legitimately backs a theorem, and keeping any such computation reproducible without turning a proof paper into an experimental one.
Profile →npx skills add brycewang-stanford/Awesome-Journal-Skills --skill icalp-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.
# ICALP Experiments (proof strategy, and computation in service of proofs) At ICALP there is usually **no experiment section** — the evidence for the claim *is the proof*. This skill is therefore about matching the **argument** to the **claim shape**, and about the narrow, real cases where **computation supports a theorem** (a computer-assisted proof, an SMT-checked base case, an exhaustive small-case verification). It is deliberately not an empirical-evaluation guide: a paper whose contribution is a benchmark result is mis-routed (`icalp-topic-selection`). ## Match the argument to the claim | Claim shape | The argument that fits | Common failure caught by referees | |---|---|---| | Upper bound / faster algorithm | Algorithm + correctness proof + complexity analysis | Correctness hand-waved; complexity ignores a hidden cost | | Approximation ratio | An analysis bounding cost vs optimum, with a tight example | Ratio proved only on the easy case; no tight instance | | Lower bound (unconditional) | A reduction, adversary, or information-theoretic argument | Model too weak to be interesting, or gap left open | | Conditional lower bound | A fine-grained reduction from SETH/3SUM/APSP | W
- Match the argument to the claim
- When computation legitimately supports a theorem
- Keep it a proof paper, not an experiment paper
- Reproducibility of the computational part
- Worked vignette: a dichotomy with a computer-checked base
- Output format
What does the icalp-experiments skill do?
Use when matching the argument of an ICALP (EATCS) theory paper to its claim — choosing the proof strategy for an upper or lower bound, deciding when supporting computation (SAT/SMT-verified base cases, computer-assisted case analysis, exhaustive small-case checks) legitimately backs a theorem, and keeping any such computation reproducible without turning a proof paper into an experimental one.
How do I install it?
Run `npx skills add brycewang-stanford/Awesome-Journal-Skills --skill icalp-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 984 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.