Agent skill

icalp-artifact-evaluation

Use to understand why ICALP (EATCS) has no artifact-evaluation track or badge scheme, and what plays the equivalent role for a pure-theory paper — the full version with complete proofs, reproducible computational certificates, and optional machine formalization — so authors coming from a systems/ML venue do not waste effort building an artifact ICALP does not evaluate.

brycew6m4,252★ · +31/wk · 3 repos on radarProfile →
claude-codeMIT
Install
npx skills add brycewang-stanford/Awesome-Journal-Skills --skill icalp-artifact-evaluation --agent claude-code

Same command for any agent — swap --agent for codex, cursor, copilot.

Facts
Files in the skill folder: 1
SKILL.md size: 4 KB
Bundled scripts: none
Path: ICALP-Skills/skills/icalp-artifact-evaluation/SKILL.md
Open the folder on GitHub →
Where it comes from
Stars: 984 · +31 this week
Language: Stata
Read our review of the source →

Weekly change comes from our own snapshots, not the repository page — it measures attention, not adoption.

From the SKILL.md

# ICALP Artifact Evaluation (there isn't one — and what replaces it) Read this first if you are arriving from a venue with an artifact track. **ICALP has no artifact evaluation, no artifact-evaluation committee, and no ACM/IEEE badges.** It is a **pure theoretical computer science** venue: the contribution is a theorem, and the "artifact" a referee cares about is the **proof**. Building a Docker image, a benchmark harness, or a reproducibility capsule for an ICALP submission is effort spent on something no one will evaluate — and can even signal that the paper is mis-routed. ## Why no artifact track - ICALP results are **mathematical**: correctness is established by a proof a referee checks, not by running code on a machine. - The community norm and the LIPIcs open-access model center the **published proof and the full version**, not a software deliverable. - Contrast the software-engineering / systems / ML world (ACM/IEEE Available–Functional–Reusable– Reproduced badges, or ML reproducibility checklists): those exist because the contribution *is* a system or an empirical result. At ICALP it is not. ## What plays the artifact's role | Systems/ML artifact concept | ICALP equivalent

What's inside
Steps it walks through
  1. Why no artifact track
  2. What plays the artifact's role
  3. When your paper DOES contain software
  4. Do not
  5. Output format
More from Awesome-Journal-Skills
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About this skill
What does the icalp-artifact-evaluation skill do?

Use to understand why ICALP (EATCS) has no artifact-evaluation track or badge scheme, and what plays the equivalent role for a pure-theory paper — the full version with complete proofs, reproducible computational certificates, and optional machine formalization — so authors coming from a systems/ML venue do not waste effort building an artifact ICALP does not evaluate.

How do I install it?

Run `npx skills add brycewang-stanford/Awesome-Journal-Skills --skill icalp-artifact-evaluation --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.

Keep going