ecai-related-work
Use when writing the ECAI related-work section — covering the relevant general-AI lanes (symbolic, learning, multi-agent, application) for a broad reviewer pool, writing delta-first positioning, keeping self-citations double-blind, and doing it within a tight reference budget (1 page standalone / 2 pages in IJCAI-ECAI 2026).
Profile →npx skills add brycewang-stanford/Awesome-Journal-Skills --skill ecai-related-work --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.
# ECAI Related Work ECAI's related work has a peculiar difficulty: the reviewer pool is **broad** (a planning paper may draw a KR reviewer and an ML reviewer), yet the **space is tiny** — the body is 7 pages and references overflow into only 1 page (standalone ECAI) or 2 pages (IJCAI-ECAI 2026). You must position against the right lanes for a general audience *and* stay compact. ## Cover the lanes a general-AI reviewer will expect Identify which AI lanes your contribution touches and place it in each — a broad reviewer will fault a section that only cites its author's home subfield: - **Symbolic / foundational lane** — the KR, planning, search, reasoning, or argumentation line your problem sits in. - **Learning lane** — the ML/statistical methods your work uses or competes with. - **Multi-agent / decision lane** — if agents, game-theoretic, or sequential-decision aspects apply. - **Application lane** — the real-world domain, especially for a **PAIS**-flavored contribution. - **Cross-venue neighbors** — the closest work at IJCAI, AAAI, AAMAS, KR, or a specialist venue, so a reviewer from that community sees you know the field's flagship results. You will not cover all lanes deeply a
- Cover the lanes a general-AI reviewer will expect
- Delta-first positioning
- Keep it double-blind
- Budget discipline
- Common failure modes
- Output format
Catch first-person self-citation and identity leaks in related work grep -nEi 'our (previous|prior|earlier) (work|paper|system|approach)|we previously' paper.tex | head
What does the ecai-related-work skill do?
Use when writing the ECAI related-work section — covering the relevant general-AI lanes (symbolic, learning, multi-agent, application) for a broad reviewer pool, writing delta-first positioning, keeping self-citations double-blind, and doing it within a tight reference budget (1 page standalone / 2 pages in IJCAI-ECAI 2026).
How do I install it?
Run `npx skills add brycewang-stanford/Awesome-Journal-Skills --skill ecai-related-work --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.