ablation-planner
Use when main results pass result-to-claim (claim_supported=yes or partial) and ablation studies are needed for paper submission.
Paragraph-level structural blueprint for 10-12 page systems papers targeting OSDI, SOSP, ASPLOS, NSDI, and EuroSys. Provides page allocation, paragraph templates, and writing patterns. Use when user says \"写系统论文\", \"systems paper structure\", \"OSDI paper\", \"SOSP paper\", or
$ npx -y skills add wanshuiyin/Auto-claude-code-research-in-sleep --skill writing-systems-papers --agent claude-codeHow it fires
How this skill gets triggered: by you, by Claude, or both.
/writing-systems-papersContext preview
The summary Claude sees to decide when to auto-load this skill.
Paragraph-level structural blueprint for 10-12 page systems papers targeting OSDI, SOSP, ASPLOS, NSDI, and EuroSys. Provides page allocation, paragraph templates, and writing patterns. Use when user says \"写系统论文\", \"systems paper structure\", \"OSDI paper\", \"SOSP paper\", or
name: writing-systems-papers description: "Paragraph-level structural blueprint for 10-12 page systems papers targeting OSDI, SOSP, ASPLOS, NSDI, and EuroSys. Provides page allocation, paragraph templates, and writing patterns. Use when user says \"写系统论文\", \"systems paper structure\", \"OSDI paper\", \"SOSP paper\", or wants fine-grained structural guidance for a systems conference submission." argument-hint: "[venue-or-section]" allowed-tools: Bash(*), Read, Write, Edit, Grep, Glob, WebSearch, WebFetch, mcp__codex__codex, mcp__codex__codex-reply
Structural guidance for **$ARGUMENTS**
**Boundary**: paper-write handles the generation workflow (LaTeX output, DBLP verification, section-by-section drafting). This skill provides the **structural skeleton** — page budgets, paragraph roles, and writing patterns specific to systems venues.
---
| Section | Pages | Key Content | |---------|-------|-------------| | Abstract | ~0.25 | 150–250 words, 5 sentences | | S1 Introduction | 1.5–2 | Problem → Gap → Insight → Contributions | | S2 Background & Motivation | 1–1.5 | Terms + Production observations | | S3 Design | 3–4 | Architecture + Modules + Alternatives | | S4 Implementation | 0.5–1 | Prototype, LOC, engineering | | S5 Evaluation | 3–4 | Setup + E2E + Ablation + Scalability | | S6 Related Work | 1 | By methodology, explicit comparison | | S7 Conclusion | 0.5 | 3-sentence summary |
---
S1: Problem context and importance S2: Gap in existing approaches S3: Thesis — "X is better for Y in environment Z" (Irene Zhang formula) S4: Approach summary + headline results S5: Impact or availability
Sources: Levin & Redell — "Can you state the new idea concisely?"; Irene Zhang — "abstract cannot use terms introduced in the paper."
1. **Problem** (~0.5p) — Domain + concrete numbers + why it matters 2. **Gap analysis** (~0.5p) — G1–Gn: specific shortcomings with evidence 3. **Key insight** (1 para) — Thesis: "X is better for Y in Z" 4. **Contributions** (~0.5p) — 3–5 numbered, testable claims with §N references
Pattern: hzwer Move 1 (territory) → Move 2 (niche) → Move 3 (occupy).
1. **Technical background** (~0.5p) — Define-before-use (Gernot Heiser) 2. **Observations** (~0.5–1p) — O1, O2, O3 from production data → design insights
1. **Architecture overview** (~0.5p) — Diagram first (Yi Ding: "draw a picture first") 2. **Module details** (~2–2.5p) — Per module: choice, alternatives, why 3. **Trade-offs** (~0.5–1p) — Summary of design decisions
Rule: "Every design choice must discuss alternatives" (Irene Zhang).
Language, LOC, framework, key engineering decisions. Keep concise.
1. **Setup** (~0.5p) — Hardware, baselines, workloads, metrics 2. **End-to-end** (~1–1.5p) — X vs baselines for Y on Z 3. **Ablation** (~1–1.5p) — Remove each component, measure impact 4. **Scalability** (~0.5p) — Behavior at increasing scale
**Three-statement rule** (Irene Zhang): Every conclusion stated as:
Group by methodology. For each group: what they do, limitation, how we differ.
Three sentences: problem, solution, result. No new information.
---
Enumerate G1–Gn in intro → A1–An in design → verify in evaluation. *Example*: Lucid (ASPLOS'23) — 5 gaps mapped to 5 answers.
O1–O3 from production data → insights → design components. *Example*: GFS (arXiv 2025) — 3 observations drive 3 components.
Numbered contributions in intro, each with §N cross-reference. *Example*: Blox (EuroSys'24) — 7 contributions; Sia (SOSP'23) — 5 contributions.
"X is better for Y in Z" structures the entire paper. Combine with other patterns for maximum impact.
---
> Always verify against current CFP — rules change yearly.
| Venue | Format | Pages | Camera-Ready | |-------|--------|-------|-------------| | OSDI | USENIX | 12 | 14 | | NSDI | USENIX | 12 | 14 | | SOSP | ACM SIGOPS | 12 | — | | ASPLOS | ACM SIGPLAN | 11 | 13 | | EuroSys | ACM | 12 | — |
Based on 2025/2026 CFPs.
---
1. Determine venue and page limit 2. Choose writing pattern (Gap/Observation/Contribution/Thesis) 3. Allocate pages per section using the table above 4. Draft Abstract following 5-sentence template 5. Draft Introduction: Problem → Gap → Insight → Contributions 6. Draft Motivation with production observations (if available) 7. Draw architecture figure, then write Design 8. Draft Implementation (concise) 9. Draft Evaluation: setup → E2E → ablation → scalability 10. Draft Related Work by methodology groups 11. Draft Conclusion: 3 sentences 12. Run pre-submission checklist 13. Hand off to /paper-write for LaTeX generation and citation verification
---
· · · · · · -orange?style=flat) · · 💬 Join Community · 💡 Use ARIS as a skill-based workflow in Claude Code / Codex CLI / Cursor / Trae / Antigravity / GitHub Copilot CLI / OpenClaw / DeepSeek Harness, or get the full experience with the standalone ARIS-Code
Use when main results pass result-to-claim (claim_supported=yes or partial) and ablation studies are needed for paper submission.
Quick single-paper lookup via AlphaXiv LLM-optimized summaries with tiered source fallback. Use when user says "explain this paper", "summarize paper", pastes…
Analyze ML experiment results, compute statistics, generate comparison tables and insights. Use when user says "analyze results", "compare", or needs to…
Search, download, and summarize academic papers from arXiv. Use when user says "search arxiv", "download paper", "fetch arxiv", "arxiv search", "get paper…
Autonomously improve a generated paper via GPT-6-Astra xhigh review → implement fixes → recompile, for 2 rounds. Use when user says \"改论文\", \"improve paper\",…
Autonomous research review loop using any OpenAI-compatible LLM API. Configure via llm-chat MCP server or environment variables. Trigger with "auto review loop…