‹ 首页

outline-agent

@ar9av · 收录于 1 周前 · 上游提交 1 周前

Step 1 of the PaperOrchestra pipeline (arXiv:2604.05018). Convert (idea.md, experimental_log.md, template.tex, conference_guidelines.md) into a strict JSON outline containing a plotting plan, literature search plan (Intro + Related Work), and section-level writing plan with citation hints. TRIGGER when the orchestrator delegates Step 1 or when the user asks to "outline a paper from raw materials" or "generate the paper structure".

适合你,如果你需要从实验记录和会议指南生成结构化的论文大纲。

/ 下载安装
outline-agent.skill双击,或拖进 Claude 桌面版 / Cowork,即完成安装↓ .skill↓ .zip
用别的 agent?下载 .zip 解压,把文件夹放进它的技能目录
Claude Code~/.claude/skills/(项目级 .claude/skills/)
Codex CLI~/.codex/skills/
Cursor自动读取上面两处目录
其他工具见其文档的「skills」目录;两个下载是同一份文件,只是名字不同
/ 通过 npx 安装 校验哈希
npx oh-my-skill add ar9av/paperorchestra/outline-agent
/ 通过 bash 安装
curl -fsSL https://oh-my-skill.com/install.sh | bash -s -- ar9av/paperorchestra/outline-agent
/ 已经装过?验证本机副本,不用重装
npx oh-my-skill verify ar9av/paperorchestra/outline-agent
安装目标可用 --agent / --scope 或 --to 明确指定;省略时只会在唯一已存在的 agent 目录上自动选择,零命中或多命中会停止并提示。content_hash 缺失或不一致均拒装。
609GitHub stars
~1.3K最小装载
~6.3K含声明引用
~6.3K文本包总量
镜像托管

怎么用

技能原文 SKILL.md作者撰写 · MIT · 07b981f

Outline Agent (Step 1)

Faithful implementation of the Outline Agent from PaperOrchestra (Song et al., 2026, arXiv:2604.05018, App. F.1, pp. 40–44).

Cost: 1 LLM call.

Your task

Read four input files from the workspace and produce a single JSON object at workspace/outline.json with three top-level keys:

  • plotting_plan — array of figure objects
  • intro_related_work_plan — object with introduction_strategy and related_work_strategy
  • section_plan — array of section objects, each with section_title and subsections[]
How to do it
  1. Read the verbatim prompt at references/prompt.md. This is the exact Outline Agent system prompt from the paper. Use it as your system message.
  2. Prepend the Anti-Leakage Prompt from ../paper-orchestra/references/anti-leakage-prompt.md.
  3. Read the four input files:
  4. workspace/inputs/idea.md
  5. workspace/inputs/experimental_log.md
  6. workspace/inputs/template.tex
  7. workspace/inputs/conference_guidelines.md
  8. Synthesize across all four — the global instruction in the prompt is "Do not analyze inputs in isolation. You must synthesize information across all provided documents for every step."
  9. Emit a single JSON object following the schema in references/outline-schema.md. Cross-check against references/outline_schema.json (machine-readable).
  10. Save to workspace/outline.json.
  11. Validate: ```bash python skills/outline-agent/scripts/validate_outline.py workspace/outline.json ``` If validation fails, fix the JSON and re-validate. Do not proceed to Step 2 or Step 3 with an invalid outline — every downstream agent depends on this schema.
  1. Append §1 to research_brief.md (see skills/shared/research_brief_template.md):

After outline.json passes validation, append the §1 section to workspace/research_brief.md (create the file if absent). Template:

```markdown ## §1 · Core Claim and Narrative _Written by: outline-agent, Step 1_

Core claim: <one-sentence contribution> Narrative tension: <gap this paper resolves> Key novelty framing: <how the contribution is framed relative to prior work> Outline decisions:

  • Plotting plan: <N> figures
  • Related Work clusters: <names>
  • Section structure: <section titles> Potential weaknesses flagged at outline stage:
  • <any claim in idea.md that may be hard to support> ```

This is a free-form prose append; no machine-readable schema required.

Hard rules from the prompt (do not violate)

These are excerpted from references/prompt.md. The validator enforces them.

Plotting plan (Directive 1)
  • plot_type MUST be exactly one of "plot" or "diagram".
  • data_source MUST be exactly one of "idea.md", "experimental_log.md", or "both".
  • aspect_ratio MUST be exactly one of: "1:1", "1:4", "2:3", "3:2", "3:4", "4:1", "4:3", "4:5", "5:4", "9:16", "16:9", "21:9".
  • figure_id MUST be a semantically meaningful snake_case identifier (e.g., fig_framework_overview, fig_ablation_study_parameter_sensitivity).
  • figure_id MUST NOT contain the word "Figure".
Intro / Related Work strategy (Directive 2)
  • Strictly separate Introduction (macro-level context, 10-20 papers, foundational + survey + impact) from Related Work (micro-level technical baselines, 30-50 papers, divided into 2-4 methodology clusters that directly compete with or precede the proposed approach).
  • For each Related Work cluster: provide methodology_cluster, sota_investigation_mission, limitation_hypothesis, limitation_search_queries, bridge_to_our_method.
  • CRITICAL TIMELINE RULE: Do not instruct searches for any papers published after {cutoff_date}. Derive cutoff_date from conference_guidelines.md (e.g., "ICLR 2025 → cutoff October 2024", "CVPR 2025 → cutoff November 2024"). If unspecified, default to one month before today's date.
Section plan (Directive 3)
  • Structural hierarchy: if Subsection X.1 is created, X.2 is mandatory. No orphaned subsections. Omit subsections entirely if a section does not require division.
  • Content specificity: each content_bullets entry must reference source materials concretely. AVOID "Describe the model". REQUIRE "Formalize the Temporal-Aware Attention mechanism using Eq. 3 from idea.md."
  • Mandatory citations: every dataset, optimizer, metric, and foundational architecture/model mentioned in idea.md or experimental_log.md MUST have a citation hint, no matter how ubiquitous (e.g., AdamW, ResNet, ImageNet, CLIP, Transformer, LLaMA, GPT, LLaVA).
  • Citation hint format:
  • If you know the exact author and title: "Author (Exact Paper Title)"
  • Otherwise: "research paper or technical report introducing '[Exact Model/Dataset/Metric Name]'"
  • Do NOT guess or hallucinate authors.
Output

Exactly one file: workspace/outline.json. No prose, no code blocks, no markdown. The Section Writing Agent and Literature Review Agent will parse this JSON directly.

See references/example-output.json for a complete worked example from the paper (App. F.1, pp. 43–44).

Resources
  • references/prompt.md — verbatim Outline Agent prompt from App. F.1
  • references/outline-schema.md — prose explanation of the schema
  • references/outline_schema.json — machine-readable JSON Schema
  • references/example-output.json — example output from the paper
  • references/allowed-values.md — enumerated allowed values for each enum field
  • scripts/validate_outline.py — JSON Schema validator
  • skills/shared/research_brief_template.mdNEW §1 schema; append after outline.json passes validation
按 MIT 许可原样转载,未经改动 · 在 GitHub 查看 →

评论

登录即可评论;带「已验证安装」的,是发布者名下有本店的安装或持有记录。