Agent skill

concept-graph

Build a concept graph (nodes + prerequisite edges) from a tutorial spec, saving as `outline/concept_graph.yml`. **Trigger**: concept graph, prerequisite graph, dependency graph, 概念图, 先修关系. **Use when**: tutorial pipeline 的结构阶段(C2),需要把教程知识点拆成可排序的依赖图(在写教程 prose 前)。 **Skip if**: 还没有 tutorial spec(例如缺少 `output/TUTORIAL_SPEC.md`)。 **Network**: none. **Guardrail**: 只做结构;避免写长 prose 段落。

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Install this agent skill to your Project

npx add-skill https://github.com/WILLOSCAR/research-units-pipeline-skills/tree/main/.codex/skills/concept-graph

SKILL.md

Concept Graph (prerequisites)

Goal: represent tutorial concepts as a prerequisite DAG so modules can be planned and ordered.

Inputs

  • output/TUTORIAL_SPEC.md

Outputs

  • outline/concept_graph.yml

Output schema (recommended)

A minimal, readable YAML schema:

  • nodes: list of {id, title, summary}
  • edges: list of {from, to} meaning from is a prerequisite of to

Constraints:

  • Graph should be acyclic (DAG).
  • Prefer 10–30 nodes for a medium tutorial.

Workflow

  1. Read output/TUTORIAL_SPEC.md and extract the concept list implied by objectives + running example.
  2. Normalize each concept into a node with a stable id.
  3. Add prerequisite edges and verify the graph is acyclic.
  4. Write outline/concept_graph.yml.

Definition of Done

  • outline/concept_graph.yml exists and is a DAG.
  • Nodes cover all learning objectives from output/TUTORIAL_SPEC.md.
  • Node titles are specific (not “misc”).

Troubleshooting

Issue: the graph looks like a linear list

Fix:

  • Add intermediate prerequisites explicitly (e.g., “data model” before “evaluation protocol”).

Issue: cycles appear (A → B → A)

Fix:

  • Split concepts or redefine edges so prerequisites flow in one direction.

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WILLOSCAR/research-units-pipeline-skills

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WILLOSCAR/research-units-pipeline-skills

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维护中文毕业论文的 `codex_md/question_list.md`:把本轮问题、边界、优先级、协作方案和验收口径结构化,作为整条 thesis pipeline 的控制面。 **Trigger**: 毕业论文问题清单, thesis question list, 论文修改清单, 本轮目标, 结构问题梳理, review问题整理. **Use when**: 你已经有一批材料或上一轮 review 结果,需要明确这一轮到底修什么、不修什么,并给后续重构与编译复查提供统一入口。 **Skip if**: 当前只是在做一次性局部措辞修改,且没有形成新一轮结构/证据/编译问题。 **Network**: none. **Guardrail**: 不在这里写正文;不把问题单写成长篇散文;每条问题必须可执行、可验收。

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WILLOSCAR/research-units-pipeline-skills

novelty-matrix

Create a novelty/prior-work matrix comparing the submission’s contributions against related work (overlaps vs deltas). **Trigger**: novelty matrix, prior-work matrix, overlap/delta, 相关工作对比, 新颖性矩阵. **Use when**: peer review 中评估 novelty/positioning,需要把贡献与相关工作逐项对齐并写出差异点证据。 **Skip if**: 缺少 claims(先跑 `claims-extractor`)或你不打算做新颖性定位分析。 **Network**: none (retrieval of additional related work is out-of-scope unless provided). **Guardrail**: 明确 overlap 与 delta;尽量给出可追溯证据来源(来自稿件/引用/作者陈述)。

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WILLOSCAR/research-units-pipeline-skills

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WILLOSCAR/research-units-pipeline-skills

rubric-writer

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