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survey-seed-harvest

@WILLOSCAR/research-units-pipeline
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SKILL.md

name survey-seed-harvest
description Identify survey/review papers in a retrieved set and extract taxonomy seeds into `outline/taxonomy.yml` (topics/subtopics/terminology). **Trigger**: survey seed harvest, taxonomy seeds, 从 survey 提 taxonomy, bootstrap taxonomy. **Use when**: retrieval/dedup 后想快速从已有 survey/review 论文中提取术语与主题结构，用于加速 `taxonomy-builder`。 **Skip if**: 已经有高质量 taxonomy（或你不想被 survey 既有框架限制）。 **Network**: none. **Guardrail**: 产物是 seed，必须经 `taxonomy-builder` 重写与对齐 scope；避免生成泛化占位节点。

Survey Seed Harvest

Bootstrap taxonomy seeds from existing survey/review papers inside your retrieved set.

This is an accelerator for the early structure stage: it should make taxonomy-builder easier, not replace it.

Inputs

  • papers/papers_dedup.jsonl (deduped paper metadata with titles/abstracts)

Outputs

  • outline/taxonomy.yml (seed taxonomy; expected to be refined)

Workflow (heuristic)

Uses: papers/papers_dedup.jsonl.

  1. Find likely survey/review papers:
    • title/abstract contains “survey”, “review”, “systematic”, “meta-analysis”
  2. Extract candidate topic terms and group them into:
    • ~4–10 top-level nodes (“chapters”)
    • 2–6 children per node (mappable leaves)
  3. Write short, actionable descriptions:
    • what belongs here / what does not
    • (optional) list 2–5 representative titles as seeds
  4. Treat the result as a starting point:
    • pass it to taxonomy-builder for domain-meaningful rewriting and scope alignment.

Quality checklist

  • outline/taxonomy.yml exists and is valid YAML.
  • Taxonomy has at least 2 levels (children used) and every node has a description.
  • Avoid generic placeholder nodes like “Overview/Benchmarks/Open Problems” unless they are truly content-based for your domain.

Script (optional helper)

Quick Start

  • python .codex/skills/survey-seed-harvest/scripts/run.py --help
  • python .codex/skills/survey-seed-harvest/scripts/run.py --workspace <workspace_dir>

All Options

  • --top-k <n>: number of candidate terms to consider
  • --min-freq <n>: minimum frequency threshold

Examples

  • More conservative term selection:
    • python .codex/skills/survey-seed-harvest/scripts/run.py --workspace <ws> --top-k 80 --min-freq 3

Notes

  • This helper is keyword-based; treat the output as seeds and refine with taxonomy-builder.