L’interface est localisée ; les présentations et documents des Skills sont traduits automatiquement par IA dans votre langue. Le code, les commandes, chemins et termes techniques restent en version originale, et le document de l’auteur fait foi.
Explorer les Skills
Données et recherche · SKILL.md

graph-query-and-data-management

graph-query-and-data-management

Operate the Agriculture KnowledgeGraph Neo4j graph import/query, CSV schemas, hierarchy tree, and vector utilities.

Independent GitHub snapshot · Automated classification · Original documentation governs

Documentation de la Skill

GitHub

name: graph-query-and-data-management description: "Operate the Agriculture KnowledgeGraph Neo4j graph import/query, CSV schemas, hierarchy tree, and vector utilities." disable-model-invocation: true metadata: disco-role: operating license: GPL 3.0

Graph Query and Data Management

Use this sub-skill when the task is about the Agriculture KnowledgeGraph data model rather than the web UI or model-training pipelines.

Use this for

  • Planning or debugging Neo4j imports for Hudong, Wikidata, attribute, weather, and city-climate CSV artifacts.
  • Understanding graph labels, relationship types, and relation-search semantics.
  • Translating or modernizing the repo's Neo4j wrapper query methods safely.
  • Inspecting CSV field meanings, delimiter quirks, and hierarchy/vector utility input formats.
  • Running a tiny non-repo smoke check of the hierarchy tree behavior.

Route elsewhere

  • Django service startup, URL/view behavior, form fields, and preload side effects: use ../web-app-service/.
  • THULAC entity recognition, predicted labels, KNN, or fastText files: use ../entity-labeling-and-ner/.
  • Scrapy crawlers, Wikidata conversion scripts, and weather data acquisition: use ../crawlers-and-wikidata-pipelines/.
  • PCNN relation extraction datasets, Mongo annotation data, or TensorFlow training: use ../relation-extraction-pipeline/.

Read first

Bundled helpers

  • Tree API smoke check creates temporary edge/leaf fixtures and asserts source-compatible hierarchy behavior without importing the original checkout.
  • Cypher import templates provides adaptable LOAD CSV templates that use Neo4j import-directory file URLs, not machine-local absolute paths.

Operating cautions

  • Treat live Neo4j, MongoDB, the Django service, large word-vector files, and network crawls as external prerequisites unless a task explicitly provisions them.
  • The historical source concatenates Cypher strings. When writing new code, prefer parameterized queries and preserve exact label/relationship semantics.
  • The source is old and un-packaged; use these references as operating guidance and keep runtime work self-contained.
Skills enregistrées