La interfaz está localizada; las descripciones y documentos de las Skills se traducen automáticamente con IA a su idioma. El código, los comandos, rutas y términos técnicos se mantienen en el original, y prevalece el documento del autor.
Explorar Skills
Datos e investigación · 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

Documentación 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 guardadas