● Сообщество
cocoindex-io
⚡ Сразу
cocoindex-claude
автор cocoindex-io · cocoindex-io/cocoindex-claude
Teaches Claude Code how to build CocoIndex data-transformation pipelines — real-time incremental processing for vector DBs and knowledge graphs.
CocoIndex is a real-time data transformation framework for AI pipelines (source → transform → vector DB / knowledge graph). This skill loads its conventions into Claude Code so the model writes idiomatic CocoIndex flows, custom functions, and CLI/API commands instead of guessing at an unfamiliar library.
Зачем использовать
Ключевые функции
- Drop-in knowledge of CocoIndex flow definitions, sources, and sinks
- Guidance on writing custom transformation functions correctly
- Claude picks the right CLI vs programmatic API based on task
- Understands incremental processing semantics so it doesn't suggest full rebuilds
- Official — authored by the CocoIndex team
Живое демо
Как выглядит на практике
cocoindex-claude-skill.replay
▶ готово
Сценарии использования
Реальные сценарии: cocoindex-claude
Когда использовать: You've read the CocoIndex homepage and want Claude to scaffold a working flow instead of copy-pasting tutorials.
Поток
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Describe the pipeline
Use the cocoindex skill — scaffold a flow that watches ./docs, chunks markdown, embeds with OpenAI, writes to Qdrant.✓ Скопировано
→ Claude generates a flow.py with @cocoindex.flow_def and the right source/transform/export calls
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Run and verify
Now show me the exact CLI commands to build, run, and incrementally update this flow.✓ Скопировано
→ cocoindex setup / update / eval commands in the correct order
Итог: A working flow.py plus the commands to run it — no more guessing at the CocoIndex decorator surface.
Подводные камни
- Claude invents APIs that don't exist in CocoIndex — Explicitly prompt 'use only APIs documented in the cocoindex skill' — hallucination drops when the skill is in scope
Когда использовать: Built-in transforms don't cover your parsing / enrichment step.
Поток
-
Describe the transform
With the cocoindex skill — write a @cocoindex.op.function that takes a PDF path, extracts tables, returns structured rows.✓ Скопировано
→ Idiomatic function signature with correct typed inputs/outputs
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Wire it into the flow
Now plug this into my existing flow at the chunking stage.✓ Скопировано
→ Diff against current flow.py with the new op in place
Итог: A custom transform that obeys CocoIndex's incremental semantics.
Подводные камни
- Function returns non-deterministic output, breaking incremental processing — Skill reminds Claude that transforms must be pure — if you hit this, re-read the incremental section
Комбинации
Сочетайте с другими MCP — эффект x10
Let Claude actually write the flow.py file to disk, not just print it in chat
Scaffold the CocoIndex flow and save it to ./pipelines/docs_to_qdrant.py.✓ Скопировано
Pipe CocoIndex output into a Postgres vector store and query it from the same session
Build the flow targeting pgvector, then run a retrieval query against it.✓ Скопировано
Стоимость и лимиты
Во что обходится
- Квота API
- None
- Токенов на вызов
- Modest — skill loads reference material only when relevant
- Деньги
- Free — skills are local files
- Совет
- CocoIndex itself is free; costs come from your embedding model and vector DB, not this skill.
Безопасность
Права, секреты, радиус поражения
Хранение учётных данных: No credentials — pure prompts
Исходящий трафик: None from the skill itself. Your pipeline calls whichever embedding / DB services you configure.
Устранение неполадок
Частые ошибки и исправления
Wrong trigger keywords — Claude writes generic Python instead of CocoIndex
Mention CocoIndex explicitly, or say 'scaffold a cocoindex flow_def'.
Альтернативы
cocoindex-claude в сравнении
| Альтернатива | Когда использовать | Компромисс |
| LlamaIndex skills | You want LlamaIndex's retrieval abstractions instead of CocoIndex's transform-centric model | Different mental model — LlamaIndex is retrieval-first, CocoIndex is pipeline-first |
| Hand-written Python | You need one-off processing and don't want incremental state | No incremental rebuilds, no framework conventions |