Ingests repository files into the ChromaDB vector store. Builds or updates the vector index from a manifest or directory scan using ingest.py. Use when new files need to be indexed or the vector store is out of date. <example> user: "Index these new plugin files into the vector database" assistant: "I'll use vector-db-ingest to add them to the vector store." </example> <example> user: "The vector store is missing recent files -- update it" assistant: "I'll use vector-db-ingest to re-index the changes." </example>
From vector-dbnpx claudepluginhub richfrem/agent-plugins-skills --plugin vector-dbThis skill is limited to using the following tools:
assets/resources/architecture_sequence.mmdassets/resources/deployment_model.mmdassets/resources/rag_design_choices.mdassets/resources/stabilizers/README.mdassets/resources/stabilizers/vector_consistency_check.mdevals/evals.jsonevals/results.tsvrequirements.inrequirements.txtscripts/ingest.pyscripts/ingest_code_shim.pyscripts/init.pyscripts/operations.pyscripts/query.pyscripts/vector_config.pyscripts/vector_consistency_check.pyGuides Payload CMS config (payload.config.ts), collections, fields, hooks, access control, APIs. Debugs validation errors, security, relationships, queries, transactions, hook behavior.
Designs KPI dashboards with metrics selection (MRR, churn, LTV/CAC), visualization best practices, real-time monitoring, and hierarchy for executives, operations, and product teams.
Transforms raw data into narratives with story structures, visuals, and frameworks for executive presentations, analytics reports, and stakeholder communications.
This skill requires Python 3.8+ and standard library only. No external packages needed.
To install this skill's dependencies:
pip-compile ./requirements.in
pip install -r ./requirements.txt
See ./requirements.txt for the dependency lockfile (currently empty — standard library only).
You ingest (index) repository files into the ChromaDB vector store so they can be semantically
searched. You build or update the parent-child chunk structure that query.py searches against.
This is a write operation. The vector store is the backing index for Phase 2 search.
If chromadb is not installed or vector_profiles.json is missing, run the init skill first:
python3 ./scripts/init.py
Use the vector-db-launch skill if the server is not already up:
# Check heartbeat
curl -sf http://127.0.0.1:8110/api/v1/heartbeat
# If not running, start it:
chroma run --host 127.0.0.1 --port 8110 --path .vector_data &
See SKILL.md for full launch instructions.
python3 ./scripts/ingest.py \
--profile knowledge --full
python3 ./scripts/ingest.py \
--profile knowledge --since 24
python3 ./scripts/ingest.py \
--profile knowledge --full --code
ingest_code_shim.py is invoked automatically for .py and .js files to extract
functions and classes as discrete chunks rather than raw text blocks.
Run a quick smoke test to confirm the new content is retrievable:
python3 ./scripts/query.py \
"describe what was just ingested" --profile knowledge --limit 3
.vector_data/ directly -- always use ingest.py..sqlite3 files with cat or sqlite3 -- will corrupt context.