richfrem/vector-db-ingest
plugins/vector-db/skills/vector-db-ingest/SKILL.md
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 Use when new files need to be indexed or the vector store is out of date.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>
$ install --global
skillsauthnpx skillsauth add richfrem/agent-plugins-skills vector-db-ingestInstall this skill globally with one command. Works with Claude Code, Cursor, and Windsurf.
Security Scan Results
3 of 9 scanners reported clean
Some scanners were skipped, did not run, or reported a non-clean status. Review each row below.
3
Scanners Passed
9
Scanners in report
Clean
TrivyContainer and dependency vulnerability scanner
95%
Clean
SemgrepStatic code analysis for vulnerabilities
95%
Clean
mcp-scan (Snyk)Model Context Protocol security validation
95%
Skipped
Snyk (dep)Open source security scanning
50%
Skipped
Socket.devSupply chain security analysis
50%
Skipped
VirusTotalMulti-engine malware detection
50%
Skipped
CrowdStrikeAdvanced threat intelligence
50%
Skipped
OSV-ScannerOpen Source Vulnerability database check
50%
Skipped
OWASP Dep-Check
50%
Last scanned: Apr 27, 2026, 7:58 AM109.8s10 files scanned
SKILL.md
- name:
- vector-db-ingest
- plugin:
- vector-db
- description:
- |
- user:
- The vector store is missing recent files -- update it
- assistant:
- I'll use vector-db-ingest to re-index the changes.
- allowed-tools:
- Bash, Read, Write
Dependencies
This skill requires the chromadb and langchain packages defined in the plugin root.
VDB Ingest Agent
Role
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.
High-Performance Mode: This skill uses a configurable batch processing engine (default 1,000 files) defined in .agent/learning/vector_profiles.json.
Prerequisites
1. First-time setup
If vector_profiles.json is missing, run the init skill first:
python ./scripts/init.py
2. Execution Mode
This plugin defaults to In-Process mode for zero-latency direct disk access. No background server is required unless explicitly configured in the profile.
Execution Protocol
Full ingest (first time or full rebuild)
Note: The --profile flag is mandatory to load the correct manifest and batch settings.
python ./scripts/ingest.py --profile wiki --full
Incremental ingest (only new/changed files since N hours)
python ./scripts/ingest.py --profile wiki --since 24
Single File/Folder Ingest
python ./scripts/ingest.py --profile wiki --file path/to/file.md
python ./scripts/ingest.py --profile wiki --folder path/to/folder
After Ingesting
Run a quick semantic search to confirm the new content is retrievable:
python ./scripts/query.py "search query" --profile wiki --limit 3
Rules
- Profile Sovereignty: Always pass
--profileto ensure the correct batch size and manifest are used. - In-Process Reliability: Ensure no other process is holding a lock on the database folder during ingestion.
- Source Transparency: State which profile was ingested, how many files, and any errors encountered.
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