Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx agentmods add skills/richfrem/agent-plugins-skills/vector-db-ingestnpx skills add richfrem/agent-plugins-skills --skill vector-db-ingestgit clone --depth 1 https://github.com/richfrem/agent-plugins-skillsWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/skills/richfrem/agent-plugins-skills/vector-db-ingest)<a href="https://agentmods.dev/skills/richfrem/agent-plugins-skills/vector-db-ingest"><img src="https://agentmods.dev/badge/skills/richfrem/agent-plugins-skills/vector-db-ingest.svg" alt="Measured on agentmods" height="20"></a>What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00122 | $0.00581 |
| Opus 5 | $0.00061 | $0.00291 |
| Sonnet 5 | $0.00024 | $0.00116 |
| Haiku 4.5 | $0.00012 | $0.00058 |
Grade A, and why
vector-db-ingest scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 2d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
What it actually says
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.
What ships with it
16 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
- assets/resources/architecture_sequence.mmd 53 B
- assets/resources/deployment_model.mmd 48 B
- assets/resources/rag_design_choices.md 50 B
- assets/resources/stabilizers/README.md 53 B
- assets/resources/stabilizers/vector_consistency_check.md 71 B
- evals/evals.json 956 B
- evals/results.tsv 172 B
- requirements.in 21 B
- requirements.txt 22 B
- scripts/ingest_code_shim.py 36 B runs code
- scripts/ingest.py 26 B runs code
- scripts/init.py 24 B runs code
- scripts/operations.py 30 B runs code
- scripts/query.py 25 B runs code
- scripts/vector_config.py 33 B runs code
- scripts/vector_consistency_check.py 44 B runs code
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 2d ago First seen · 75 lines · 122 tokens per session scan A 1438ceca3e74
vector-db-ingest is a skill published in the GitHub repository richfrem/agent-plugins-skills (6 stars, last pushed yesterday), licensed MIT. It adds 122 tokens to every session and 581 once invoked, about $0.0006 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-09-03.
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