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 skills add woliveiras/geremmyas --skill chromadb-rag-workflowgit clone --depth 1 https://github.com/woliveiras/geremmyasWrote 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/woliveiras/geremmyas/chromadb-rag-workflow)<a href="https://agentmods.dev/skills/woliveiras/geremmyas/chromadb-rag-workflow"><img src="https://agentmods.dev/badge/skills/woliveiras/geremmyas/chromadb-rag-workflow/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/woliveiras/geremmyas/chromadb-rag-workflow"><img src="https://agentmods.dev/badge/skills/woliveiras/geremmyas/chromadb-rag-workflow.svg" alt="Reviewed on agentmods" width="80" 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 | $0.00052 | $0.00314 |
| Opus 5 | $0.00026 | $0.00157 |
| Sonnet 5 | $0.00010 | $0.00063 |
| Haiku 4.5 | $0.00005 | $0.00031 |
Grade A, and why
chromadb-rag-workflow 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 11d 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
ChromaDB RAG Workflow
Build Chroma-backed retrieval with stable collections, metadata, and evaluation.
Process
- Identify source documents, update cadence, tenancy/security boundaries, and retrieval success criteria.
- Choose
PersistentClientorHttpClientbased on deployment shape. - Define collection naming, embedding function/model, document IDs, and metadata schema.
- Choose chunking and normalization before ingestion.
- Ingest with stable IDs and metadata needed for filters and debugging.
- Add retrieval tests for expected matches, metadata filters, no-match cases, and stale/deleted document behavior.
- Document backup, rebuild, and re-embedding strategy.
- Keep retrieval metrics or qualitative eval examples close to the feature.
Rules
- Do not change embedding model for an existing collection without a re-embedding plan.
- Do not delete/recreate persistent collections as normal cleanup.
- Do not rely on vector similarity alone when tenant, document type, or freshness filters are known.
- Keep source documents recoverable so vector data can be rebuilt.
Output
- Collection and metadata design
- Ingestion/retrieval flow
- Persistence and backup plan
- Retrieval evaluation checklist
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.
- 11d ago First seen · 40 lines · 52 tokens per session scan A cdb8f95ea691
chromadb-rag-workflow is a skill published in the GitHub repository woliveiras/geremmyas (10 stars, last pushed 1mo ago), licensed MIT. It adds 52 tokens to every session and 314 once invoked, about $0.0003 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 2026-08-31.
Other skills, from other repositories
embeddings
Vector embeddings with HNSW indexing, sql.js persistence, and hyperbolic support. 75x faster with agentic-flow integration. Use when: semantic search, pattern matching, similarity queries, knowledge retrieval. Skip when: exact text matching, simple lookups, no semantic understanding needed.
agent-platform-rag-engine-management
Manage and query Agent Platform RAG Engine Corpora and retrieve grounded contexts using the Google GenAI SDK. Use when listing RAG corpora or files, inspecting a corpus, retrieving contexts, or generating content grounded in a RAG corpus. Do not use for standard database queries (use SQL/Spanner skills), Google…
llm-app-patterns
Production-ready patterns for building LLM applications. Covers RAG pipelines, agent architectures, prompt IDEs, and LLMOps monitoring. Use when designing AI applications, implementing RAG, building agents, or setting up LLM observability.
9router-embeddings
Generate vector embeddings via 9Router /v1/embeddings using OpenAI / Gemini / Mistral / Voyage / Nvidia / GitHub embedding models for RAG, semantic search, similarity. Use when the user wants embeddings, vectors, RAG, semantic search, or to embed text.
azure-search-documents-dotnet
Azure AI Search SDK for .NET (Azure.Search.Documents). Use for building search applications with full-text, vector, semantic, and hybrid search. Covers SearchClient (queries, document CRUD), SearchIndexClient (index management), and SearchIndexerClient (indexers, skillsets). Triggers: "Azure Search .NET"…
browserwing-admin
Manage and operate BrowserWing — an intelligent browser automation platform. Install dependencies, configure LLM, create/manage/execute automation scripts, use AI-driven exploration to generate scripts, browse the script marketplace, and troubleshoot issues.