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.
git clone --depth 1 https://github.com/OrcaQubits/agentic-commerce-skills-pluginsWrote 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/agents/orcaqubits/agentic-commerce-skills-plugins/nlweb-expert)<a href="https://agentmods.dev/agents/orcaqubits/agentic-commerce-skills-plugins/nlweb-expert"><img src="https://agentmods.dev/badge/agents/orcaqubits/agentic-commerce-skills-plugins/nlweb-expert/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/agents/orcaqubits/agentic-commerce-skills-plugins/nlweb-expert"><img src="https://agentmods.dev/badge/agents/orcaqubits/agentic-commerce-skills-plugins/nlweb-expert.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 | $0.00226 | $0.04323 |
| Opus 5 | $0.00113 | $0.02161 |
| Sonnet 5 | $0.00045 | $0.00865 |
| Haiku 4.5 | $0.00023 | $0.00432 |
Grade A, and why
nlweb-expert 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.
How it starts
The opening of the file, as written. The whole thing — 234 lines — stays where its author put it; the contents beside it link to each section on GitHub.
You are an expert in NLWeb — the open framework, announced by Satya Nadella at Microsoft Build 2025 and authored by R.V. Guha (creator of RSS / RDF / Schema.org), that turns any website into a conversational, agent-accessible "AI application." You help developers build production-grade NLWeb deployments on both the site operator side (exposing /ask and /mcp) and the agent integrator side (calling NLWeb endpoints as a tool source).
IMPORTANT: Live Documentation Rule
NLWeb is an actively evolving project. Releases are tracked as dated markdown files in docs/release_notes/, not semver tags. The codebase moves quickly — handler classes, config keys, and CLI flags change between releases. Before writing any implementation code:
- Always web-search for the latest README, docs, and release notes before coding.
- Always fetch live docs from the official sources below for exact config keys, JSON-RPC schemas, CLI flags, and module paths.
- Never assume a class name (
NLWebHandler,ToolSelector,db_load.py) or a config field is current — verify against the live repo first. - Cite the release date you are coding against in comments (e.g.,
# NLWeb release 2025-07-29).
Official Sources (fetch these before implementation)
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 · 234 lines · 226 tokens per session scan A 953a3dfe8736
nlweb-expert is an agent published in the GitHub repository OrcaQubits/agentic-commerce-skills-plugins (39 stars, last pushed 2d ago), licensed MIT. It adds 226 tokens to every session and 4,323 once invoked, about $0.0011 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 2026-09-15.
Other agents, from other repositories
qdrant-expert
Configure and operate the vector store in production. TRIGGER WHEN: creating Qdrant collections, tuning HNSW, quantization, dense plus sparse hybrid search, payload indexing, multi-tenancy, or Qdrant performance troubleshooting. DO NOT TRIGGER WHEN: end-to-end RAG design, or another vector database such as Pinecone…
FAI LangChain Expert
LangChain framework specialist — LCEL expression language, chains, agents with tool use, retrievers, memory, callbacks, LangSmith tracing, and production RAG pipeline patterns.
elasticsearch-observability
Our expert AI assistant for debugging code (O11y), optimizing vector search (RAG), and remediating security threats using live Elastic data.
Demonstrate
Agent for demonstrating VS Code features.
playwright-test-generator
Use this agent when you need to create automated browser tests using Playwright Examples: Context: User wants to generate a test for the test plan item.
code-reviewer
Performs thorough code reviews for the Notebooks in the Cookbook repo, focusing on Python/Jupyter best practices, and project-specific standards. Use this agent proactively after writing any significant code changes, especially when modifying notebooks, Github Actions, and scripts.