data-retriever

data-retriever is an agent for Claude Code from davebream/claude-of-alexandria. It costs 32 tokens per session (5,210 once invoked), scanned A, original, GPL-3.0.

A data-gathering agent for biblical passages. It retrieves information about word forms, sentence or argument structure, vocabulary, and quoted material, then condenses it into structured summaries.

In plain words
What is it for?
Use it when a task needs summarized language, discourse, vocabulary, or quotation information from a biblical passage.
Why use it?
No further details are provided about its exact data sources or output format, so its broader use cannot be stated reliably.

Agent for Claude Code

Written for Claude Code: shipped in a Claude Code plugin. Also seen: model in frontmatter.

Part of the claude-of-alexandria plugin — 8 skills, 13 agents shipped together

Good fit Use it when a task needs summarized language, discourse, vocabulary, or quotation information from a biblical passage.

Compare 6 agents from other repositories ↓
Install with agentmods
npx agentmods add agents/davebream/claude-of-alexandria/data-retriever
Install

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.

Clone the repo
git clone --depth 1 https://github.com/davebream/claude-of-alexandria

Made for: Claude Code.

Or install claude-of-alexandria, the plugin that ships this one along with the rest of its 8 skills, 13 agents.

Wrote 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.

agentmods badge for data-retriever

README.md
[![agentmods](https://agentmods.dev/badge/agents/davebream/claude-of-alexandria/data-retriever/github.svg)](https://agentmods.dev/agents/davebream/claude-of-alexandria/data-retriever)
Your own site
<a href="https://agentmods.dev/agents/davebream/claude-of-alexandria/data-retriever"><img src="https://agentmods.dev/badge/agents/davebream/claude-of-alexandria/data-retriever/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.

agentmods 80×15 button for data-retriever

Your own site · 80×15
<a href="https://agentmods.dev/agents/davebream/claude-of-alexandria/data-retriever"><img src="https://agentmods.dev/badge/agents/davebream/claude-of-alexandria/data-retriever.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 32 Only the description is in the session, so the agent can decide to use it. The body loads when it is invoked.
When invoked 5,210 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe.
Origin unknown No closer match found in the catalogue.
Token cost

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.

ModelPer sessionOnce invoked
Fable 5.1 $0.00032 $0.05210
Opus 5 $0.00016 $0.02605
Sonnet 5 $0.00006 $0.01042
Haiku 4.5 $0.00003 $0.00521

Measured 11d ago against content hash 506f361ae90c, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-11, from the pricing page.

Security

Grade A, and why

data-retriever 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.

plugins/claude-of-alexandria/agents/data-retriever.md · 263 lines

The source is not reproduced here

Licensed GPL-3.0

The repository is licensed GPL-3.0, which this catalogue does not treat as permission to reproduce the file. Read it at the source.

Read it on GitHub

Changes

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.

  1. 11d ago First seen · 263 lines · 32 tokens per session scan A 506f361ae90c

Subscribe to this mod's changes

data-retriever is an agent published in the GitHub repository davebream/claude-of-alexandria (7 stars, last pushed today), licensed GPL-3.0. It adds 32 tokens to every session and 5,210 once invoked, about $0.0002 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.

Related

Other agents, from other repositories

langchain4j-ai-development-expert

Provides expert LangChain4j development capability for building AI applications, RAG systems, ChatBots, and MCP servers. Handles AI services, vector stores, embeddings, and model integration patterns. Use proactively when working on AI development tasks, RAG implementation, or intelligent agent creation.

giuseppe-trisciuoglio/developer-kit · 65 tokens

wiki-qa-probe

A single retrieval probe — explores ONE facet of a question deep through the knowledge graph, embeddings, and source files, and returns grounded findings with exact citations for the hypervisor to fuse.

bearlike/Assistant · 43 tokens

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…

acaprino/daodan · 91 tokens

FAI LangChain Expert

LangChain framework specialist — LCEL expression language, chains, agents with tool use, retrievers, memory, callbacks, LangSmith tracing, and production RAG pipeline patterns.

frootai/frootai · 41 tokens

rag-evaluator

Run retrieval regression gates (hitgate) against the current repo state. Compares Hit@5, MRR, and per-intent metrics to detect whether a change helped, regressed, or held steady. Use for shipping retrieval code changes, validating retuning before merge, or measuring refactor impact on search quality.

LucasSantana-Dev/sharekit · 68 tokens

ai-platform-architect

Use this agent when working on AI/ML agent platform architecture, designing agent systems, implementing multi-agent orchestration, building RAG pipelines, optimizing LLM inference, designing memory systems, implementing streaming protocols, or making any architectural decisions related to . This includes agent…

asiflow/claude-nexus-hyper-agent-team · 778 tokens