AutoRAG-Research: Agent for Claude Code

.claude/agents/implementation-specialist.md

implementation-specialist is an agent for Claude Code from NomaDamas/AutoRAG-Research. It costs 395 tokens per session (456 once invoked), scanned A, original, Apache-2.0.

An implementation agent that turns an approved design into a Python data ingestor for AutoRAG-Research. A data ingestor loads an external dataset into the project's database.

In plain words
What is it for?
Use it to implement ingestors for datasets from sources such as Hugging Face, local files, or APIs, including their required methods.
Why use it?
It keeps the implementation aligned with an existing architecture instead of making unrelated design decisions. This helps convert a documented ingestion plan into working service-layer code.

Agent for Claude Code

Written for Claude Code: installed under .claude/. Also seen: model in frontmatter.

This is NomaDamas/AutoRAG-Research's own configuration. It tells Claude Code how to work on AutoRAG-Research itself, so it is not a mod to install elsewhere. Copy it as a starting point and replace the rules that are about this project. Everything AutoRAG-Research configures →

Reuse

Borrowing it

Nothing to install: this file belongs to NomaDamas/AutoRAG-Research. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.

Copy the file
curl -O https://raw.githubusercontent.com/NomaDamas/AutoRAG-Research/main/.claude/agents/implementation-specialist.md
Clone the repo
git clone --depth 1 https://github.com/NomaDamas/AutoRAG-Research

Made for: Claude Code.

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 implementation-specialist

README.md
[![agentmods](https://agentmods.dev/badge/agents/nomadamas/autorag-research/implementation-specialist/github.svg)](https://agentmods.dev/agents/nomadamas/autorag-research/implementation-specialist)
Your own site
<a href="https://agentmods.dev/agents/nomadamas/autorag-research/implementation-specialist"><img src="https://agentmods.dev/badge/agents/nomadamas/autorag-research/implementation-specialist/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 implementation-specialist

Your own site · 80×15
<a href="https://agentmods.dev/agents/nomadamas/autorag-research/implementation-specialist"><img src="https://agentmods.dev/badge/agents/nomadamas/autorag-research/implementation-specialist.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 395 Only the description is in the session, so the agent can decide to use it. The body loads when it is invoked.
When invoked 456 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 original 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 $0.00395 $0.00456
Opus 5.5 $0.00158 $0.00182
Sonnet 5.5 $0.00079 $0.00091
Haiku 4.5 $0.00040 $0.00046

Measured 2mo ago against content hash e40027996ead, method: parsed. Prices are Anthropic first-party input rates as of 2026-10-07, from the pricing page.

Security

Grade A, and why

implementation-specialist 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 2mo 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.

.claude/agents/implementation-specialist.md · 14 lines

What it actually says

Read and follow ai_instructions/implementation_specialist.md.

Task:

  • Implement the ingestor described in Mapping_Strategy.md
  • Write code in autorag_research/data/
  • Follow service-layer patterns only
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. 2mo ago First seen · 14 lines · 0 tokens per session scan A e40027996ead

Subscribe to this mod's changes

implementation-specialist is an agent published in the GitHub repository NomaDamas/AutoRAG-Research (151 stars, last pushed 2mo ago), licensed Apache-2.0. It adds 395 tokens to every session and 456 once invoked, about $0.0016 per session on Opus 5.5. 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 2026-08-30.

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