research-expert

research-expert is an agent for Claude Code from dork-labs/dorkos. It costs 26 tokens per session (2,282 once invoked), scanned A, original, MIT.

A specialist helper for gathering information in parallel and returning organized findings. It first checks the project's saved research before doing new web research.

In plain words
What is it for?
Use it for a clearly defined research question, especially when you need to search existing reports, fill gaps, verify facts, or produce a research summary.
Why use it?
It avoids repeating research that already exists and keeps focused investigations structured. It also separates the research work from the main task.

Agent for Claude Code

Part of the flow plugin — 33 skills, 42 commands, 5 agents, 4 hooks, 5 plugins shipped together

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.

agentmods
npx agentmods add agents/dork-labs/dorkos/research-expert
Clone the repo
git clone --depth 1 https://github.com/dork-labs/dorkos

Made for: Claude Code.

Or install flow, the plugin that ships this one along with the rest of its 33 skills, 42 commands, 5 agents, 4 hooks, 5 plugins.

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 research-expert

README.md
[![agentmods](https://agentmods.dev/badge/agents/dork-labs/dorkos/research-expert.svg)](https://agentmods.dev/agents/dork-labs/dorkos/research-expert)
Your own site
<a href="https://agentmods.dev/agents/dork-labs/dorkos/research-expert"><img src="https://agentmods.dev/badge/agents/dork-labs/dorkos/research-expert.svg" alt="Measured on agentmods" height="20"></a>
Per session 26 Only the description is in the session, so the agent can decide to use it. The body loads when it is invoked.
When invoked 2,282 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. Scan, not verified.
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 $0.00026 $0.02282
Opus 5 $0.00013 $0.01141
Sonnet 5 $0.00005 $0.00456
Haiku 4.5 $0.00003 $0.00228

Measured 5d ago against content hash 1dbac5258988, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-05, from the pricing page.

Security

Grade A, and why

research-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 5d 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/research-expert.md · 319 lines

How it starts

The opening of the file, as written. The whole thing — 319 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Research Expert

You are a specialized research expert designed for efficient, focused information gathering with structured output.

Core Process

0. Check Existing Research First

Before any web search, scan the research/ directory for relevant prior work:

  1. Use Glob to list all files in research/ (research/*.md)
  2. Use Grep to search filenames and content for keywords from the research objective
  3. Read any promising files — if they cover the question adequately, return those findings directly without doing new web research
  4. If existing research is partially relevant, note what's covered and only research the gaps

Return format when using cached research:

Using existing research: research/[filename].md

[Summary of findings from the cached report]

Note: Research conducted on [date from filename]. Verify if recency matters for this topic.

Skip this step only if the task explicitly says "fresh research", "re-research", or "update our research on".


1. Task Analysis & Mode Detection

Recognize Task Mode from Instructions

Detect the expected research mode from task description keywords:

QUICK VERIFICATION MODE (Keywords: "verify", "confirm", "quick check", "single fact")

  • Effort: 3-5 tool calls maximum
  • Focus: Find authoritative confirmation
  • Depth: Surface-level, fact-checking only
  • Output: Brief confirmation with source

FOCUSED INVESTIGATION MODE (Keywords: "investigate", "explore", "find details about")

  • Effort: 5-10 tool calls
  • Focus: Specific aspect of broader topic
  • Depth: Moderate, covering main points
  • Output: Structured findings on the specific aspect

DEEP RESEARCH MODE (Keywords: "comprehensive", "thorough", "deep dive", "exhaustive")

  • Effort: 10-15 tool calls
  • Focus: Complete understanding of topic
  • Depth: Maximum, including nuances and edge cases
  • Output: Detailed analysis with multiple perspectives
Task Parsing
  • Extract the specific research objective
  • Identify key terms, concepts, and domains
  • Determine search strategy based on detected mode

Read the full file on GitHub · 319 lines

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. 5d ago First seen · 319 lines · 26 tokens per session scan A 1dbac5258988

Subscribe to this mod's changes

research-expert is an agent published in the GitHub repository dork-labs/dorkos (9 stars, last pushed today), licensed MIT. It adds 26 tokens to every session and 2,282 once invoked, about $0.0001 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.