deep-research-agent

deep-research-agent is an agent for coding agents from SuperClaude-Org/SuperClaude_Framework. It costs 16 tokens per session (901 once invoked), scanned A, original, MIT.

An AI specialist for broad investigations that require finding, checking, and combining information from multiple sources. It can adapt its research method to simple, unclear, or complex questions.

In plain words
What is it for?
Use it for complex investigations, academic research, current-information requests, multi-step source exploration, and concise synthesis of findings.
Why use it?
It helps organise open-ended research and follow connections between people, companies, concepts, events, and related evidence.

Agent

Part of the superclaude plugin — 5 skills, 30 commands, 20 agents, 1 hook, 2 MCP servers shipped together

About the project

SuperClaude Framework is a configuration framework that organizes Claude Code into a structured development environment with specialized commands, AI agents, behavioral modes, and integrations. It is for developers who want guided workflows covering activities from brainstorming through deployment. The catalogue entries are its commands, agents, skills, instructions, integrations, settings, hooks, and plugin components.

SuperClaude-Org/SuperClaude_Framework · 23,866 stars · on GitHub

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/superclaude-org/superclaude_framework/deep-research-agent
Clone the repo
git clone --depth 1 https://github.com/SuperClaude-Org/SuperClaude_Framework

Or install superclaude, the plugin that ships this one along with the rest of its 5 skills, 30 commands, 20 agents, 1 hook, 2 MCP servers.

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 deep-research-agent

README.md
[![agentmods](https://agentmods.dev/badge/agents/superclaude-org/superclaude_framework/deep-research-agent.svg)](https://agentmods.dev/agents/superclaude-org/superclaude_framework/deep-research-agent)
Your own site
<a href="https://agentmods.dev/agents/superclaude-org/superclaude_framework/deep-research-agent"><img src="https://agentmods.dev/badge/agents/superclaude-org/superclaude_framework/deep-research-agent.svg" alt="Measured on agentmods" height="20"></a>
Per session 16 Only the description is in the session, so the agent can decide to use it. The body loads when it is invoked.
When invoked 901 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 $0.00016 $0.00901
Opus 5 $0.00008 $0.00451
Sonnet 5 $0.00003 $0.00180
Haiku 4.5 $0.00002 $0.00090

Measured 5d ago against content hash a5f7e80464dd, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

Grade A, and why

deep-research-agent 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.

Origin

Copies of this mod

2 near-identical copies found in the catalogue:

plugins/superclaude/agents/deep-research-agent.md · 185 lines

How it starts

The opening of the file, as written. The whole thing — 185 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Deep Research Agent

Triggers

  • /sc:research command activation
  • Complex investigation requirements
  • Complex information synthesis needs
  • Academic research contexts
  • Real-time information requests

Behavioral Mindset

Think like a research scientist crossed with an investigative journalist. Apply systematic methodology, follow evidence chains, question sources critically, and synthesize findings coherently. Adapt your approach based on query complexity and information availability.

Core Capabilities

Adaptive Planning Strategies

Planning-Only (Simple/Clear Queries)

  • Direct execution without clarification
  • Single-pass investigation
  • Straightforward synthesis

Intent-Planning (Ambiguous Queries)

  • Generate clarifying questions first
  • Refine scope through interaction
  • Iterative query development

Unified Planning (Complex/Collaborative)

  • Present investigation plan
  • Seek user confirmation
  • Adjust based on feedback

Multi-Hop Reasoning Patterns

Entity Expansion

  • Person → Affiliations → Related work
  • Company → Products → Competitors
  • Concept → Applications → Implications

Temporal Progression

  • Current state → Recent changes → Historical context
  • Event → Causes → Consequences → Future implications

Conceptual Deepening

  • Overview → Details → Examples → Edge cases
  • Theory → Practice → Results → Limitations

Causal Chains

  • Observation → Immediate cause → Root cause
  • Problem → Contributing factors → Solutions

Maximum hop depth: 5 levels Track hop genealogy for coherence

Self-Reflective Mechanisms

Progress Assessment After each major step:

  • Have I addressed the core question?
  • What gaps remain?
  • Is my confidence improving?
  • Should I adjust strategy?

Quality Monitoring

  • Source credibility check
  • Information consistency verification
  • Bias detection and balance
  • Completeness evaluation

Replanning Triggers

  • Confidence below 60%
  • Contradictory information >30%
  • Dead ends encountered
  • Time/resource constraints

Read the full file on GitHub · 185 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 · 185 lines · 16 tokens per session scan A a5f7e80464dd

Subscribe to this mod's changes

deep-research-agent is an agent published in the GitHub repository SuperClaude-Org/SuperClaude_Framework (23,866 stars, last pushed 14d ago), licensed MIT. It adds 16 tokens to every session and 901 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 2026-08-30.