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.
npx agentmods add agents/superclaude-org/superclaude_framework/deep-researchgit clone --depth 1 https://github.com/SuperClaude-Org/SuperClaude_FrameworkWrote 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/superclaude-org/superclaude_framework/deep-research)<a href="https://agentmods.dev/agents/superclaude-org/superclaude_framework/deep-research"><img src="https://agentmods.dev/badge/agents/superclaude-org/superclaude_framework/deep-research.svg" alt="Measured on agentmods" 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 | $0.00011 | $0.00288 |
| Opus 5 | $0.00005 | $0.00144 |
| Sonnet 5 | $0.00002 | $0.00058 |
| Haiku 4.5 | $0.00001 | $0.00029 |
Grade A, and why
deep-research 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 4d 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.
Copies of this mod
1 near-identical copy found in the catalogue:
- sc-deep-research — 95% identical, 2 lines differ
What it actually says
Deep Research Agent
Deploy this agent whenever the SuperClaude Agent needs authoritative information from outside the repository.
Responsibilities
- Clarify the research question, depth (
quick,standard,deep,exhaustive), and deadlines. - Draft a lightweight plan (goals, search pivots, likely sources).
- Execute searches in parallel using approved tools (Tavily, WebFetch, Context7, Sequential).
- Track sources with credibility notes and timestamps.
- Deliver a concise synthesis plus a citation table.
Workflow
- Understand — restate the question, list unknowns, determine blocking assumptions.
- Plan — choose depth, divide work into hops, and mark tasks that can run concurrently.
- Execute — run searches, capture key facts, and highlight contradictions or gaps.
- Validate — cross-check claims, verify official documentation, and flag remaining uncertainty.
- Report — respond with:
🧭 Goal: 📊 Findings summary (bullets) 🔗 Sources table (URL, title, credibility score, note) 🚧 Open questions / suggested follow-up
Escalate back to the SuperClaude Agent if authoritative sources are unavailable or if further clarification from the user is required.
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.
- 4d ago First seen · 32 lines · 11 tokens per session scan A 31d09ec6f550
deep-research is an agent published in the GitHub repository SuperClaude-Org/SuperClaude_Framework (23,866 stars, last pushed 13d ago), licensed MIT. It adds 11 tokens to every session and 288 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.
Other agents, from other repositories
Financial Analyst
Analyzes financial data, generates reports, and provides business insights.
Research Assistant
Autonomous agent for conducting thorough research and synthesizing findings.
data-analyst
Turns business questions into queries, metrics, and honest answers — analysis, dashboards, cohorts, and the caveats that come with them.
transcript-analyst
Analyze agent execution transcripts — answer questions about tool usage, reasoning, turns, parallel calls, stumbles, and behavior patterns.
complexity-analyzer
Code complexity metrics and simplification specialist.
sc-deep-research
Adaptive research specialist for external knowledge gathering.