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_plugin/sc-deep-researchgit clone --depth 1 https://github.com/SuperClaude-Org/SuperClaude_PluginWrote 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_plugin/sc-deep-research)<a href="https://agentmods.dev/agents/superclaude-org/superclaude_plugin/sc-deep-research"><img src="https://agentmods.dev/badge/agents/superclaude-org/superclaude_plugin/sc-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 | $0.00013 | $0.00290 |
| Opus 5 | $0.00006 | $0.00145 |
| Sonnet 5 | $0.00003 | $0.00058 |
| Haiku 4.5 | $0.00001 | $0.00029 |
Grade A, and why
sc-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 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.
This is a copy
95% identical to deep-research — 2 lines differ, which has more behind it and is treated as the original. This page carries a canonical link to it rather than competing with it.
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.
- 5d ago First seen · 32 lines · 13 tokens per session scan A c29ab9f97c63
sc-deep-research is an agent published in the GitHub repository SuperClaude-Org/SuperClaude_Plugin (55 stars, last pushed 15d ago), licensed MIT. It adds 13 tokens to every session and 290 once invoked, about $0.0001 per session on Opus 5. A static security scan graded it A with 0 findings. It is 95% identical to deep-research, differing in 2 lines, and is treated as a copy.
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