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 skills add madebyaris/advance-minimax-m3-cursor-rules --skill deep-researchgit clone --depth 1 https://github.com/madebyaris/advance-minimax-m3-cursor-rulesWrote 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/skills/madebyaris/advance-minimax-m3-cursor-rules/deep-research)<a href="https://agentmods.dev/skills/madebyaris/advance-minimax-m3-cursor-rules/deep-research"><img src="https://agentmods.dev/badge/skills/madebyaris/advance-minimax-m3-cursor-rules/deep-research/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.
<a href="https://agentmods.dev/skills/madebyaris/advance-minimax-m3-cursor-rules/deep-research"><img src="https://agentmods.dev/badge/skills/madebyaris/advance-minimax-m3-cursor-rules/deep-research.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector pass
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 5.1 | $0.00072 | $0.02675 |
| Opus 5 | $0.00036 | $0.01337 |
| Sonnet 5 | $0.00014 | $0.00535 |
| Haiku 4.5 | $0.00007 | $0.00267 |
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 11d 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.
How it starts
The opening of the file, as written. The whole thing — 288 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Deep Research
Conduct thorough, multi-step research using an iterative loop of search, compress, reflect, and synthesize. Works with any Cursor-supported model.
Effort Scaling
Before starting, calibrate depth to the question:
| Tier | When | Searches | Delegation (Task) |
Output |
|---|---|---|---|---|
| Quick | Focused factual question, single concept | 2-3 | None | Concise answer with sources |
| Standard | Multi-faceted topic, comparison, how-something-works | 5-8 | None | Structured analysis with sections |
| Exhaustive | Comprehensive survey, architecture decision, landscape review | 10+ | Parallel Task investigations |
Full report with citations |
Calibration:
Question complexity: [single-fact / multi-faceted / comprehensive]
Source diversity needed: [one source type / mixed]
User expectation: [quick answer / detailed analysis / full report]
-> Tier: [Quick / Standard / Exhaustive]
Phase 0: Scope
Immediately classify the research request before any searching.
Step 1 -- Classify research type:
| Type | Signal | Example |
|---|---|---|
| Comparison | "vs", "compare", "which is better", "difference between" | "React vs Vue for enterprise apps" |
| Explanation | "how does", "what is", "explain", "why does" | "How does Raft consensus work?" |
| Investigation | "debug", "find out why", "what caused", "root cause" | "Why is our build 3x slower?" |
| Survey | "landscape", "options for", "state of", "overview" | "State of CSS-in-JS in 2026" |
| Fact-check | "is it true", "verify", "confirm" | "Does React 19 still need keys?" |
Step 2 -- Determine sources:
| Source | When to use |
|---|---|
WebSearch + WebFetch |
General knowledge, current events, library docs, community solutions |
SemanticSearch + Grep + Read |
Codebase-specific questions, internal patterns, project architecture |
| Mixed | "How should we implement X?" (need both external best practices and internal conventions) |
What ships with it
1 file beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
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.
- 11d ago First seen · 288 lines · 72 tokens per session scan A 8e3264091495
deep-research is a skill published in the GitHub repository madebyaris/advance-minimax-m3-cursor-rules (125 stars, last pushed 2mo ago), licensed MIT. It adds 72 tokens to every session and 2,675 once invoked, about $0.0004 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.
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quick-tasks
Token-saving mode for everyday lightweight work. Use for one-line fixes, typo/config-value changes, quick questions ("what does this function do?"), throwaway scripts, and anything that ends inside a single file. Output is a minimal diff and a short report. For multi-file, design, or new-feature work, switch to the…
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