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- Research Brief Pack — Topic + Audience → 1–2 Page Brief
Research Brief Pack — Topic + Audience → 1–2 Page Brief
Turn any topic and audience into a clear 1–2 page research brief — key points, risks, and source placeholders your agent can draft in one pass.
$9
Works with the AI tools you already use
Research Brief Pack — Topic + Audience → 1–2 Page Brief
Example session with this skill installed
topic: Use of Rust for high-frequency trading systems
audience: CTO of a boutique hedge fund
goal: Decide if we should migrate from C++ to Rust for our 2025 core engine
depth: standard
- Read your context and instructions
- Compiled the research brief
- Generated the document
I have prepared a research brief comparing Rust and C++ for high-frequency trading (HFT), focusing on memory safety, performance overhead, and ecosystem maturity.
Research brief: Use of Rust for high-frequency trading systems
Audience: CTO of a boutique hedge fund
Goal: Decide if we should migrate from C++ to Rust for our 2025 core engine
Geography / horizon: geo not specified · 2025
Depth: standard
Generated: 2024-05-22 · Draft for human verification — not advice
1. Executive snapshot
Rust presents a compelling alternative to C++ by offering memory safety without a garbage collector, potentially reducing "segmentation fault" related downtime. While execution speed is comparable, the primary hurdle is the lack of specialized HFT libraries and the significant cost of retraining a senior C++ team. The decision hinges on whether long-term stability outweighs the immediate migration risk and talent scarcity.
2. Key points
KP1 — Performance Parity: Benchmarks show Rust's Zero-Cost Abstractions match C++ in most computational tasks. Confidence: high
- KP2 — Memory Safety: Ownership model eliminates common C++ vulnerabilities like use-after-free. Confidence: high
KP3 — Ecosystem Gap: Lack of mature, low-latency market data connectors compared to C++'s 30-year lead. Confidence: medium
KP4 — Compile Times: Significantly slower than C++, which may impact rapid iterative deployment cycles. Confidence: high
KP5 — Talent Pool: High-calibre Rust developers are available but often lack deep market-microstructure experience. Confidence: medium
3. Implications for CTO
- Consider a hybrid approach: keep the core matching engine in C++ while building new risk management modules in Rust.
- Budget for a longer onboarding period; even senior C++ devs face a learning curve with the Rust borrow checker.
- Evaluate the cost of building internal wrappers for proprietary C++ HFT libraries.
4. Risks and watch-outs
| Risk | Severity | Why it matters | Mitigation / watch |
|---|---|---|---|
| Latency Spikes | high | Unexpected LLVM optimisations might introduce jitter. | Profile with cargo-flamegraph early. |
| Library Lock-in | medium | Dependence on a single wrapper for C++ interop. | Audit cxx or bindgen stability. |
| Hiring Delay | medium | Small niche of HFT-ready Rust engineers. | Start internal training 6 months prior. |
5. Open questions
- Perform a side-by-side latency benchmark of a specific order-routing logic in both languages.
- Audit existing vendor APIs to see if Rust bindings are officially supported.
- Review current C++ technical debt to quantify the "safety" benefit of a rewrite.
6. Source placeholders
- [SOURCE: Comparative analysis of Rust vs C++ in low-latency systems — URL TBD]
- [SOURCE: State of the Rust Ecosystem for Finance 2024 report — URL TBD]
7. Suggested next step
Conduct a two-week "spike" project to rewrite a non-critical market data parser in Rust to measure developer velocity and performance.
Next steps
- Verify the placeholder sources against recent industry whitepapers.
- Assign a senior engineer to run the suggested two-week spike project.
research-brief-pack-topic-audience-1-2-p.pdf
PDF · document
Example file from a real run - the skill writes it into your workspace.
Connects securely to your tools. The creator never sees your data.
What you get
About this skill
Research Brief Pack is a focused Agensi skill for coding agents (Cursor, Claude Code, Codex CLI, Gemini CLI, Copilot, and other runtimes that load SKILL.md).
What you get
Give the agent a topic and an audience (optional: goal, geography, time horizon). It returns a structured Markdown brief:
- Executive snapshot
- Key points with confidence labels
- Implications for that audience
- Risks table (severity + mitigation)
- Open questions for human follow-up
- Source placeholders (you fill real URLs)
- One concrete next step
Typical length: about 400–800 words — roughly 1–2 pages when printed or pasted into Notion/Docs.
Who it’s for
Founders, PMs, consultants, freelancers, and analysts who want a repeatable first draft before meetings, pitches, or build decisions — without the agent inventing citations or overconfident forecasts.
How it behaves
- Asks for missing topic/audience instead of guessing
- Separates established points from uncertain ones
- Refuses to fabricate statistics, expert quotes, or source URLs
- Uses en-GB wording and an honesty pass (no guaranteed outcomes)
What’s included: SKILL.md installable instructions; example-output.md clearly marked sample; README.md install and usage notes.
Honest limits
This skill drafts a starting brief. You (or your client) must verify facts and replace placeholder sources before decisions that matter. It is not legal, medical, or financial advice, and it does not claim any sales or income result from using or listing skills.
How to install
Works the same in every agent - Claude, Cursor, Codex, Copilot and 20+ more.
- 1
Download the ZIP
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- 2
Unzip into your skills folder
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- 3
Ask your agent to use it
Restart the agent if it was already running. It picks the skill up automatically - no config needed.
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Click the path to copy it. Create the folder if it does not exist yet.
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