Research brief structure
Skill Solonnikov/agent-skills/skills/research-brief-structure
Produces research briefs that answer a question — sources, synthesis, gaps, recommendation — rather than summaries that describe a topic. Use when a user needs to research a decision, investigate a market or tool, understand an unfamiliar domain quickly, or present findings to a stakeholder who wants an answer, not a report.From its SKILL.md
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SKILL.md
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Research Brief Structure
A brief answers a question. A summary describes a topic. Knowing the difference saves a lot of wasted effort.
When to use
- A user needs to decide something and wants grounded reasoning, not just "read these articles."
- Evaluating a tool, vendor, market, or competitor.
- Onboarding into an unfamiliar domain (technology, industry, topic) quickly.
- Preparing for a stakeholder meeting where the deliverable is a recommendation, not a literature review.
Before you start
Nail down:
- The question. Specific, answerable, single. "Should we use Postgres or MongoDB?" is a question. "Database research" is not.
- The decision or action the brief supports. A brief with no downstream decision tends to be unfocused. "Pick one by Friday" focuses it.
- Audience. Technical peer, exec, cross-functional? Drives depth, vocabulary, how much context to include.
- Timebox. 1 hour? 1 day? 1 week? Scope matches the time.
- What's already been done. Prior briefs, opinions already formed, earlier research — skip relitigating, build on.
Authoring workflow
- Restate the question at the top, precisely. If you can't pin it down in one sentence, you don't know what you're researching.
- Gather sources. Cast wide, include varied viewpoints. Note for each: who, what claim, how credible. See source-evaluation.md.
- Synthesize. Don't list sources — extract claims, note agreement / contradiction, identify gaps. See synthesis-patterns.md.
- Identify gaps. What did you want to know but couldn't find? What would change the recommendation if discovered?
- Recommend. Take a position. Use the evidence; acknowledge uncertainty.
- Name the trigger to revisit. If you learned X, the recommendation would flip. Spell that out so the reader can act on it later.
The brief template
# Brief: [Question] — [YYYY-MM-DD]
## Question
[Restated in one sentence. Who needs the answer and by when.]
## Recommendation
[One sentence. Specific. "Use Postgres" not "Postgres looks good." Confidence level: high / medium / low.]
## Reasoning
[3–5 bullets with the strongest evidence. Each bullet cites source.]
## Alternatives considered
- [Option B] — pros, cons, why not.
- [Option C] — pros, cons, why not.
## Risks and mitigations
- [Top 2–3 risks of the recommendation. For each: how to mitigate.]
## Gaps
- [What you couldn't confirm. What would change the answer.]
## Trigger to revisit
[Specific event or data point that would cause re-evaluation.]
## Sources
- [Title] — [author / org] — [link] — [credibility note].
- [Title] — [author / org] — [link] — [credibility note].
Non-negotiable rules
- Start with the recommendation. Busy readers don't read to the end. Lead with the answer; back it up below.
- Specific recommendation, not vibes. "We should probably consider..." is not a recommendation. "Use X" is.
- Cite what you claim. Every non-obvious assertion has a source. "Industry standard" is not a source.
- Use primary sources when possible. Official docs > blog posts > tweets about blog posts about official docs.
- Flag uncertainty explicitly. "I couldn't find benchmarks for X at scale" is stronger than hiding the gap.
- Include dissenting evidence. If half of sources disagree with your recommendation, say so. Pretending the disagreement doesn't exist gets caught in review.
- Time-bound the brief. "This was researched on YYYY-MM-DD" matters. Fast-moving topics (new tech, vendor features) may be stale in 6 months.
- Don't write in meandering paragraphs. Bullets, tables, clear sections. Briefs are read fast; structure them for skimming.
Length
- One page for decision briefs. Forces clarity.
- Two pages max for complex topics.
- Appendices for methodology, raw data, long quotes — but the front page stands alone.
Output
The brief itself, plus:
- A 2-sentence TL;DR suitable for Slack / email.
- A 15-minute "walk me through it" talking script if the reader wants to be briefed orally.
References
- Brief template — the full template with a worked example.
- Source evaluation — assessing credibility, primary vs secondary, spotting bias, red flags.
- Synthesis patterns — how to turn raw notes into a coherent brief: agree/disagree, cluster, contradict, find gaps.
What ships with it: 3 files
16.2 KB alongside SKILL.md
references/
- brief-template.md4.6 KB
- source-evaluation.md5.7 KB
- synthesis-patterns.md5.8 KB
Gives 0 of the 12 instructions most plan spec skills give in ~1.1k tokens
Counted across 1,099 of the 1,860 authors here whose files we hold, read 2026-08-07
- Ask one question at a timein 51 of 1099
- Break plans into vertical slicesin 29 of 1099, across 11 files
- Publish issues in dependency orderin 27 of 1099, across 9 files
- Iterate until user approves the breakdownin 25 of 1099, across 7 files
- Explore the repository to understand the codebase statein 24 of 1099, across 7 files
- Use domain glossary vocabularyin 23 of 1099, across 5 files
- Apply correct triage labels to published issuesin 23 of 1099, across 5 files
- Prefer AFK slices over HITLin 22 of 1099, across 7 files
- Write a specification before writing any codein 22 of 1099, across 14 files
- Write failing tests before implementation codein 22 of 1099, across 20 files
- Ask clarifying questions until requirements are concretein 21 of 1099, across 13 files
- Respect existing architecture decision recordsin 20 of 1099, across 5 files
Said here and by no other author read
- Define a single answerable question before researching
- Identify the downstream decision the brief supports
- Determine the audience and timebox before starting
- Restate the research question at the top
- Synthesize source claims instead of listing sources
- Lead the brief with the recommendation
Grouped from the skills themselves: near-identical wordings counted once, and counted by distinct author, so one author publishing three of these counts once. Length counted with cl100k_base; the agent that loads this file may tokenize it differently.