research-prompt
Skill11 starsChanged 4 months agoMITView on GitHub
Write a single-paragraph Deep Research prompt to hand to a human researcher (or a deep-research AI). Use when the user wants a research brief, a "deep research prompt", a one-paragraph task for a researcher, or asks "what should our researcher look for". Produces ONE tight paragraph with full context, numbered sub-questions, and per-finding output format.
We split this skill into the rules it gives an agent
5 rules. 3 are common, 1 is distinctive, and 1 is very specific to this project.
3
Common
Most of the 4 edited versions we read keep these.
1
Distinctive
This author's own choices. Worth a look.
1
Very specific
Tied to their project's names, files or tools. Probably skip.
- Common
- Distinctive
- Very specific
- Common: line 12
One paragraph: No headers, no bullet list in the deliverable.
- Very specific: line 19
Source hierarchy: Prefer primary sources (official docs, GitHub, papers, filings, changelogs).
- Common: line 20
Contradiction handling: If sources conflict, separate confirmed facts / inference / unresolved uncertainty — don't force fake consensus.
- Distinctive: line 21
Completion bar (define "done"): Don't stop at the first plausible answer.
- Common: line 33
Add include/avoid constraints + the per-finding output format.
“Common” is measured: kept by at least 6 in 10 of the 4 edited versions of this file we could read. “Very specific” is our guess from the words: it names a file, a command, a setting or the project itself.
Files
Research Prompt
Goal: turn a vague research need into ONE self-contained paragraph that a researcher with zero prior knowledge of the project can act on with zero back-and-forth.
Rules
- One paragraph. No headers, no bullet list in the deliverable.
- Prompt the job, not the topic. Give search handles (timeframe, ranking, source type, decision logic) — not just a subject.
- Assume zero prior knowledge. Write for a researcher who has never heard of the project. Open by explaining, in plain English, what the project/product is, why it exists, and the current situation — so they understand what's going on, what we need, and why we need it.
- Lead with the goal + decision. Right after that explainer, state the single question the research must answer and the decision/use it informs.
- Embed all context. Names, dates, product, prior known facts, constraints. The researcher must not need to ask anything or guess.
- Number the sub-questions inline (1, 2, 3…) so coverage is explicit. Keep to 3–6. One mission per prompt — don't cram unrelated questions.
- State constraints. What to include, what to avoid (e.g. "only non-Chinese competitors", "no marketing fluff").
- Source hierarchy. Prefer primary sources (official docs, GitHub, papers, filings, changelogs); forums/X/Reddit are weak signal only, never factual proof.
- Contradiction handling. If sources conflict, separate confirmed facts / inference / unresolved uncertainty — don't force fake consensus. Flag low-confidence claims for verification.
- Completion bar (define "done"). Don't stop at the first plausible answer. Corroborate each key claim with multiple independent primary sources where they exist; where sources are scarce, say so explicitly instead of padding. Keep going until every numbered sub-question is covered to this bar.
- Gap round before finishing. Require a final self-critique pass: list gaps, contradictions, and any single-source claims, then run another round of searches to close them — repeat until clean.
- Constrain output hard, method loosely. Be strict on the deliverable; leave the search path flexible so the researcher can explore.
- Demand a fixed output per finding: source link + specific claim + one-line "why it matters / why a viewer should care".
- Verifiable, citable facts only. No opinions.
- Last sentence: instruct them to output everything into a single detailed markdown file.
Process
- Pull context from the relevant project files / conversation (dates, names, known facts, audience, end use), and write a 1–2 sentence plain-English explainer of what the project is and why it exists for a reader who knows nothing.
- Identify the ONE question the research answers.
- Draft 3–6 numbered sub-questions that fully cover it.
- Add include/avoid constraints + the per-finding output format.
- Compress to one clean paragraph. Cut filler.
Template
[For a reader with zero prior knowledge: in 1–2 plain-English sentences, what the project/product is, why it exists, and the current situation.] Research [TOPIC + key identifying facts] to answer one question: [THE QUESTION] — for [DECISION / END USE]. Find: (1) …; (2) …; (3) …; (4) …. [Constraints: include X, avoid Y.] Prefer primary sources; treat forums/social as weak signal only; if sources conflict, separate fact from inference and flag what needs verification. Don't stop at the first plausible answer: corroborate each key claim with multiple independent primary sources where they exist (and say so explicitly where they don't), continuing until every numbered question is covered to that bar. Before finishing, do a self-critique pass — list gaps, contradictions, and any single-source claims, then run another round of searches to close them, repeating until clean. For each point, give the source link, the specific claim, and a one-line "why it matters". No marketing fluff — verifiable, citable facts only. Output everything into a single detailed markdown file.
Executing the prompt
To run the finished prompt with an AI researcher, execute it via DeepAPI POST /v1/research/deep — follow the deep-research skill.
Other versions4 projects use a version of this.
Word for word · 0
None found.
Edited · 3
- matyasstoch/david-skills★ 5992% same
- amanuelmamo7/Skills★ 183% same
- talhaMah56/claude_skills★ 096% same
Wrote their own version · 1
- cill-i-am/skills★ 1same name
How matches are found. Word for word: the exact same text. Edited: shares passages with this file (“99% same” means 99% of its five-word phrases also appear here; 10% or more counts). Their own version: similar meaning, or, weakest, the same name. We can’t tell which project had it first. Projects are counted among the 200 most-starred candidates, and mentions are links to the repository we found, up to 50 per site, so both counts are a floor.
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Your trail
Files you open will collect here, so you can find them again.
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Now do this for your own.
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