10.01Desk Research and Evidence SynthesisAvailable

Literature Review and Desk Research

Find, verify and appraise existing evidence, synthesise it against your decision, resolve conflicting sources, and know when primary research is genuinely needed.

Free. Works on Claude, ChatGPT, Gemini or any assistant that accepts a skill file.

What this skill does

The method, encoded.

Most research questions have already been partly answered by someone. The difficulty is finding that evidence, judging whether it is any good, and knowing what it still leaves open.

This skill supplies a working method for exactly that. It turns a business decision into review questions with a stopping rule, maps the source types that would carry the answer (academic, official statistics, regulatory, industry, company and trade sources), builds and logs a search strategy, and screens what it finds in two passes. Every source then passes a verification gate before it is allowed to carry a claim, and is appraised on eight dimensions: authority, recency, methodology, sample, geography, relevance, conflicts of interest, and whether it is primary evidence or a restatement of somebody else's.

The synthesis is organised by claim rather than by source, so disagreement between sources is diagnosed and adjudicated rather than averaged into a false consensus. The output tells you what the existing evidence establishes, at what confidence, what it does not, and precisely what primary research would still have to measure.

It is uncompromising on one point: a reference that cannot be located is not a reference, and is never written out in citation format.

Best used for

  • Establishing what is already known before commissioning primary research
  • Deciding whether primary research is needed at all
  • Building a defensible evidence base with no fieldwork budget
  • Resolving conflicting published figures circulating in a business
  • Writing the context or background section of a report or proposal
  • Appraising the quality of secondary sources a stakeholder already believes
  • Producing a narrative literature review for commercial or applied academic work

Typical inputs

What you give it.

Decision or business question the review must serve, Scope boundary (markets, time window, population of interest), Accessible sources (academic, official statistics, regulatory, industry, company, trade press), Optional date cutoff or recency requirement, Optional existing internal evidence base or past studies, Optional construct definition, Optional budget and timeline for possible primary research

Typical outputs

What you get back.

Documented search log (sources consulted, strings, dates, hits, screening counts), Appraised source table with quality dimensions and evidence tier per source, Claim-level extraction table traceable to page or section locators, Synthesis organised by review question, with confidence per conclusion, Disagreement register with diagnosed cause and adjudication, Sufficiency assessment (answered, partially answered, contested, absent), Primary research recommendation, or an explicit statement that none is needed, Limitations statement covering access, language, recency and search scope

Method coverage

What the skill works through.

  1. What desk research is, and where it fails
  2. Turning a decision into answerable review questions
  3. Mapping the evidence landscape before you search
  4. Building and logging a search strategy
  5. Screening: two passes and standard exclusion reasons
  6. Verifying sources before they carry any weight
  7. The eight-dimension source quality framework
  8. Primary evidence, secondary analysis, restatement and opinion
  9. Extracting claims with their bases and question wording
  10. Synthesising by claim rather than by source
  11. Why sources disagree, and how to adjudicate
  12. Deciding whether you still need primary research
  13. Narrative review versus systematic review
  14. Handling AI-generated citations that do not exist

Download

Free skill. One file.

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How to install

Add the skill file and the five kernel protocols to a Claude Project, a ChatGPT Project, a Gemini Gem, or paste them at the top of any assistant conversation. Then give it your real research material, not a description of it.

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Questions

Common questions.

What is the difference between desk research and a literature review?

In practice they are the same activity applied in different settings. Desk research usually describes commercial work drawing on statistics, industry and company sources; a literature review usually describes academic work drawing on peer-reviewed publications. The method here covers both, because the appraisal problems are identical.

How do I judge whether a research source is credible?

Score it on eight dimensions separately rather than forming a general impression: authority, recency of the underlying data (not the publication date), methodology, sample and base, geography, relevance to your actual question, conflicts of interest, and whether it is primary evidence or a restatement. A fatal weakness on one dimension is not offset by strength on another.

How do I check whether an AI-generated citation is real?

Open the source. A reference is real when you can retrieve the document and confirm that the locating details and the specific claim both come from it, not from something citing it. The characteristic AI failure is a half-remembered reference: roughly the right author, roughly the right year, a plausible journal, and no such paper. Treat any reference you cannot open as absent, not as a lead.

Can AI do a literature review?

It can do the mechanical parts well: building search vocabularies across disciplines, screening at scale, extracting consistently, and holding a large evidence table in view. It cannot be trusted to supply sources from its own knowledge, and it should never generate a bibliography without access. Verification, quality appraisal and the sufficiency judgement need a researcher.

Two published sources give different numbers. Which one do I use?

Usually neither, until you have diagnosed the difference. Most conflicts turn out to be definitional (different constructs under the same word), methodological (stated importance versus observed behaviour), sampling, temporal or geographic rather than genuine contradiction. Report both figures with their sources and say what causes the gap. Do not average them.

How do I know when to stop searching?

Write the stopping rule before you start. A workable one: stop when each review question has either converging evidence from at least two independently produced sources of adequate quality, or a documented record of the searches that failed to find any.

When do I need a systematic review instead?

When the work will be examined, peer reviewed, or must be reproducible by a third party. A systematic review requires a pre-specified protocol, an exhaustive search, and protocol-standard reporting. A purposive documented review is a different and lighter method, and it should never be described as systematic.

How do I decide whether primary research is still needed?

Classify each review question as answered, partially answered, contested or absent, based on the quality and relevance of what you found. The questions that remain contested or absent, and that the decision actually turns on, are the brief for the primary study. Everything already established is money you do not need to spend.

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