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What you get

A launching pad, not a finished review: a document that orients a researcher in an unfamiliar field fast enough to start reading confidently. What a generous colleague who knows the field would tell you over coffee — here’s the lay of the land, here are the key people, here’s how the thinking evolved, read these first. Consensus ships this as a packaged skill. The workflow below is what it does, so you can run it, adapt it, or rebuild it in Claude Code, Codex, or your own agent framework.

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Who it’s for

Research-software engineers, methodologists, and technical researchers who run the same class of review repeatedly. Teams doing this report cutting a review from roughly two days to one.

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Set up the connection

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Phase 1 — Reconnaissance

Run one broad exploratory search. Confirm it returned data before going further. Then read the abstracts for:
  • The major themes and subfields
  • The terminology researchers actually use — usually not the phrasing the requester used
  • Methodological distinctions that matter here (RCT vs observational, animal vs human)
  • Angles the requester probably has not considered
Note citation counts as they come back. A paper with unusually high citations relative to its age is likely foundational — flag it for the priority reading list.

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Phase 2 — Pick a framework

Evaluate PICO first; it applies far more broadly than just clinical questions. Many real questions span frameworks. “How does social media affect teen mental health” has PICO elements, qualitative elements, and technology elements. Pick a primary for structure and say which components borrow from elsewhere — the goal is clarity, not orthodoxy. Name the chosen framework explicitly, show how the topic maps to each component, and say in one sentence why you picked it over the alternatives.

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Phase 3 — Confirm before spending the budget

Stop and check in. Output a scannable summary:
  1. What the literature shows — 3–4 sentences on themes, terminology, what is well-studied, what is contested.
  2. Framework mapping table — one row per component, each proposing a sub-area to explore, plus a fifth row for any cross-cutting theme.
  3. Search depth — let the requester choose, and say what constrains it.
The key idea: extra budget buys deeper analysis, not more of the same. Review-article searches (systematic review [topic], meta-analysis [topic]) are disproportionately valuable because one good review pre-digests dozens of primary studies.

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Phase 4 — Execute

Run searches sequentially — send, wait for the result, confirm it contains data, record what came back, then send the next. There is a one-query-per-second limit on every plan except Enterprise, so parallel firing produces 429s rather than speed. See rate limits. Era-gated searches are the cheapest way to understand a field’s trajectory: run the most important sub-area once with year_max: 2015 and once with year_min: 2021, then compare.
  • Terminology shifts — “gut flora” became “gut microbiome”. A researcher searching only modern terms will miss foundational older work.
  • Conclusion shifts — older papers reaching different conclusions signals a paradigm shift or accumulating evidence.
  • Methodological evolution — observational studies → RCTs → meta-analyses tells you how mature the evidence base is.

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Cross-search intelligence

This is what turns a pile of results into field knowledge. Track three things across all searches:
  1. Repeat-hit papers. A paper appearing in 3 of 5 sub-area searches is foundational to the whole field, not just one sub-area. Flag these as must-reads.
  2. Recurring authors. The same author group across multiple searches signals a dominant lab. Note the top 3–5 — anyone entering this field needs to know the key voices.
  3. Citations per year. Divide citation count by years since publication. A 2023 paper with 150 citations is a far stronger signal than a 2008 paper with 150.

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Phase 5 — Produce the guide

Structure the output as a launch pad:
  1. Topic overview — one tight paragraph: what the topic is, which framework was used, and a characterization of the evidence landscape (“robust on X, sparse on Y”).
  2. Start here — priority reading order. The most actionable section. 5–7 papers across all sub-areas, ordered as a newcomer should read them: best recent review first, then the foundational paper(s), then 2–3 at the current frontier, ending with one that highlights a gap or controversy. Per paper give what it contributes in the sequence and what to pay attention to while reading it (“focus on Table 3, which compares effect sizes across all RCTs”).
  3. How the field got here — a 5–8 row timeline plus a note on terminology evolution.
  4. Sub-area guides — per sub-area: what the research shows, 3–5 key papers, 6–10 search terms including historical ones, and 2–3 ready-to-paste Boolean strings.
  5. Key research groups — the 3–5 most frequent authors, their sub-areas, a representative paper each.
  6. Open questions and gaps — split into methodological, population/context, and conceptual. For each, say why it matters, not just that it is unstudied.
  7. Bibliography — alphabetical, every entry with a clickable full Consensus URL.
  8. Audit log.

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Audit requirements

Follow the grounding rules. For this workflow, log per search: query, filters as sent, papers returned, status. Then report searches executed, searches successful, searches failed after retry, unique papers received after dedup, and papers cited. State the detected plan cap and what it means for coverage: at 10 successful searches with a 10-result cap, the theoretical ceiling is 100 papers before dedup. Flag any sub-area returning fewer than 5 papers as potentially incomplete coverage rather than a genuine gap.

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What to check before you trust it

  • Confirm the reading order is actually ordered. If it is just five good papers with no sequencing logic, the most valuable section has degraded into a list.
  • Check the terminology note. A field whose vocabulary shifted and whose guide does not mention it will send researchers into incomplete searches.
  • Watch for silent filter emptiness. If a narrow pass returned almost nothing, relax one filter at a time and say which was binding — never present that as “little evidence exists”.
  • Calibrate once. Have a person check one sub-area’s papers by hand before trusting the method at volume.

Turn a syllabus into a recommended reading list

The teaching-focused sibling of this workflow.

Track new papers across many topics on a schedule

Take the same method and run it unattended on a cron.

Best practices

Rate limits, grounding rules, and the five primitives.

All use cases

Browse the gallery by persona.