Home Explore Help
Sign In
kekezack
/
XzhLoongSkills
1
0
Fork 0
Files Issues 0 Pull Requests 0 Wiki
Tree: fe7bac5c45
Branches Tags
XzhLoongSkills
/
skills
/
research-skills
/
medical-imaging-review
/
references
/
WORKFLOW.md

WORKFLOW.md 13 KB
History Raw

6-Phase Literature Review Workflow

This workflow replaces the v2 "7-phase write-then-QA" structure with a "write-with-verify + multi-agent peer review" structure. Verification is embedded throughout, not bolted on at the end.

Phase 0: Paradigm Capture

Goal: Before writing anything, ground the review in 2-3 published flagship-quality exemplars from the target journal tier.

Why: LLMs default to a generic "survey paper" register — numbered chapters, hedging language, neutral catalogue, dense subsections. Flagship reviews (Nature Reviews / Nat Med / Lancet family) write very differently. Without an exemplar to anchor against, the draft will drift toward survey-paper style and become hard to retrofit.

Actions:

  1. Identify 2-3 exemplar reviews from the target journal tier. Selection criterion: same modality or same problem family, published in last 3 years, by recognized authors.

  2. Read them carefully (not just skim). Pay attention to:

    • Heading depth and numbering (most flagship reviews use 2 levels, no numbers)
    • Paragraph rhythm (topic → evidence → verdict, not topic → list → list → list)
    • Citation density (1.5-2.5 refs per paragraph typical)
    • Equation handling (Box vs inline)
    • Vendor handling (Table vs body)
    • Authorial voice (do they take positions or stay neutral?)
    • Box and Figure usage (how many, how dense)
    • Table count (rarely more than 3)

  3. Write the extracted style spec to PARADIGM.md. See PARADIGM.md template for the exact structure.

Deliverable: PARADIGM.md in the project root.

Time budget: 2-3 hours (reading + spec writing).

Phase 1: Project Initialization

Goal: Set up the project files and writing guidelines.

Actions:

  1. Create CLAUDE.md from the TEMPLATES.md ▸ CLAUDE.md template. Fill in:

    • Topic-specific terminology table
    • Reference source configurations (ArXiv / PubMed / Zotero queries)
    • Expected literature categories (don't commit yet — refine after Phase 2)

  2. Create IMPLEMENTATION_PLAN.md from TEMPLATES.md ▸ IMPLEMENTATION_PLAN.md. Note the 3-axis structure for §Methods (not flat).

  3. Create empty manuscript_draft.md. Leave it empty until Phase 4 — don't pre-populate with placeholder text.

  4. Link PARADIGM.md and CITATION_INTEGRITY.md and HALLUCINATION_PATTERNS.md from CLAUDE.md so they're easy to refer back to.

Deliverable: Project skeleton with 4 files (PARADIGM.md, CLAUDE.md, IMPLEMENTATION_PLAN.md, manuscript_draft.md).

Time budget: 1 hour.

Phase 2: Literature Collection + Verification (simultaneous)

Goal: Gather the corpus while verifying each entry's metadata in real time.

Why simultaneous: v2 separated collection from verification — collection in Phase 2, verification never. Result: 17 placeholder DOIs and many wrong-author lists shipped to the final draft. v3 verifies on the way in.

Actions:

2.1 ArXiv (methodological preprints)

Query: "[topic] AND (segmentation OR detection OR classification)"
Categories: cs.CV, eess.IV, cs.LG
Date: last 3 years
Max results: 50-80 per query (NOT 100 — discriminate aggressively)

For each paper added:

  • mcp__arxiv-mcp-server__download_paper(paper_id)
  • mcp__arxiv-mcp-server__read_paper(paper_id) — read abstract + methods + results
  • Note: actual title, full author list, exact module names, headline numbers, dataset name

2.2 PubMed (peer-reviewed clinical literature)

MeSH: "Deep Learning"[MeSH] AND "[domain]"[MeSH]
Filters: Review or Clinical Study, last 5 years

For each paper added:

  • WebFetch on https://pubmed.ncbi.nlm.nih.gov/<PMID>/
  • Note: title, full author list (first 6 + et al.), journal, year, volume, issue, pages, DOI, headline finding direction (positive/negative)

2.3 Zotero (user's local library — especially closed-access)

For closed-access journals (Med Image Anal, Eur Radiol, JACC, Lancet family, Nature family) the user often has PDFs in Zotero. Always check before assuming inaccessible.

mcp__zotero__zotero_search_collections(query: "<topic>")
mcp__zotero__zotero_get_collection_items(collection_key: ..., detail: "summary", limit: 200)
mcp__zotero__zotero_search_items(query: "<author> <method>", limit: 5)
mcp__zotero__zotero_get_item_fulltext(item_key: ...)

2.4 Verification — apply CITATION_INTEGRITY rules as you collect

For each paper added to the bibliography, before committing the entry:

  • DOI resolves on Crossref (api.crossref.org/works/<DOI>)
  • First and last author names match the first-source verbatim
  • Journal name, year, volume, issue, pages match
  • No placeholder strings (xxx, [TBD], ?) anywhere in the entry

If any check fails, do not add the entry. Either resolve the metadata or drop the paper.

See CITATION_INTEGRITY.md for the full 5-rule protocol.

2.5 Build the literature matrix

3-axis Sub-family Key papers (verified) Count Source
Architectural priors CNN [refs] N arXiv
Architectural priors Transformer [refs] N arXiv
Inductive priors Topology [refs] N arXiv
... ... ... ... ...
Clinical Validation [refs] N PubMed
Datasets Public [refs] N mixed

Note the 3 axes, not a flat 10-category list. See DOMAINS.md for the 3-axis structure per domain.

2.6 Gap analysis

After initial collection:

  • Are negative trials covered? (LLM tendency: only cite positive trials → over-rosy review)
  • Are recent 6-month preprints covered? (LLM tendency: stale by training-cutoff date)
  • Are inter-vendor reproducibility studies covered? (LLM tendency: report-only-positives)
  • Are demographic-bias / fairness studies covered? (LLM tendency: ignore entirely)

For each gap, run a targeted search.

Deliverable: Literature matrix (in CLAUDE.md or IMPLEMENTATION_PLAN.md) with every entry verified.

Time budget: 1-2 days (depending on topic breadth). Most of the time is reading abstracts to discriminate relevance, not searching.

Phase 3: Outline + 3-Axis Method Taxonomy

Goal: Lock in section structure + the 3-axis method grouping before writing prose.

Actions:

  1. Define top-level sections from the Standard Review Structure template. No numbered headings.

  2. For §Methods, force yourself into the 3-axis grouping (NOT a flat 10-subsection list):

    • Axis 1: Architectural priors (what kind of network)
    • Axis 2: Inductive priors (what kind of geometric / structural / multi-task bias is built in)
    • Axis 3: Data regime (how is data used / pre-trained / federated)

Each axis becomes one H3 subsection. Inside each axis, group method families with bold lead-ins (**Topology-aware design.**), not deeper H4 headings.

  1. Map each paper from the literature matrix to one (or sometimes two) axes. A paper that's only about a topology loss → axis 2. A paper that's a Mamba variant for segmentation → axis 1. A paper about federated learning for cardiac MRI → axis 3.

  2. Plan the three tables explicitly:

    • Table 1: public datasets (name, year, cases, annotation type, access)
    • Table 2: representative methods (with modality / family / dataset / metric — pick 12-20 papers across all 3 axes)
    • Table 3: commercial products (manufacturer / product / regulatory / validation evidence)

  3. Plan Box 1: evaluation metrics with formulas.

  4. Plan figures (typically 3-5; overview, taxonomy, representative architectures, workflow).

Deliverable: Section outline and 3-axis paper mapping in IMPLEMENTATION_PLAN.md.

Time budget: 0.5-1 day.

Phase 4: Write with Per-Claim Verification

Goal: Produce the manuscript prose, with verification embedded in every paragraph.

Why per-claim verification: v2 wrote first and QA'd later. The QA was structural, not factual. Result: shipped fabricated module names and wrong numbers. v3 verifies each claim before committing it.

Actions per section:

  1. Write an introduction paragraph (1-2 paragraphs on motivation + scope). This is the safest part of the section — make it punchy and clear, set up the verdict that will close the section.

  2. For each method family, repeat this micro-loop:

a. Re-read the cited paper's abstract + relevant methods/results section. Use read_paper (arxiv) or zotero_get_item_fulltext (closed-access). Do not skip this. If you can't access the paper, do not write its internal architecture.

b. Write 2-4 sentences describing the method's actual contribution, using actual module names and actual numbers. Cite the paper as [N].

c. Verify the [N] you just placed:

  - Is N's bibliography entry the paper you just read? (body↔bib reconciliation)
  - Does your sentence's number (Dice / sensitivity / HR) appear in the paper?
  - Does your sentence's directional claim (lower/higher / increased/decreased) match the paper?

d. If any verification fails, fix immediately. Do not move on with broken citations — they compound.

  1. Close the section with a verdict sentence (for 3 of the H3 subsections — pick the most opinionated positions). See SKILL.md ▸ Verdict Sentences.

  2. Equations go into Box 1, not the body. If you find yourself typing a $$ outside Box 1, stop and move the equation.

  3. Vendor names go into Table 3, not the body. If you find yourself typing "HeartFlow" / "Cleerly" / etc. outside Table 3, stop and rewrite with category descriptor.

  4. Update bibliography as you go (don't batch at the end — the body↔bib reconciliation breaks down with batching).

Self-check during writing

Every 5-6 paragraphs, pause and scan for the 9 hallucination patterns (see HALLUCINATION_PATTERNS.md):

  • Are author names sounding generic? (pattern 1)
  • Are performance numbers suspiciously round or high? (pattern 2)
  • Am I claiming directional findings I haven't verified? (pattern 3)
  • Am I citing vendor materials as if peer-reviewed? (pattern 4)
  • Are there any xxx or [TBD] strings? (pattern 5)
  • Are [N] referring to what I think? (pattern 7)
  • Are my metric formulas correct? (pattern 8)

Deliverable: manuscript_draft.md complete from Introduction through References, with per-claim verification trace in the writing log.

Time budget: 3-5 days (the largest phase).

Phase 5: Multi-Agent Peer Review

Goal: Before delivering to the user, run a 4-perspective audit.

Why: Single-author self-review misses patterns. The 4 specialized agents catch what a single writer doesn't.

Actions:

Launch a manuscript-review agent team with 4 teammates (see the ai-review-revision skill's references/agent_team_setup.md for the exact TeamCreate / TaskCreate / Agent spawn templates):

Teammate Focus
style-reviewer Compare against PARADIGM.md spec; identify register / structural drift
ref-checker Verify every [N] body↔bib match; spot-check author lists and DOIs
peer-reviewer Roleplay as flagship-tier journal reviewer; identify missing controversies, weak verdicts, scope drift
fact-checker Cross-check every quantitative claim (Dice, HR, sample size, p-value) against first-source

After all 4 reports return, synthesize into review_outputs/00_team_synthesis.md. For any issue ≥2 reviewers independently flag, treat as hard fix. For single-reviewer flags, judge based on severity.

If the issues are minor (handful of style nits, 1-2 minor citation issues): fix them in place and ship.

If the issues are major (≥5 hard factual errors, ≥10 citation drift instances, missing major controversies): the right move is to apply the ai-review-revision skill's Phase 1 (factual reset) workflow before delivery. This is unusual but possible — and it's a signal that this skill needs further improvement.

Deliverable: 4 review reports + synthesis + a final-quality draft.

Time budget: 1 day for the multi-agent review, plus fix time depending on findings.

Phase 6: Submission Prep

Goal: Format-level finalization for a specific target journal.

Use the ai-review-revision skill's references/phase4_submission_prep.md for:

  • Journal selection (3-tier reach / match / safety)
  • Presubmission inquiry templates
  • Cover letter template
  • Box vs body duplication scan
  • Figure realization (no placeholders at submission)
  • Citation format conversion ([N] → <sup>N</sup> depending on journal)
  • Self-check checklist

Deliverable: Submission-ready package (manuscript + figures + cover letter + author info).

Time budget: 0.5-1 week including presubmission inquiry wait.

Total Timeline

For a typical medical-imaging review project:

Phase Duration
Phase 0: Paradigm capture 2-3 hours
Phase 1: Init 1 hour
Phase 2: Collect + verify 1-2 days
Phase 3: Outline + 3-axis taxonomy 0.5-1 day
Phase 4: Write with per-claim verification 3-5 days
Phase 5: Multi-agent peer review 1 day + fix time
Phase 6: Submission prep 0.5-1 week (incl. presubmission wait)
Total 2-3 weeks of focused work

Compare to v2 + downstream fix: typically 1 week of v2 drafting + 2-3 weeks of post-hoc revision. Net the same time, but v3 delivers a submission-ready draft instead of one needing factual reset.