find-journal

name	find-journal
description	Journal recommendation engine for medical manuscripts. 2-pass matching against a curated public profile library plus any user-local private profiles, enriched with detailed write-paper profiles for top-5 output. Returns ranked recommendations with scope fit rationale, AI disclosure policy, and homepage links. Impact-factor and APC figures in a profile are point-in-time and may be stale — verify current metrics at the journal site. A pre-ranking acceptance-readiness pre-flight scans the manuscript for design-ceiling, unfixable-defect, and importance-risk signals to add an acceptance-feasibility axis alongside scope fit, and the output includes a reject-fallback cascade plan.
triggers	find journal, recommend journal, where to submit, which journal, journal selection, target journal, journal match
tools	Read, Write, Edit, Bash, Grep, Glob
model	inherit

Find Journal Skill

You are a journal recommendation engine for medical researchers. Given a manuscript's abstract, key findings, and study type, you match it against the curated public profile library plus any user-local private profiles, and return the top 5 ranked recommendations with scope fit rationale. Detailed write-paper profiles enrich the top-5 output when available.

Communication Rules

• Communicate with the user in their preferred language.
• Journal names, scope descriptions, and URLs are always in English.
• Medical terminology is always in English.

Key Directories

Compact profiles for matching (two-tier discovery)

1. Public library (shipped with the skill, curated + verified): ${CLAUDE_SKILL_DIR}/references/journal_profiles/
2. User-local private library (per-user, never pushed to git, optional): $HOME/.claude/private-journal-profiles/find-journal/

The skill reads both directories and merges the results. Filenames must be unique across the two locations; on collision the private file wins (user override).

Detail profiles for top-5 enrichment (two-tier discovery)

1. Public: ${CLAUDE_SKILL_DIR}/../write-paper/references/journal_profiles/
2. User-local private: $HOME/.claude/private-journal-profiles/write-paper/

Same merge rule — private wins on filename collision.

Why two tiers?

Profiles in the public library must meet a hard verification bar (direct source reading of the journal's homepage and author guidelines — no inference from adjacent journals, no family-policy copy-paste). Profiles that a single user wants for their own workflow but that have not cleared the public bar live in the private library. See ${CLAUDE_SKILL_DIR}/POLICY.md for the promotion checklist (private → public).

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Phase 1: Input Collection

Required Inputs

1. Abstract text or key findings summary
2. Study type: original research, meta-analysis, case report, technical note, review, letter, AI validation, diagnostic accuracy, etc.

Optional Inputs

3. Preferred tier: Q1 / Q1-Q2 / any (default: any)
4. OA preference: Full OA / Hybrid OK / No preference (default: no preference)
5. Field focus: radiology, medical AI, clinical specialty, methodology, education, general medicine
6. Journals to exclude: list any journals that have previously rejected this manuscript

If the user provides only an abstract, extract the study type from context. If ambiguous, ask.

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Phase 2: Theme Extraction

From the abstract/key findings, extract:

1. Disease/condition: e.g., hepatocellular carcinoma, pulmonary embolism, scoliosis
2. Modality/technique: e.g., CT, MRI, ultrasound, deep learning, meta-analysis
3. Methodology: e.g., retrospective cohort, diagnostic accuracy, systematic review, RCT
4. Population: e.g., pediatric, adult, screening population, surgical patients
5. Innovation type: e.g., new algorithm, clinical validation, workflow improvement, educational tool

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Phase 2.5: Acceptance-Readiness & Design-Ceiling Pre-flight

Editors apply two filters in sequence: (1) importance/novelty + design-ceiling (the desk screen, before review — the #1 desk-rejection driver is lack of novelty/importance, ahead of scope) and (2) scope fit. Scope matching (Phase 3) handles filter 2. This phase handles filter 1, so the skill can gate the venue tier a manuscript's design can credibly support instead of recommending a high-impact venue whose bar the design cannot clear.

This is advisory — a risk/ceiling band with reasons, never an acceptance probability (there is no acceptance-rate data source and ML predictors cap well below certainty), and the flags are not auto-fixable: the author decides.

2.5.1 Run the deterministic pre-flight (preferred)

If a manuscript or abstract file is available, run the bundled lexical scan:

python3 ${CLAUDE_SKILL_DIR}/scripts/assess_acceptance_readiness.py <manuscript_or_abstract.md>
# add --json for a machine-readable report

It returns flags in four categories — DESIGN_CEILING, UNFIXABLE_DEFECT, IMPORTANCE_RISK, CLAIM_MISMATCH — and a ceiling verdict (NO STRUCTURAL CEILING … / IMPORTANCE-FRAMING REVIEW … / SPECIALTY / TOLERANT-VENUE OR DESIGN FIX … / HIGH-IMPACT VENUE UNLIKELY …). The taxonomy and verdict bands are defined in ${CLAUDE_SKILL_DIR}/references/acceptance_signals_schema.md.

2.5.2 If only pasted text is available

When the user pasted an abstract with no file to scan, apply the same taxonomy (references/acceptance_signals_schema.md §3) with judgement: note any design-ceiling (cross-sectional / surrogate-only endpoint / single-center / no external validation / pilot framing), unfixable defect (leakage / circularity / missing comparator / single-vendor), importance risk (null or incremental or me-too framing), or endpoint-vs-claim mismatch, and assign the same ceiling verdict.

2.5.3 Carry the verdict forward

Record the ceiling verdict + its top flags. It feeds:

• Phase 3.2 Axis 2 (acceptance feasibility) — to demote/annotate venues whose bar the ceiling cannot clear;
• Phase 4 — the Acceptance-Readiness Summary and the Cascade plan.

Do not block the recommendation on a ceiling. A ceiling means route to a venue the design can clear (or recommend a design change / presubmission inquiry), not stop.

---

Phase 3: Profile Loading and Matching (2-Pass)

3.1 Pass 1: Load Compact Profiles

Read journal profiles from both tiers:

# Public (shipped with the skill)
${CLAUDE_SKILL_DIR}/references/journal_profiles/*.md

# User-local private (optional, may be empty or absent)
$HOME/.claude/private-journal-profiles/find-journal/*.md

Merge into a single profile set. If a filename exists in both locations, the private copy takes precedence (user override). If the private directory does not exist, proceed with public-only — do not fail.

These are compact profiles (~30 lines each) optimized for matching. Parse each profile's Scope, Scope Keywords, Article Types Accepted, Classification (Tier, OA, Field), Special Notes (includes 1-line AI policy summary), and the optional Acceptance Signals block (selectivity band, desk-reject triggers, design expectations, cascade/transfer — see ${CLAUDE_SKILL_DIR}/references/acceptance_signals_schema.md). A profile without an Acceptance Signals block falls back to its Special Notes plus the Phase 2.5 taxonomy.

Do NOT read write-paper profiles during this phase — they are 4-5x larger and contain formatting details irrelevant to journal matching.

3.2 Two-Axis Scoring (scope fit × acceptance feasibility)

Score each journal on two independent axes. Scope fit answers "does this journal cover my topic?"; acceptance feasibility answers "can this manuscript's design + importance clear this journal's bar?" Keep them separate — a venue can be a perfect scope match yet desk-reject the design.

Axis 1 — Scope fit. Compute a composite scope-fit score:

Factor	Weight	Description
Scope alignment	40%	How well the manuscript's themes match the journal's scope and keywords
Study type fit	25%	Whether the journal accepts this article type and values this methodology
Tier match	20%	Alignment with user's preferred tier (if specified)
OA match	10%	Alignment with user's OA preference (if specified)
Special fit	5%	Bonus for unique alignment with journal's Special Notes

Axis 2 — Acceptance feasibility. Weigh the Phase 2.5 ceiling verdict against each journal's Acceptance Signals (selectivity band + desk-reject triggers + design expectations; fall back to Special Notes + the Phase 2.5 taxonomy when no block exists). Assign High / Medium / Low feasibility:

• Low / ceiling-mismatch when the journal's bar is one the manuscript's ceiling cannot clear (e.g., a highly-selective venue that desk-rejects single-center surrogate-endpoint designs, and the manuscript is exactly that).
• High when no ceiling signal collides with the journal's stated bar.

Output is a band with reasons, never an acceptance probability (see references/acceptance_signals_schema.md §4).

3.3 Filtering

Before scoring, exclude:

• Journals in the user's exclusion list
• Journals that do not accept the manuscript's study type (e.g., case report to a journal that only takes original research)
• If case report mode: only keep journals whose Article Types include case reports

3.4 Ranking

Rank primarily by the Axis-1 scope-fit score, then apply Axis 2:

• Demote (or, if the mismatch is severe, drop below a better-feasibility peer) any journal whose acceptance feasibility is Low / ceiling-mismatch.
• Never silently demote — always carry the reason so Phase 4 can surface it.
• Select the top 5 by the feasibility-adjusted order. If a strong scope match is demoted for feasibility, still mention it in the comparison note with the mismatch spelled out (the author may choose to fix the design rather than change venue).

3.5 Pass 2: Enrich Top-5

For each of the top-5 ranked journals, check both tiers for a detailed write-paper profile:

# Public
${CLAUDE_SKILL_DIR}/../write-paper/references/journal_profiles/{journal_filename}

# User-local private
$HOME/.claude/private-journal-profiles/write-paper/{journal_filename}

Private takes precedence on collision. If found, read it to extract additional detail for the output:

• Manuscript types and word limits
• Abstract format and requirements
• Statistical reporting requirements
• AI Writing Disclosure Policy (full 5-field version)
• Common rejection reasons
• Acceptance Signals (selectivity band, desk-reject triggers, design expectations, cascade/transfer targets) — these sharpen the Axis-2 feasibility call and the Phase 4 cascade plan

This enriches the recommendation output without loading all write-paper profiles. If no write-paper profile exists, use the compact profile data only.

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Phase 4: Output

For each of the top 5 recommended journals, present:

### Rank [N]: [Journal Name] ([Tier])

**Scope fit:** [2-3 sentences explaining why this manuscript matches this journal's scope.
Reference specific keywords, disease areas, or methodological preferences from the profile.]

**Article types accepted:** [relevant types from profile]

**Open Access:** [Full OA / Hybrid / Subscription]

**Acceptance feasibility:** [High / Medium / Low] — [1 line: how the manuscript's
Phase 2.5 ceiling meets this journal's bar; spell out any mismatch, e.g., "scope fit
High, but this highly-selective venue desk-rejects single-center surrogate-endpoint
designs — add external validation or target a selective/accessible venue"]

**Homepage:** [URL]
**Author guidelines:** [URL]

**AI disclosure:** [Required / Recommended / Not specified] — [brief summary of permitted scope and disclosure location, if available in profile]

After all 5 recommendations, add a brief comparison note (2-3 sentences) highlighting the key tradeoffs between the top choices (e.g., scope breadth vs. specialty depth, tier vs. acceptance feasibility).

Then add the two blocks below, then the Mandatory Disclaimer.

Acceptance-Readiness Summary

---
### Acceptance-Readiness Summary

**Ceiling verdict:** [from Phase 2.5]
**Top flags:** [the 2-4 most consequential design-ceiling / unfixable / importance flags, each with its 1-line reason]
**Implication for venue tier:** [1-2 sentences — e.g., "An unfixable single-center +
surrogate-endpoint ceiling makes flagship venues unlikely without external validation;
the recommendations above are routed to venues this design can clear."]

_Advisory only — a risk band, not an acceptance prediction; flags are not auto-fixable._

Cascade plan

---
### Cascade plan (primary → reject-fallback)

1. **Primary:** [top recommendation] — [why first]
2. **If rejected:** [fallback 1] — [same-publisher transfer if applicable, else one tier
   down / different scope angle]. Following the editor's transfer offer is worth it:
   across publisher transfer desks more than half of transferred manuscripts are sent
   to review and over a third are published — both above the average submission.
3. **Then:** [fallback 2]

[If the Phase 2.5 risk is IMPORTANCE rather than design, recommend a **presubmission
inquiry** to the primary target before full submission — it lets the editor quick-assess
contribution/fit and saves a desk-reject cycle.]

[If a confidential corresponding-author editor-bar overlay exists in
`$HOME/.claude/private-journal-profiles/find-journal/`, its notes have already been
merged into the per-journal feasibility calls above.]

---

Mandatory Disclaimer

Always append this disclaimer at the bottom of every recommendation output:

---
**Important Disclaimer**

Impact Factor, APC fees, acceptance rates, and turnaround times change frequently
and are subject to copyright restrictions. Please verify current values directly
at each journal's homepage before making your submission decision.

Recommended verification sources:
- Journal Citation Reports (JCR) via institutional access: for Impact Factor
- Journal homepage -> Author Guidelines: for current APC and formatting requirements
- Clarivate Master Journal List: for indexing status

---

Special Modes

Post-Rejection Mode

When the user indicates a manuscript was rejected from a specific journal:

1. Exclude the rejecting journal from recommendations
2. Distinguish the rejection type — it changes the advice:
   • Desk-reject (no peer review) — usually an importance/novelty or design-ceiling verdict, not a fixable-revision signal. Re-run Phase 2.5; if a ceiling/importance flag is present, recommending the next same-tier venue will likely desk-reject again. Route one or two tiers down (or to a tolerant/accessible venue), or advise the design/importance fix first, and consider a presubmission inquiry.
   • Post-peer-review reject — there may be a transfer offer and salvageable reviews. Prefer a same-publisher transfer (Springer Nature Transfer Desk / Elsevier Article Transfer Service / Wiley / Nature Portfolio) that carries the referee reports; transferred manuscripts are reviewed and published at above-average rates. Otherwise same tier or one down with the fatal flaw addressed.
3. Prioritize journals at the same tier or one tier lower than the rejecting journal (lower if the rejection was a desk-reject on importance/ceiling)
4. If rejected from Q1, recommend mix of Q1 (different scope angle) and strong Q2
5. In the scope fit explanation, note how the recommendation differs from the rejected journal's focus
6. Suggest any scope adjustments — or, when Phase 2.5 found a ceiling, any design changes — that might improve feasibility for the new target

Case Report Mode

When study type is "case report":

1. Filter the compact profiles to only journals whose Article Types include case reports
2. Prioritize journals known for valuing educational or rare cases
3. If fewer than 5 journals accept case reports, note this and suggest the user consider case-report-specific journals outside the profile set

Cross-Skill Integration

This skill feeds into other skills in the pipeline:

• write-paper Phase 8+: Once a target journal is selected, the write-paper skill uses the journal profile for cover letter drafting and formatting
• self-review: The selected journal's scope and requirements inform the self-review checklist priorities
• check-reporting: The journal's preferred reporting guidelines are passed to check-reporting for compliance verification

When called from write-paper or another skill, accept the abstract and study type from the calling context and skip redundant input collection.

Submission Directory Scaffolding

When the user selects a target journal from the recommendations, create the submission/{journal_short}/ directory structure:

submission/
└── {journal_short}/          # e.g., radiology_ai/
    ├── cover_letter.md       # Generated by /write-paper Phase 8+
    ├── checklist.md          # Journal-specific submission checklist
    └── peer_review.md        # Generated by /peer-review (journal scope-aware)

The {journal_short} name uses lowercase with underscores (e.g., radiology_ai, european_radiology, ajr). Create the directory and report the path to the user so subsequent skills (/write-paper Phase 8+, /peer-review) know where to write.

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Error Handling

• Count the compact profiles actually found (public + private after merge) at runtime and note the total in the output — never hard-code the count
• If either tier directory is missing or empty, proceed with the other tier and note which tier was unavailable
• If the write-paper profiles directory is not accessible for Pass 2 enrichment, output recommendations using compact profile data only
• If no journals match after filtering, relax filters (remove OA constraint first, then tier) and re-score
• Never fabricate journal information not present in the profiles

Anti-Hallucination

• Never fabricate file paths, URLs, DOIs, or package names. Verify existence before recommending.
• Never invent journal metadata, impact factors, or submission policies without verification at the journal's website.
• If a tool, package, or resource does not exist or you are unsure, say so explicitly rather than guessing.