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Find Journal

aperivue/medsci-skills

  • 51 installs
  • 236 repo stars
  • Updated August 3, 2026
  • aperivue/medsci-skills

Find-journal is a Claude Code skill that recommends the top-5 target journals for a medical manuscript by matching its abstract and study type against a curated journal-profile library.

About

Find-journal is a journal recommendation engine for medical manuscripts. Given an abstract, key findings, and study type, a researcher uses it to match against a curated public profile library plus optional private profiles and get the top 5 ranked journals with scope-fit rationale and AI-disclosure policy. It carries no cached impact-factor or APC data; users verify current metrics at journal sites.

  • Journal recommendation engine matching a manuscript against a curated profile library
  • 2-pass matching: compact profiles then top-5 enrichment with detailed write-paper profiles
  • Weighted scoring (scope 40%, study-type 25%, tier 20%, OA 10%, special 5%) with AI-disclosure notes

Find Journal by the numbers

  • 51 all-time installs (skills.sh)
  • Ranked #804 of 1,879 Documentation skills by installs in the Skillselion catalog
  • Data as of Aug 5, 2026 (Skillselion catalog sync)
At a glance

find-journal capabilities & compatibility

Capabilities
fill icmje coi · fill protocol · humanize
Use cases
research · documentation
Pricing
Free
From the docs

What find-journal says it does

Journal recommendation engine for medical manuscripts.
SKILL.md
Returns ranked recommendations with scope fit rationale, AI disclosure policy, and homepage links.
SKILL.md
No cached IF/APC data — users verify current metrics at journal sites.
SKILL.md
npx skills add https://github.com/aperivue/medsci-skills --skill find-journal

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Listed on Skillselion
Installs51
repo stars★ 236
Last updatedAugust 3, 2026
Repositoryaperivue/medsci-skills ↗

What it does

Recommend the top-5 target journals for a medical manuscript by matching abstract and study type to journal profiles.

Who is it for?

Medical researchers deciding where to submit, who want ranked journals with scope-fit rationale and AI-policy notes.

Skip if: Providing current impact-factor or APC figures, which it deliberately does not cache.

When should I use this skill?

A manuscript is drafted and the author needs to choose a target journal to submit to.

What you get

Top-5 ranked journal recommendations with scope-fit rationale, AI-disclosure policy, and homepage links.

  • top-5 ranked journal recommendations with rationale and links

By the numbers

  • returns top 5 ranked recommendations
  • 2-pass matching
  • scope alignment weighted 40%

Files

SKILL.mdMarkdownGitHub ↗

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).

---

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.

---

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

---

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), and Special Notes (includes 1-line AI policy summary).

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

3.2 Scoring Algorithm

For each journal, compute a composite score:

FactorWeightDescription
Scope alignment40%How well the manuscript's themes match the journal's scope and keywords
Study type fit25%Whether the journal accepts this article type and values this methodology
Tier match20%Alignment with user's preferred tier (if specified)
OA match10%Alignment with user's OA preference (if specified)
Special fit5%Bonus for unique alignment with journal's Special Notes

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

Sort by composite score. Select top 5.

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

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

3.6 Profile Coverage Advisory

Before emitting the final output, scan the skill directory for profile-gap TODO files and decide whether to append a Coverage Advisory block.

What this step protects against. The recommendation list is bounded by what the public and private libraries contain. If a high-value journal is simply missing from both tiers, the ranking silently substitutes an adjacent journal and the user never learns that a better-fitting target exists. The Coverage Advisory surfaces known gaps and directs the user to /add-journal (or manual PDF + verification) to close them.

Procedure.

1. Locate TODO files. Glob ${CLAUDE_SKILL_DIR}/TODO_*_profiles.md. These are maintainer-curated gap files, one per field (e.g., TODO_neurointervention_profiles.md, future: TODO_pediatric_*, TODO_endocrinology_*). The file must contain a ## Field Keywords section — files without this section are ignored.

2. Match against manuscript themes. For each TODO file, read the Field Keywords block. If any keyword (case-insensitive, word-boundary match) appears in the manuscript's abstract or in the themes extracted in Phase 2, mark the TODO as relevant.

3. Parse the gap list. From each relevant TODO, extract the journal entries under headings matching ## 추가 필요 / ## Missing / ## Pending — they are the still-missing journals. Exclude any entry already marked completed (lines containing ✅ or "추가 완료 / Completed"). Also skip journals listed under ## Private (waiting on private→public promotion).

4. Emit the advisory. If at least one TODO is relevant and at least one journal in it is still missing, append a Coverage Advisory block immediately below the top-5 recommendation list and above the Mandatory Disclaimer. If no TODO is relevant, skip this block entirely — no false alarms.

Output format (when emitted).

---
### ⚠️ Profile Coverage Advisory — {field name}

Your manuscript matches keywords for the **{field name}** field, and the public profile
library has known gaps here. The following journals may be strong-fit candidates that did
not appear in the top-5 only because they are not yet in the library:

- **{Journal 1}** ({Publisher}) — {1-line reason from TODO entry}
- **{Journal 2}** ({Publisher}) — {1-line reason from TODO entry}
- ...

To add any of them to the public library:

1. Open the journal's author-guidelines page and save it as PDF (or paste the text).
2. Invoke `/add-journal` with the PDF — it transcribes the Identity / Scope / Article
   Types / AI policy fields directly from the source and verifies the ISSN against
   `portal.issn.org`, per `skills/find-journal/POLICY.md`.
3. After the new profile lands in `references/journal_profiles/`, re-run `/find-journal`
   to see the updated ranking.

TODO source: `skills/find-journal/{TODO filename}`
---

Guardrails.

  • Do not fabricate journals, publishers, or rationale. Copy the TODO entry verbatim (or

paraphrase minimally from the same line).

  • Do not promote a still-private profile into the advisory — private profiles are by

definition not production-ready.

  • Keep the advisory concise (≤10 missing journals per field). If a TODO file lists more,

show the first 10 in priority order and add a "... and {N} more in the TODO file" line.

  • The advisory is informational. It does not change the top-5 ranking or its scores.

---

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]

**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 likelihood).

If Phase 3.6 produced a Coverage Advisory, insert it immediately after the comparison note and before the Mandatory Disclaimer.

---

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. Prioritize journals at the same tier or one tier lower than the rejecting journal 3. If rejected from Q1, recommend mix of Q1 (different scope angle) and strong Q2 4. In the scope fit explanation, note how the recommendation differs from the rejected journal's focus 5. Suggest any scope adjustments that might improve fit 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.

---

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.

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FAQ

Does it report impact factor and APC?

No; it carries no cached IF or APC data. It returns scope fit and links, and users verify current metrics at the journal sites.

How does it rank journals?

A composite score weighting scope alignment 40%, study-type fit 25%, tier match 20%, OA match 10%, and special fit 5%.

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