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Journal if

Skill Agents365-ai/journal-if/skills/journal-if

Use when looking up journal impact factors (JCR IF), checking a journal's impact factor by name, comparing IF across journals, or answering questions about "影响因子" / "impact factor" / "IF". Triggers on "impact factor", "journal IF", "影响因子", "JCR", "IF score", "journal rank", "which journal has higher IF", "what is the IF of". PROACTIVELY USE when user mentions journal prestige, publication venue quality, or manuscript submission target evaluation.From its SKILL.md

Install
npx -y skills add Agents365-ai/journal-if --skill journal-if

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SKILL.md

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Journal Impact Factor Lookup

Look up journal impact factors using a two-source cascade: bundled CSV cache (~200 common journals) → OpenAlex API (approximate 2-year IF for any journal).

Critical rule: Always use journal_if.py for lookups. Never guess impact factors — they change yearly and vary by edition.

Quick Reference

User wants...TierCommand
Look up IF of a journalreadpython3 journal_if.py lookup "Nature Medicine"
Search for a journalreadpython3 journal_if.py search "cancer immunology"
Process a list of journalsreadpython3 journal_if.py batch journals.txt
Cache-only (no network)readpython3 journal_if.py --offline lookup "Cell"
Inspect cache statereadpython3 journal_if.py cache status
Refresh upstream CSVwritepython3 journal_if.py cache update
Machine-readable CLI contractreadpython3 journal_if.py schema
Schema for one subcommandreadpython3 journal_if.py schema lookup

Output format

Stdout is a stable JSON envelope when the CLI is not attached to a terminal (piped or captured by an agent), and a human-readable view when run on a TTY. To force a format: --format json|table|human|auto. --json is a back-compat alias for --format json.

Envelope shape:

  • Success: { "ok": true, "data": {...}, "meta": { "schema_version", "cli_version", "latency_ms" } }
  • Partial success (batch): { "ok": "partial", "data": { "succeeded": [...], "failed": [...] }, "meta": {...} }
  • Error: { "ok": false, "error": { "code", "message", "retryable", ... }, "meta": {...} }

Exit codes

CodeMeaning
0success (including partial success)
1runtime / upstream error
2validation / bad input (missing file, bad flag)
3not found (no journal matched)

Error codes (inside error.code)

CodeRetryableExitMeaning
not_foundno3Lookup completed but no source matched
upstream_unavailableyes1OpenAlex API failed transiently; retry later or use --offline
file_not_foundno2Input file path does not exist
validation_errorno2Bad argument or flag combination
runtime_erroryes1Unexpected internal error

Data Sources

  1. Bundled CSV — ~200 top journals across life sciences, medicine, chemistry, physics, and engineering. Curated from JCR data, shipped with the skill. Always available, instant.

  2. OpenAlex API — Free, open API that computes an approximate 2-year impact factor from citation counts. Covers virtually all academic journals. The number differs from the official JCR IF — it's a citation-rate metric computed from the same formula (citations in year Y to items published in Y-1 and Y-2, divided by citable items in those two years) but using OpenAlex's own article classification. Adequate for ranking and comparison; do not cite as "the JCR impact factor" in formal contexts.

When to use which

ScenarioSource
Quick check of a major journalBundled CSV (instant)
Niche or newer journalOpenAlex fallback (automatic)
Formal submission / grantNote: OpenAlex IF ≠ official JCR IF. Cite only as approximate.
Batch processing many journalsCSV for cached ones, OpenAlex for misses
Offline / air-gapped--offline flag (bundled CSV only)

Workflow

Step 1: Detect Intent

IntentAction
"What's the IF of Nature?"lookup "Nature"
"Compare IF of Cell and Science"Run lookup twice, compare results
"Which immunology journals have IF > 20?"search "immunology" then filter
"Process this list of journals"batch journals.txt
"Is this a high-impact journal?"lookup then interpret IF in field context

Step 2: Execute

Run the appropriate journal_if.py command. The script handles:

  1. Local CSV lookup (instant, ~200 curated journals)
  2. OpenAlex API fallback (automatic, approximate 2-year IF)
  3. Fuzzy matching — catches minor name variations

Step 3: Present Results

  • Show the journal name, impact factor, and data year
  • Note the source (CSV cache vs OpenAlex approximate)
  • For search results: show a table with IF, year, and category

Understanding Impact Factor

IF RangeTypical TierExample
> 30Elite (top 0.1%)Nature (64.8), Science (56.9), Cell (64.5)
20–30Exceptional (top 1%)Cancer Cell (50.3), Immunity (32.4)
10–20Excellent (top 5%)Nature Communications (16.6), Sci Adv (13.6)
5–10Strong (top 15%)eLife (7.7), Cell Reports (8.8)
2–5SolidPLOS ONE (3.7), Sci Rep (4.6)
< 2Niche / newMany field-specific and new journals

Caveats:

  • IF varies dramatically by field — a top mathematics journal may have IF < 5 while a mid-tier oncology journal has IF > 10.
  • Always compare IF within the same field.
  • The IF data year matters; values shift annually.
  • OpenAlex approximate IF differs from official JCR IF; treat as a ranking metric, not a certified number.

Batch Processing

Create a text file with one journal name per line:

Nature Medicine
Journal of Biological Chemistry
Proceedings of the National Academy of Sciences

Then run:

python3 journal_if.py batch journals.txt

Troubleshooting

IssueSolution
"No data found"Try a shorter/alternative name; use search for fuzzy matching
OpenAlex returns 0 or None IFThe journal may be too new (needs 2+ years of data); use --offline to check cache only
OpenAlex IF differs from JCRExpected — OpenAlex uses its own article classification. Use for ranking, not formal citation.
Cache download failsCheck network; the bundled CSV still works offline
Wrong journal matchedUse more specific name; the fuzzy matcher picks the closest substring match

What ships with it: 3 files

46.2 KB alongside SKILL.md, 1 of them executable

data/

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