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.
- Installs
- 365
- Last 24h
- —
- Trending rank
- —
- Security
- Not audited
Install
Works with every agent the skills CLI supports.
npx skills add https://github.com/agents365-ai/365-skills --skill journal-if- 01
Install
Run the command in your project. The CLI asks which agents to install for.
- 02
Describe the task
Ask your agent for something this skill covers. It loads journal-if automatically when relevant.
- 03
Review the result
The agent follows the SKILL.md steps, scripts and references bundled with the skill.
SKILL.md
The instructions your agent reads when the skill is triggered.
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... | Tier | Command |
|---|---|---|
| Look up IF of a journal | read | python3 journal_if.py lookup "Nature Medicine" |
| Search for a journal | read | python3 journal_if.py search "cancer immunology" |
| Process a list of journals | read | python3 journal_if.py batch journals.txt |
| Cache-only (no network) | read | python3 journal_if.py --offline lookup "Cell" |
| Inspect cache state | read | python3 journal_if.py cache status |
| Refresh upstream CSV | write | python3 journal_if.py cache update |
| Machine-readable CLI contract | read | python3 journal_if.py schema |
| Schema for one subcommand | read | python3 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
| Code | Meaning |
|---|---|
0 | success (including partial success) |
1 | runtime / upstream error |
2 | validation / bad input (missing file, bad flag) |
3 | not found (no journal matched) |
Error codes (inside error.code)
| Code | Retryable | Exit | Meaning |
|---|---|---|---|
not_found | no | 3 | Lookup completed but no source matched |
upstream_unavailable | yes | 1 | OpenAlex API failed transiently; retry later or use --offline |
file_not_found | no | 2 | Input file path does not exist |
validation_error | no | 2 | Bad argument or flag combination |
runtime_error | yes | 1 | Unexpected internal error |
Data Sources
-
Bundled CSV — ~200 top journals across life sciences, medicine, chemistry, physics, and engineering. Curated from JCR data, shipped with the skill. Always available, instant.
-
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
| Scenario | Source |
|---|---|
| Quick check of a major journal | Bundled CSV (instant) |
| Niche or newer journal | OpenAlex fallback (automatic) |
| Formal submission / grant | Note: OpenAlex IF ≠ official JCR IF. Cite only as approximate. |
| Batch processing many journals | CSV for cached ones, OpenAlex for misses |
| Offline / air-gapped | --offline flag (bundled CSV only) |
Workflow
Step 1: Detect Intent
| Intent | Action |
|---|---|
| "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:
- Local CSV lookup (instant, ~200 curated journals)
- OpenAlex API fallback (automatic, approximate 2-year IF)
- 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 Range | Typical Tier | Example |
|---|---|---|
| > 30 | Elite (top 0.1%) | Nature (64.8), Science (56.9), Cell (64.5) |
| 20–30 | Exceptional (top 1%) | Cancer Cell (50.3), Immunity (32.4) |
| 10–20 | Excellent (top 5%) | Nature Communications (16.6), Sci Adv (13.6) |
| 5–10 | Strong (top 15%) | eLife (7.7), Cell Reports (8.8) |
| 2–5 | Solid | PLOS ONE (3.7), Sci Rep (4.6) |
| < 2 | Niche / new | Many 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
| Issue | Solution |
|---|---|
| "No data found" | Try a shorter/alternative name; use search for fuzzy matching |
| OpenAlex returns 0 or None IF | The journal may be too new (needs 2+ years of data); use --offline to check cache only |
| OpenAlex IF differs from JCR | Expected — OpenAlex uses its own article classification. Use for ranking, not formal citation. |
| Cache download fails | Check network; the bundled CSV still works offline |
| Wrong journal matched | Use more specific name; the fuzzy matcher picks the closest substring match |
FAQ
What does the journal-if skill do?
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.
How do I install journal-if?
Run npx skills add https://github.com/agents365-ai/365-skills --skill journal-if in your project. The skills CLI detects the agents you use and copies the skill into the right folder. For Claude Code you can also place the skill folder at ~/.claude/skills/journal-if/ (personal) or .claude/skills/journal-if/ (project).
Which AI agents can use journal-if?
Any agent that supports the open Agent Skills format (a folder with a SKILL.md file), including Claude Code, Codex, Cursor, GitHub Copilot, Gemini CLI, Windsurf, Cline, OpenCode and more.
Is journal-if safe to install?
No partner security audit is available yet. Skills can run commands and scripts, so read the SKILL.md and any bundled files before installing.
Who maintains journal-if?
It is published by agents365-ai in agents365-ai/365-skills. It has 365 recorded installs.
More from agents365-ai/365-skills
drawio-skill
agents365-ai/365-skills
Create, edit, synchronize, inspect, test, and publish editable draw.io diagrams. Use when the user explicitly requests draw.io/diagrams.net, needs a polished architecture, ERD, UML, sequence, C4, SysML, BPMN, network, swimlane, ML, or infrastructure diagram, wants code/IaC/SQL/OpenAPI/AsyncAPI/Protobuf converted into a diagram, or wants an existing diagram queried, reviewed, diffed, restyled, kept in sync, or made interactive. Prefer Mermaid/PlantUML elsewhere when the requested artifact is diagrams-as-code rather than an editable draw.io file.
excalidraw
agents365-ai/365-skills
Use when user requests diagrams, flowcharts, architecture charts, or visualizations. Also use proactively when explaining systems with 3+ components, complex data flows, or relationships that benefit from visual representation. Generates .excalidraw files and exports to PNG/SVG via Kroki API or locally using excalidraw-brute-export-cli.
creating-mermaid-diagrams
agents365-ai/365-skills
Generate Mermaid diagrams (.mmd) and export to PNG/SVG/PDF using mmdc CLI or Kroki API. USE THIS SKILL when user mentions diagram, flowchart, sequence diagram, class diagram, ER diagram, state machine, architecture, visualize, git graph, 画图, 架构图, 流程图, 时序图. PROACTIVELY USE when explaining ANY system with 3+ components, API flows, authentication sequences, class hierarchies, database schemas, or state machines. Supports 11+ diagram types with fully automatic layout.
plantuml-skill
agents365-ai/365-skills
Use when user requests diagrams, flowcharts, sequence diagrams, class diagrams, component diagrams, ER diagrams, architecture charts, or visualizations — including generating a diagram from existing source code, or rendering/extracting PlantUML embedded in a Markdown file to images (e.g. preparing docs for Confluence/Notion). Also use proactively when explaining systems with 3+ components, APIs, data flows, or class hierarchies. Generates .puml files and exports to PNG/SVG via Kroki API (no local install required).
tldraw-skill
agents365-ai/365-skills
Use when user requests diagrams, flowcharts, architecture charts, or visualizations. Also use proactively when explaining systems with 3+ components, complex data flows, or relationships that benefit from visual representation. Generates .tldr JSON files and exports to PNG/SVG locally using @kitschpatrol/tldraw-cli.
paper-fetch
agents365-ai/365-skills
Use whenever the user wants to obtain, download, or fetch a paper's PDF — given a DOI, an arXiv id, a paper title, a citation, or a list of DOIs. Trigger on phrases like "download this paper", "find the PDF for [DOI]", "grab me the [Nature/bioRxiv/arXiv] paper on X", "get the open-access version", "I need this article", or any bulk/batch paper download request, even when the user doesn't explicitly say "PDF" or "DOI". Resolves via Unpaywall → Semantic Scholar → arXiv → PubMed Central → bioRxiv/medRxiv → publisher direct (institutional opt-in) → Sci-Hub mirrors as last-resort fallback.
Popular other skills
hyperframes-cli
heygen-com/hyperframes
The HyperFrames CLI by job - scaffold, check, look at frames, edit the timeline, preview, render locally or in the cloud, publish, project history - plus reading its JSON and recovering from build or render failures.
triage
mattpocock/skills
Move issues and external PRs through a state machine of triage roles, categorise, verify, grill if needed, and write agent-ready briefs.
ask-matt
mattpocock/skills
Ask which skill or flow fits your situation. A router over the skills in this repo.
to-questionnaire
mattpocock/skills
Turn a decision you can't fully answer into a questionnaire for someone else to fill in.
loop-me
mattpocock/skills
Grill me about specs for the workflows I want to build, within this workspace.