Use when designing, reviewing, or refactoring a CLI that must serve AI agents alongside humans, or when converting an API or SDK into an agent-usable CLI interface.
日本語の概要は準備中です。原文の説明を表示しています。
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.
インストールする前に、エージェントに与えられる指示の中身を確認できます。
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.
| 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 |
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:
{ "ok": true, "data": {...}, "meta": { "schema_version", "cli_version", "latency_ms" } }{ "ok": "partial", "data": { "succeeded": [...], "failed": [...] }, "meta": {...} }{ "ok": false, "error": { "code", "message", "retryable", ... }, "meta": {...} }| 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.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 |
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.
| 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) |
| 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 |
Run the appropriate journal_if.py command. The script handles:
| 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:
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
| 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 |
まだレビューはありません。使ってみた感想をお寄せください。
概要と使いどころ
Use when designing, reviewing, or refactoring a CLI that must serve AI agents alongside humans, or when converting an API or SDK into an agent-usable CLI interface.
日本語の概要は準備中です。原文の説明を表示しています。
Search free commercial-use creative assets across multiple online sources — photos, illustrations, icons, video footage, music, sound effects, and fonts. Use when the user needs to find assets for videos, PPTs, articles, or any content creation. Trigger on phrases like "find me a photo of", "search for icons", "I need background music", "find video footage", "search fonts", "找一张图片", "搜素材", "帮我找图标/视频/音乐/字体". Covers Pexels, Unsplash, Pixabay, Iconify, Freesound, Google Fonts and more — with API-backed search where available.
日本語の概要は準備中です。原文の説明を表示しています。
Query the Semantic Scholar academic corpus through AI2's Asta MCP server: keyword or title search with venue and date filters, who-cited-a-paper traversal, author profiles and publications, DOI/arXiv/PMID lookup, and ~500-word full-text snippets for evidence, with citation counts and h-index. Use when the user asks for papers on a topic, who cited a paper, an author's work, recent literature since a date, or a venue-scoped paper list. Requires the Asta MCP server.
日本語の概要は準備中です。原文の説明を表示しています。
Extract and organize frames from a Bilibili video (bangumi episode, UP upload, or a local file) into scenery shots and per-character image groups, using anime-specific person detection + CCIP character-identity embeddings. Two modes — cluster everyone, or pull out one (or several) named characters via reference folders. Use when the user wants to collect, extract, or organize anime frames/screenshots by character or by scenery from a Bilibili video. Read-only download for personal viewing/analysis; uploads nothing.
日本語の概要は準備中です。原文の説明を表示しています。
Fetch Bilibili (哔哩哔哩) video comments for UP主 self-analysis. Use when the user asks to collect, download, export, or analyze comments on a Bilibili video (BV号 / URL / UID). Produces JSONL + summary.json suitable for further Claude Code analysis (sentiment, keywords, audience trends). Read-only; does not post/edit/delete.
日本語の概要は準備中です。原文の説明を表示しています。
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.
日本語の概要は準備中です。原文の説明を表示しています。