Query train schedules and remaining tickets from China Railway 12306.
Works with
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Before installing skills in Cursor, ensure your development environment meets these requirements:
node --version12306Execute the skills CLI command in your project's root directory to begin installation:
Fetches 12306 from kirorab/12306-skill and configures it for Cursor.
The CLI shows a list of agents. Use arrow keys and space to select Cursor:
Confirm successful installation by checking the skill directory location:
Restart Cursor to activate 12306. Access via /12306 in your agent's command palette.
We perform automated surface-level scans (Gen AI Scanner, Socket, Snyk) during installation. These checks detect common vulnerabilities but do not guarantee complete security. Always review skill source code and verify the publisher's reputation before production use.
Skills execute code in your environment. Always review source, verify the publisher, and test in isolation before production.
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Create detailed user stories, acceptance criteria, and feature specs
Example
Generate user stories for 'password reset feature' with acceptance criteria, edge cases, and test scenarios
Reduce spec writing time by 50%, ensure comprehensive coverage
Research competitors, compare features, identify gaps
Example
Analyze 5 competitor products, create feature comparison matrix, suggest differentiation opportunities
Complete competitive research in 2 hours instead of 2 days
Evaluate features using frameworks (RICE, ICE, Kano) and create prioritized backlogs
Example
Score 20 feature ideas using RICE framework, generate prioritized roadmap with rationale
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Query train schedules and remaining tickets from China Railway 12306.
node {baseDir}/scripts/query.mjs <from> <to> [options]
-f md): prints table to stdout# All trains from Beijing to Shanghai (defaults to today)
node {baseDir}/scripts/query.mjs 北京 上海
# Markdown table output (to stdout, good for chat)
node {baseDir}/scripts/query.mjs 北京 上海 -t G -f md
# Morning departures, 2h max, with second class available
node {baseDir}/scripts/query.mjs 上海 杭州 -t G --depart 06:00-12:00 --max-duration 1h --seat ze
# Only bookable trains arriving before 6pm
node {baseDir}/scripts/query.mjs 深圳 长沙 --available --arrive -18:00
# Custom output path
node {baseDir}/scripts/query.mjs 广州 武汉 -o /tmp/tickets.html
# JSON output (to stdout)
node {baseDir}/scripts/query.mjs 广州 武汉 --json
-d, --date <YYYY-MM-DD>: Travel date (default: today)-t, --type <G|D|Z|T|K>: Filter train types (combinable, e.g. GD)--depart <HH:MM-HH:MM>: Depart time range (e.g. 08:00-12:00, 18:00-)--arrive <HH:MM-HH:MM>: Arrive time range (e.g. -18:00, 14:00-20:00)--max-duration <duration>: Max travel time (e.g. 2h, 90m, 1h30m)--available: Only show bookable trains--seat <types>: Only show trains with tickets for given seat types (comma-separated: swz,zy,ze,rw,dw,yw,yz,wz)-f, --format <html|md>: Output format — html (default, saves file) or md (markdown table to stdout)-o, --output <path>: Output file path, html mode only (default: {baseDir}/data/<from>-<to>-<date>.html)--json: Output raw JSON to stdout| Column | Meaning |
|---|---|
| 商务/特等 | Business class / Premium (swz) |
| 一等座 | First class (zy) |
| 二等座 | Second class (ze) |
| 软卧/动卧 | Soft sleeper / Bullet sleeper (rw/dw) |
| 硬卧 | Hard sleeper (yw) |
| 硬座 | Hard seat (yz) |
| 无座 | Standing (wz) |
Values: number = remaining seats, 有 = available (qty unknown), — = not applicable
node {baseDir}/scripts/stations.mjs 杭州
node {baseDir}/scripts/stations.mjs 香港西九龙
CRITICAL: When querying by city name (e.g., "武汉", "上海", "深圳", "广州"), the API may return trains from/to ANY station in that city, not just the main station.
Common Pitfalls:
Best Practice - Always verify exact stations:
stations.mjs to list all stations in the city:
node {baseDir}/scripts/stations.mjs 武汉
node {baseDir}/scripts/query.mjs 武汉 上海虹桥 -f md
When planning transfers (中转):
--json) to verify exact station namesFor accurate results, follow this workflow:
List stations in departure city:
node {baseDir}/scripts/stations.mjs 北京
List stations in arrival city:
node {baseDir}/scripts/stations.mjs 上海
Query with exact station names (e.g., 北京南 → 上海虹桥):
node {baseDir}/scripts/query.mjs 北京南 上海虹桥 -d 2026-03-05 -f md
For transfers: Always verify both segments use the same station by checking fromStation and toStation in JSON output.
{baseDir}/data/stations.jsonMake data-driven prioritization decisions faster
Draft PRDs, status updates, and stakeholder presentations
Example
Create executive summary of Q3 roadmap, monthly progress report, feature launch announcement
Save 3-5 hours/week on communication overhead
Prerequisites
Time Estimate
30-60 minutes to see productivity improvements
Steps
Common Pitfalls
✓ Do
✗ Don't
💡 Pro Tips
✓ Use when
Use for user story writing, competitive research, roadmap prioritization, stakeholder communication, and PRD drafting. Best for reducing repetitive documentation and research work.
✗ Avoid when
Avoid for strategic product vision (requires deep customer empathy), pricing decisions (needs market and financial expertise), or when face-to-face customer discovery is more valuable than speed.
mattpocock/skills
parcadei/continuous-claude-v3
cursor/plugins
ailabs-393/ai-labs-claude-skills
pproenca/dot-skills
mattpocock/skills
Useful defaults in 12306 — fewer surprises than typical one-off scripts, and it plays nicely with `npx skills` flows.
Keeps context tight: 12306 is the kind of skill you can hand to a new teammate without a long onboarding doc.
We added 12306 from the explainx registry; install was straightforward and the SKILL.md answered most questions upfront.
I recommend 12306 for anyone iterating fast on agent tooling; clear intent and a small, reviewable surface area.
We added 12306 from the explainx registry; install was straightforward and the SKILL.md answered most questions upfront.
12306 is among the better-maintained entries we tried; worth keeping pinned for repeat workflows.
Useful defaults in 12306 — fewer surprises than typical one-off scripts, and it plays nicely with `npx skills` flows.
12306 fits our agent workflows well — practical, well scoped, and easy to wire into existing repos.
12306 has been reliable in day-to-day use. Documentation quality is above average for community skills.
12306 reduced setup friction for our internal harness; good balance of opinion and flexibility.
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