longbridge-earnings
Post-earnings analysis skill — generates institutional-grade earnings update reports (8–12 page DOCX) and structured conversation summaries for companies under coverage. Covers beat/miss analysis, segment breakdown, margin trends, guidance assessment, updated estimates, and valuation. Supports US, HK, and A-share markets. Use this skill whenever the user wants a post-earnings analysis or quarterly-results writeup, even if they do not say "earnings update" verbatim. Triggers: "earnings update", "quarterly results", "Q1/Q2/Q3/Q4 results", "earnings report", "post-earnings analysis", "beat/miss",
npx skills add majiayu000/claude-skill-registry --skill longbridge-earnings --agent claude-code
Same command for any agent — swap --agent for codex, cursor, copilot.
Weekly change comes from our own snapshots, not the repository page — it measures attention, not adoption.
# Earnings Update Skill > **Response language**: match the user's input language — Simplified Chinese / Traditional Chinese / English. Both the DOCX report body and the in-chat summary follow the user's language; chart labels, axis titles, and file names always stay in English. ## When to Use | Trigger | Example | |---------|---------| | Post-earnings analysis | "Analyze TSLA.US latest earnings" / "帮我分析腾讯最新财报" | | Specific quarter update | "Tencent Q4 2024 earnings update" / "业绩更新" | | Quarterly results | "Q1/Q2/Q3/Q4 results for [company]" | **Do not trigger if:** user wants an initiation report. ## Data Sources Priority: **CLI (primary) → Web Search (supplement)** Use the Longbridge CLI for all market data. Before using any command, run `longbridge <command> --help` to check available options — the CLI is updated frequently. **CLI + Python pattern**: prefer reading from a file over piping into `python3 -c`. Multi-line JSON with embedded quotes can hit shell-quoting edge cases (especially under zsh's `-c` argument handling), so the safer pattern is: ```bash longbridge institution-rating 700.HK --format json > /tmp/rating.json python3 -c "import json; d = json.load(open('/tmp/ratin
- When to Use
- Data Sources
- Execution Workflow
- Output
- MCP fallback
- Related skills
- Reference Files
longbridge institution-rating 700.HK --format json > /tmp/rating.json
python3 -c "import json; d = json.load(open('/tmp/rating.json')); print(d)"What does the longbridge-earnings skill do?
Post-earnings analysis skill — generates institutional-grade earnings update reports (8–12 page DOCX) and structured conversation summaries for companies under coverage. Covers beat/miss analysis, segment breakdown, margin trends, guidance assessment, updated estimates, and valuation. Supports US, HK, and A-share markets. Use this skill whenever the user wants a post-earnings analysis or quarterly-results writeup, even if they do not say "earnings update" verbatim. Triggers: "earnings update", "quarterly results", "Q1/Q2/Q3/Q4 results", "earnings report", "post-earnings analysis", "beat/miss",
How do I install it?
Run `npx skills add majiayu000/claude-skill-registry --skill longbridge-earnings --agent claude-code` — it drops the skill into your project so the agent can pick it up. Swap the --agent value for codex, cursor or copilot if you use one of those.
Where does this skill come from?
From majiayu000/claude-skill-registry, a repository with 534 stars. We read it straight from the repository tree rather than a submitted listing, so what you see here is what is actually published.
Is a popular skill a good skill?
Not necessarily. Stars measure attention, not adoption — a repository can trend for a week and be abandoned. That is why we show the weekly change from our own snapshots next to the total, instead of a single flattering number.