Loading...
Loading...
Found 287 Skills
Corporate event opportunity scanner for A-share companies via Longbridge — identifies and analyses events that may create pricing dislocations: M&A / restructuring (asset injection / reverse merger), major shareholder increases / buybacks (positive signal), equity incentive plans (management alignment), index inclusion / exclusion (forced passive flows), and lockup expiry (potential selling pressure). Provides historical statistical patterns and trading window recommendations per event type. Triggers: "捕捉机会", "事件机会", "并购重组机会", "增持机会", "回购信号", "指数调整机会", "解禁压力", "事件套利", "捕捉機會", "事件機會", "並購重組機會", "增持機會", "回購信號", "指數調整機會", "解禁壓力", "event opportunity", "corporate event", "M&A opportunity", "buyback signal", "index inclusion", "lockup expiry", "event catalyst", "special situation", "event-driven".
Scores completed OKR sets at cycle close with KR-level scoring per the canonical OKR type enum (committed | aspirational | learning | operational_health | compliance_or_safety), committed-vs-aspirational interpretation, evidence quality assessment, learning synthesis, and next-cycle recommendations. Refuses to retroactively change targets or shrink committed scope, average away guardrail KRs, treat 0.7 as success for committed or compliance_or_safety KRs, equate effort with impact, or use scores for individual performance. Hands off to iterate-lessons-log, iterate-retrospective, define-hypothesis, measure-dashboard-requirements, measure-instrumentation-spec, and foundation-okr-writer.
Extracts figures and sub-figures from academic PDF papers. Supports Fig/Figure, Scheme, Chart, Supplementary Figure, Extended Data Figure (Nature), and Chinese equivalents (图/方案/示意图/附图/补充图). Sub-figure label recognition supports (a)/(A)/a)/(i)/(1)/a. formats. High-quality PNG output at configurable DPI. Use when user asks to "extract figure", "截取文献图片", "提取子图", "get figure from paper", "Scheme", "方案图", "补充图", "Supplementary Figure", or "Extended Data".
Use when stories, specs, BRDs, APIs, workflows, or equivalent delivery artifacts exist and you need to review them for testability, missing business rules, unclear behavior, scope ambiguity, and QA blocking gaps before generating tests. Supports `--quick-flow` for fast assumption-driven execution and `--full-flow` for question-driven verified execution. Explicit full or end-to-end spec refinement requests continue through the existing 18-stage refinement cascade.
Screen and identify undervalued stocks with strong fundamentals using professional equity research methodology. Use when the user asks to find undervalued stocks, screen for cheap or bargain stocks, identify value investing opportunities, perform fundamental stock analysis, find stocks trading below intrinsic value, or requests a stock screener based on financial metrics like P/E ratio, debt-to-equity, free cash flow, or ROIC.
Use when converting shaders or looking up API equivalents - GLSL to MSL, HLSL to MSL, GL/DirectX to Metal mappings, MTKView setup code
This skill should be used when the user mentions Jujutsu version control, "jj" commands, working with jj repositories, or asks about Git to Jujutsu equivalents. Triggers on keywords like "jujutsu", "jj", "jj-vcs", "jj repo", "jj commit", "jj log", "jj new", "jj squash", "jj rebase", "jj bookmark", or questions about Jujutsu workflows and concepts.
Model Kotlin persistence code correctly for Spring Data JPA and Hibernate. Covers entity design, identity and equality, uniqueness constraints, relationships, fetch plans, and common ORM (Object-Relational Mapping) traps specific to Kotlin. Use when creating or reviewing JPA (Java Persistence API) entities, diagnosing N+1 or LazyInitializationException, placing indexes and uniqueness rules, or preventing Kotlin-specific bugs such as data class entities and broken equals/hashCode.
Review the latest changes and check whether they comply with the project's documented guidelines (AGENTS.md, CLAUDE.md, or equivalent). Use when reviewing local diffs, recent commits, or feature work and you need a findings-first assessment of architecture, reuse, testing, and repo-specific rules.
Corporate event-driven analysis via Longbridge Securities — captures and classifies events that create pricing dislocations: major-shareholder increases/decreases, equity incentives, private placements, rights issues, buybacks, M&A/restructuring, index rebalancing, and management changes. Combines filings, corporate actions, and shareholder data to produce event signals. Triggers: "公司事件", "事件驱动", "大股东增持", "大股东减持", "股权激励", "定增", "配股", "回购", "并购重组", "指数调整", "管理层变更", "公告分析", "公司事件", "事件驅動", "大股東增持", "大股東減持", "股權激勵", "定增", "配股", "回購", "並購重組", "指數調整", "corporate event", "event-driven", "share buyback", "equity incentive", "major shareholder increase", "rights issue", "M&A arbitrage", "index rebalancing", "insider buying", "corporate action analysis".
Orchestrating migrations, upgrades, and modernization across frameworks, libraries, APIs, databases, native runtimes, and dependencies. Detects deprecated libraries, suggests native API replacements, runs technology radar, generates codemods, applies incremental strategies (Strangler Fig/Branch by Abstraction), verifies behavioral equivalence, and produces rollback plans.
Replace the usage of `expect` and similar functions from `package:matcher` to `package:checks` equivalents.