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Found 5,940 Skills
Discounted cash flow (DCF) valuation model built from Longbridge financial data — historical FCF (operating cash flow minus capex), projected FCF with growth assumptions, WACC (Beta / risk-free rate / equity risk premium), terminal value, intrinsic value vs current price, and margin of safety. Triggers: "DCF", "现金流折现", "内在价值", "自由现金流", "WACC", "折现率", "安全边际", "终值", "现金流贴现", "現金流折現", "內在價值", "自由現金流", "折現率", "安全邊際", "DCF model", "discounted cash flow", "intrinsic value", "free cash flow", "WACC", "discount rate", "margin of safety", "terminal value", "Gordon growth".
Suggest tests worth writing for a feature using the ZOMBIES heuristic (Zero, One, Many, Boundaries, Interface, Exceptions, Simple scenarios). Pass a free-text feature description, or omit args to use the current branch's diff. Outputs only the categories that apply — not a full ZOMBIES checklist.
Implement a prepare-environment script (Bash on macOS/Linux, PowerShell on Windows) for an arbitrary programming language, following the same conceptual pattern as the bundled Java reference script in assets/. Use when the user wants to add a one-time per-build setup step (install deps, pre-build artifacts, populate caches) for a new language (Python, Node.js, Go, Rust, Flutter, etc.) to a ***plain project, or wants to regenerate / adapt the existing Java runner.
Behavioral frameworks, technical interview patterns, system design, coding, and negotiation prep
Generates a curated supplementary reading list from any course syllabus using Consensus academic search. Grill-me intake (syllabus input format + course audience + year range) plus a grouping forcing-options checkpoint before any search runs — so the reading list matches the course's level and recency need. Parses the syllabus to extract topics and learning outcomes, searches Consensus for recent peer-reviewed papers per topic, and produces a professionally formatted .docx with clickable Consensus links, plain-language summaries calibrated to audience level, and Bloom-higher-order discussion questions tied to course learning goals. Triggers whenever a user uploads a syllabus, course outline, or curriculum document and wants supplementary readings. Also triggers on: 'syllabus reading list', 'find papers for my course', 'create a reading list from this syllabus', 'recent research for my class', 'supplementary readings', 'find journal articles for these topics', 'what recent papers cover this material', 'any new research on these course topics', 'update my syllabus with recent papers'. Even casual mentions when a syllabus is attached should trigger this skill.
Interactive setup guide for using Infisical as a secret management tool in your projects. Helps users integrate Infisical into local development (CLI), Docker containers (build-time and runtime secret injection), CI/CD pipelines (GitHub Actions, GitLab CI), Kubernetes (Operator + CRDs), and application code (Node.js, Python, Go, Java, .NET, Ruby SDKs). Also walks through choosing and configuring machine identity auth methods (Universal Auth, AWS Auth, Kubernetes Auth, OIDC, etc.). Use this skill whenever someone asks about: using Infisical, injecting secrets, infisical run, infisical init, connecting their app to Infisical, Docker secrets, Kubernetes secrets operator, machine identity setup, SDK initialization, CI/CD secret injection, or 'how do I get my secrets into my app'.
Count the Tokens consumed by the local Codex in recent time by task purpose dimension, and output a Chinese table including model and category proportions; output the Faster x2 status only when explicit session-level fields exist.
Guides secure software delivery and DevSecOps for cleared/classified or high-side programs—disconnected or air-gapped CI/CD, artifact promotion across classification boundaries (conceptual), SBOM/signing/ provenance, SAST/DAST/secrets/IaC/container gates, supply-chain controls, STIG/CIS deploy baselines, IaC for classified landing zones, cleared developer workstations, build/deploy audit logging, and ATO/RMF pipeline evidence (not SSP ownership). Use for classified DevSecOps, cleared pipeline, high-side CI/CD, air-gapped build, cross-domain release, classified software delivery, STIG pipeline, ATO evidence CI, SBOM classified, secure software factory—not portfolio cyber governance (classified-cyber-security-senior-manager), ISSO/SSP (information-systems-security-officer-classified-specialist), commercial-only DevSecOps (devsecops), general DevOps (devops), build-only validation (build-validator), pentest (penetration-tester), or enterprise GRC-only (compliance-specialist).
Guides privacy research engineering for safeguards—PII and sensitive-data detection research, redaction and de-identification evals, memorization and extraction risk studies, privacy benchmarks and labeled corpora, logging/retention minimization for safety pipelines, and research memos on privacy–utility trade-offs for guardrail systems. Use when measuring PII detector quality, designing privacy eval suites for moderation stacks, studying training-data leakage or prompt logging risk, or recommending privacy mitigations for safeguard models—not for SOC 2/GDPR evidence automation (compliance-engineer), legal DPIA or AI policy (ai-risk-governance), harm/toxicity classifier R&D (ml-research-engineer-safeguards), production inference gateways (ml-infrastructure-engineer-safeguards), or general non-privacy research (ai-researcher).
A qualitative research assistant tool based on Braun & Clarke's Reflexive Thematic Analysis framework. Supports two input modes: (1) Provide raw interview text directly → The skill completes initial TA coding for each document, then proceeds to theme identification after summarization; (2) Provide existing initial coding pool → Directly enter the process of clustering, review, and naming suggestions. Outputs a structured candidate theme table, clearly marking codes with ambiguous boundaries and naming suggestions to be decided by researchers. This skill is triggered when users mention terms such as "thematic analysis", "theme coding", "help me cluster codes", "extract themes from codes", "Braun Clarke", "candidate themes", "how to categorize these codes into themes", "help me check the theme structure", "conduct thematic analysis on interviews". Note the difference from grounded-coding: grounded-coding focuses on category construction and theoretical relationships for procedural grounded theory; thematic-analysis focuses on semantic theme identification following the Braun & Clarke approach, outputting theme structures rather than theoretical propositions.
Soroban smart contract development on Stellar (Rust SDK). Covers project setup, contract structure, storage types, authorization, cross-contract calls, events, error handling, testing (unit, integration, fuzz, property, mutation, fork, differential), security patterns and vulnerability classes, advanced architecture patterns (upgrades, factories, governance, DeFi primitives), and common pitfalls. Use when writing, testing, securing, or shipping Soroban contracts.
Wire Firebase Auth (email/password, Google, Apple) and Cloud Firestore into an Ionic Capacitor app. Trigger when adding Firebase Auth, Firestore, social sign-in via Firebase, or backend persistence using Google's Firebase platform.