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Found 835 Skills
Captures human source verification for tracks, timestamps it, and updates track files. Use when sources need human review before generation.
This skill should be used when the user asks to "update study", "analyze new experiments", "update experiment document", or "refresh study notes". Produces academic-paper-quality experiment reports with matplotlib plots, executive summary with comparison tables, implementation structure, experimental results with figure interpretation, proposed improvements with code examples, hypotheses, limitations, and LaTeX PDF export with figures. Features incremental detection (only analyze NEW experiments), data extraction to DataFrame, automated plot generation, iterative writing improvement loop with quality criteria, zero-hallucination verification, and LaTeX PDF export. Usage - `/update-study logs/experiment.log study.md` or `/update-study "logs/exp1.log logs/exp2.log" results/ablation_study.md`
Use when receiving code review feedback, before implementing suggestions, especially if feedback seems unclear or technically questionable - requires technical rigor and verification, not performative agreement or blind implementation
Standardize requirement/feature changes in an existing codebase (especially Chrome extensions) by turning "改需求/需求变更/调整交互/改功能/重构流程" into a repeatable loop: clarify acceptance criteria, confirm current behavior from code, assess impact/risk, design the new logic, implement with small diffs, run a fixed regression checklist, and update docs/decision log. Use when the user feels the change process is chaotic, when edits tend to sprawl across files, or when changes touch manifest/service worker/OAuth/storage/UI and need reliable verification + rollback planning.
Specification-driven development with structured phases: Initialize, Plan, Tasks, Implement+Validate. Creates structured feature specs with traceability to requirements. Use when: starting projects, planning features, implementing with verification, or tracking decisions across sessions. Also use when the user wants to break a feature into tasks, plan before coding, track implementation progress, set up a new project structure, or organize work into specs and plans. Triggers on "map codebase", "initialize", "initialize project", "create feature", "plan", "tasks", "implement", "validate", "archive", "break this into tasks", "plan this feature", "start a new project".
Breaks work into bite-sized tasks before coding. Activates when a multi-step task needs planning — creates tasks small enough for a junior developer to follow (2-5 minutes each), with exact file paths, complete implementation details, and verification steps. References Linear issue context and project-specific test commands from CLAUDE.md.
Buy a domain, configure DNS, and connect it to your Vercel project. Handles purchasing through Vercel, linking existing domains, SSL setup, and DNS verification — all from the terminal.
Create forensically sound bit-for-bit disk images using dd and dcfldd while preserving evidence integrity through hash verification.
Use when the user asks to create a pull request. Build a complete PR using best-practice structure with rich details on changes, verification, QA evidence, risks, and rollout notes. Include issue linkage and clear testing commands/results in the PR body.
Use this skill when auditing AI agent skills for security vulnerabilities, prompt injection, permission abuse, supply chain risks, or structural quality. Triggers on skill review, security audit, skill safety check, prompt injection detection, skill trust verification, skill quality gate, and any task requiring security analysis of AI agent skill files.
Use when work must be verified in local Canvas Workbench, or when the user asks to run, open, or check a component in Workbench. Verifies that Canvas Workbench is available through the project's package runner, starts the local Workbench dev server, and keeps Workbench verification as part of the implementation workflow.
Universal deep research agent team. 13-agent pipeline for rigorous academic research on any topic. 7 modes: full research, quick brief, paper review, lit-review, fact-check, Socratic guided research dialogue, and systematic review with optional meta-analysis. Covers research question formulation, Socratic mentoring, methodology design, systematic literature search, source verification, cross-source synthesis, risk of bias assessment, meta-analysis, APA 7.0 report compilation, editorial review, devil's advocate challenges, ethics review, and post-research literature monitoring. Triggers on: research, deep research, literature review, systematic review, meta-analysis, PRISMA, evidence synthesis, fact-check, guide my research, help me think through, 研究, 深度研究, 文獻回顧, 文獻探討, 系統性回顧, 後設分析, 事實查核, 引導我的研究, 幫我釐清, 幫我想想, 我不確定要研究什麼, 研究方向, 研究主題.