Azure AI Content Safety SDK for Python. Use for detecting harmful content in text and images with multi-severity classification.
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概要と使いどころ
Azure AI Content Safety SDK for Python. Use for detecting harmful content in text and images with multi-severity classification.
日本語の概要は準備中です。原文の説明を表示しています。
AI-powered E2E web testing — eyes and hands for AI coding tools. Declarative YAML scenarios, Playwright execution, visual matching (OpenCV + OCR), platform auto-detection (Flutter/React/Vue), learning DB. Install: npx skills add ksgisang/awt-skill --skill awt -g
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First-principles assumption auditor. Classifies each hidden assumption (fact / convention / belief / interest-driven), ranks by fragility × impact, and rebuilds conclusions from verified premises. Bilingual: auto-detects Chinese or English.
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Comprehensive REST API design review with automated linting, breaking-change detection, and design scorecards. Catches inconsistent conventions, missing versioning, and design smells before APIs ship. Use when reviewing a PR that adds or changes API endpoints, auditing an existing API for v2 migration, or establishing API standards for a team.
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Use when assessing AI/ML systems for prompt injection, jailbreak vulnerabilities, model inversion risk, data poisoning exposure, or agent tool abuse. Covers MITRE ATLAS technique mapping, injection signature detection, and adversarial robustness scoring.
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Audits GitHub Actions workflows for security vulnerabilities in AI agent integrations including Claude Code Action, Gemini CLI, OpenAI Codex, and GitHub AI Inference. Detects attack vectors where attacker-controlled input reaches. AI agents running in CI/CD pipelines.
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用少量竞品网址和关注字段,生成适合人工复核的竞品变化汇总。首版默认复用 changedetection.io 做上游监控底座。
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Audit whether tests detect broken behavior by tracing assertions and running narrow controlled mutations in an isolated workspace; use for test-quality reviews, not routine test execution.
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Scans CopilotKit's public product / pricing / Premium pages at the start of every weekly report to produce the authoritative list of COMMERCIAL surfaces (Premium · CopilotKit Enterprise · Intelligence Platform · paid tiers) and detect any newly-added or changed commercial feature since last week. This list defines what the report's 🏢 Enterprise section is about — CopilotKit's commercial/paid product, NOT "CopilotKit running inside an enterprise company." Emits the surface list + a free-vs-paid classifier the report uses to decide "does this issue hit a commercial surface?", plus a diff of what changed. Runs as a subagent (many web fetches) so the orchestrator's context stays small. Invoked by weekly-report (spawned at report start) and the enterprise skill; also triggers on "scan product surfaces", "what's premium", "commercial surfaces", "did we add a premium feature".
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Mint a new YYYY-MM-DD-exact-coding-baseline snapshot under research/workflow-dev/export/. Detects the current best correctness- oriented workflow from research/workflow-dev/workflow-construction.md (or takes an explicit source-workflow argument) and transforms it from a lab workflow into a consumer-ready one on three axes: strips lab-only measurement content, re-enables human-in-the-loop checkpoints, and converts auto-loading config into an explicitly-invoked skill. Supports both promoted EXACT Coding lines: Opus/Hybrid and SOL/Predictive TDD. Exports Claude Code, pi, OpenCode, cursor-agent and, for SOL, Copilot. Trigger when the user says "exact-coding baseline export", "neue exact-coding baseline", "exact-coding-baseline-export", or asks to refresh the baseline snapshot.
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Keep your constraints healthy — lifecycle management with automatic staleness detection.
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Expert-level exoplanet science covering detection methods, orbital dynamics, planetary atmospheres, habitability, and the search for biosignatures.
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Expert-level particle physics knowledge. Use when working with the Standard Model, quarks, leptons, bosons, fundamental forces, Feynman diagrams, quantum field theory, particle accelerators, or particle detectors. Also use when the user mentions 'Standard Model', 'quark', 'lepton', 'boson', 'Higgs', 'gluon', 'neutrino', 'antimatter', 'Feynman diagram', 'QCD', 'QED', 'electroweak', 'LHC', or 'particle accelerator'.
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Expert-level analytical chemistry knowledge. Use when working with chromatography, spectroscopy, electroanalytical methods, sample preparation, quantitative analysis, calibration, statistics, or instrumental analysis. Also use when the user mentions 'HPLC', 'GC', 'mass spectrometry', 'atomic absorption', 'ICP', 'titration', 'calibration curve', 'detection limit', 'NMR', 'chromatography', 'electrochemistry', 'sample preparation', or 'method validation'.
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Comprehensive quality control for U.S. patent application filing documents. Use when the user asks to QC, check, validate, or review patent filing documents before submission to the USPTO. Performs 70+ automated and manual checks across specification, drawings, ADS, declaration, assignment, and power of attorney documents. Detects cross-document inconsistencies, formatting issues, missing required fields, and common errors.
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Use for any question about a codebase, its architecture, file relationships, or project content — especially when graphify-out/ exists, where the question should be treated as a graphify query first. Turns any input (code, docs, papers, images, videos) into a persistent knowledge graph with god nodes, community detection, and query/path/explain tools.
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Diagnoses failing GitHub Actions runs by reading logs, identifying the root cause, and suggesting fixes. Use this skill whenever a user shares a GHA run URL, pastes runner log output, mentions a failing workflow, asks why a CI job is broken, or says anything like "my GHA is failing", "workflow failed", "can you check my run", or "CI is broken". Also trigger when raw log text is detected in the conversation that appears to come from a GitHub Actions runner. Do NOT use for general GHA workflow authoring questions, YAML formatting help, or passing runs with no failure context.
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Conception pipeline for Codex. Equivalent to the repository's Claude skill: detect epic/task/bug mode, then delegate to the existing repo agents and workflows. Usage: /analyse [<issue#>] [<description>]
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Execution pipeline for Codex. Detect epic/task/bug mode and implement with Codex models only. Usage: /implement <issue#>
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Evaluate design from a UX perspective, assessing visual hierarchy, information architecture, emotional resonance, cognitive load, and overall quality with quantitative scoring, persona-based testing, automated anti-pattern detection, and actionable feedback. Use when the user asks to review, critique, evaluate, or give feedback on a design or component.
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Code comment accuracy verification, documentation completeness assessment, comment rot detection.
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Error handling review — silent failure detection, catch block analysis, error logging.
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General code quality review — project guideline compliance, bug detection, code quality analysis.
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Detect Git remote URL for GitHub integration
日本語の概要は準備中です。原文の説明を表示しています。