テスト設計、脆弱性診断、品質保証（1.4万 件）
Genome-wide association studies (GWAS) with PLINK. Perform case-control and quantitative trait association testing using logistic/linear regression with covariates, generate Manhattan and QQ plots for result visualization. Use when running GWAS or association tests.
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Workflow for enrichment testing, ranked-gene analysis, pathway scoring, and pathway-focused visualization across omics outputs.
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。
Binder design ranking using ipSAE (interprotein Score from Aligned Errors). Use this skill when: (1) Ranking binder designs for experimental testing, (2) Filtering BindCraft or RFdiffusion outputs, (3) Comparing AF2/AF3/Boltz predictions, (4) Predicting binding success rates, (5) Need better ranking than ipTM or iPAE. For structure prediction, use chai or alphafold. For QC thresholds, use protein-qc.
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Grounded in first principles, rigorously examine and refine a user's plan, task, decision, goal, strategy, proposal, or idea through structured, progressively deeper questioning, in order to bridge the gap between the User and the Agent. Use when the user explicitly requests grilling, challenge, pressure-testing, cross-examination, red-team review, pre-mortem analysis, or a decision audit. The goal is to uncover unclear objectives, hidden assumptions, contradictions, weak evidence, missing information, overlooked constraints, dependencies, risks, trade-offs, failure modes, and misalignment between intended outcomes and likely real-world results. Begin by establishing a shared understanding of the user's actual intent, goals, constraints, and success criteria. Ask focused, high-leverage questions rather than broad or repetitive ones. Adapt each question based on previous answers, probing deeper where uncertainty, unsupported assumptions, or strategic weaknesses remain. Regularly summarize the current understanding of the user's intent and position to confirm alignment, expose misunderstandings, and refine the problem or goal definition. Distinguish facts, assumptions, hypotheses, and unknowns. Challenge reasoning rigorously while remaining constructive, respectful, and solution-oriented. Continue until the reasoning is internally coherent, evidence-aware, constraint-conscious, risk-assessed, and translated into a clearer, more actionable goal, decision, or plan. Ultimately, achieving the super-alignment.
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Audit a website's content, structure, SEO health, and technical setup through SandBase. Use when asked for website audit, content audit, SEO health check, site structure analysis, or technical assessment.
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Plan, implement, or review test driven development work in an existing codebase with compatibility, security, and verification controls. Use when the user explicitly requests test driven development work.
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Plan, implement, or review google cloud waf security work in an existing codebase with compatibility, security, and verification controls. Use when the user explicitly requests google cloud waf security work.
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。
Plan, implement, or review kubernetes security policies work in an existing codebase with compatibility, security, and verification controls. Use when the user explicitly requests kubernetes security policies work.
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Create or review audit support deliverables with traceable assumptions, decision criteria, ownership, and risk controls. Use when the user asks for audit support planning or analysis.
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Block a sender so their messages are dropped before decryption (and the relay is told to refuse their resends); re-allow one with `--remove`, or list blocked senders with `--list`. Use to stop unwanted or abusive mail from a specific sender, undo a block, or audit your block list. If the sender is not specified, ask with AskUserQuestion.
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。
Audit user-selected Markdown or text files for deterministic plain-language findings. Use only when the user explicitly invokes this skill.
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。
Cross-agent self-inspection of your AI-agent stack. Audits skills, MCP servers, hooks, plugins, commands, credentials, and memory files across Claude Code, Codex, OpenClaw, and NanoClaw. Produces a structured inventory and narrative briefing with cross-ecosystem risk analysis. Use when the user asks to audit their own setup, check what they have installed, review their agent stack security posture, or understand cross-tool interactions. Use when a user has accumulated skills/plugins/MCP servers over time and wants visibility into their attack surface. Use after installing new skills or plugins. Do NOT use for vetting external code before install (that is repo-forensics). Do NOT use for incident response during active attacks. Do NOT use for fixing or patching vulnerabilities (forensify is read-only).
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Security forensics for git repos, AI skills, and MCP servers. Audits dependencies, detects prompt injection, credential theft, runtime dynamism, manifest drift, known CVEs, CISA KEV (actively exploited) vulns, and 2026 attack patterns. Not for fixing vulnerabilities or pentesting.
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Runs recurring guard sweeps for operations, cost, security, workflow health, and docs drift. Use when the maintainer wants the repository checked and cleaned up without micromanaging each subsystem.
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References Serverless OpenClaw security model. Covers Bridge 6-layer defense, IDOR prevention, secret management, Cognito authentication, and IAM least privilege. Use as a security checklist when writing or reviewing code.
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Runs a comprehensive release review before tagging and publishing a new version. Reviews code, docs, tests, security, cost, and operations; use platform-native parallelism when available and a sequential fallback otherwise.
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。
Development workflow guide. Covers build, test, lint, format commands, package structure, Git hooks, TDD methodology, and coding conventions. Use when setting up dev environment, running tests, or following project conventions.
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Troubleshoots common issues. Covers CDK deploy failures, Docker build errors, Lambda agent issues, test failures, and OpenClaw compatibility. Use when encountering errors during development or deployment.
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Shows project progress, phase completion status, test coverage, and deployment info. Use when checking what has been implemented, what remains, or current operational state.
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Operates this repository as a solo maintainer across PR triage, issue handling, release work, deploys, ops checks, cost checks, security review, and docs drift. Use when the user wants you to just handle maintenance work end-to-end.
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 SDK for Python (the `ai` package). Use for Python model calls (LLMs, image, video, speech, embedding, transcription, reranking, or evaluation), agents, model interaction tests, tool calling, subagents, approvals, durable execution, telemetry, AI SDK UI backends, and custom providers.
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Brief description of what this skill does and when to use it.
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Use when implementing features or fixing bugs with strict Test-Driven Development (TDD). Activate for coding tasks that require new functionality, refactoring, or comprehensive test coverage, especially when the user mentions TDD or Test Driven Development.
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。
Browser automation CLI for AI agents. Use when the user needs to interact with websites, including navigating pages, filling forms, clicking buttons, taking screenshots, extracting data, testing web apps, or automating any browser task. Triggers include requests to "open a website", "fill out a form", "click a button", "take a screenshot", "scrape data from a page", "test this web app", "login to a site", "automate browser actions", or any task requiring programmatic web interaction.
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。