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概要と使いどころ
Run or resume a deliverable active-outreach workflow across lead discovery, screening, customer intel, and outreach email. Use when an operator or system pipeline needs durable run state, visible intermediate artifacts, evidence gates, report-bound human approval, and a final editable email draft that is never auto-sent.
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。
Add a new Dagster asset to the pipeline. Use when creating a Bronze, Silver, or Gold layer asset.
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。
Isolate the root cause of ML performance drops, inconsistent evaluations, prediction errors, and training-serving mismatches across data, labels, splits, pipelines, models, metrics, and runtime behavior. Use when investigating a reproducible failure or regression, not routine model selection or general performance validation.
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 and implement infrastructure, CI/CD, container, deployment, observability, and operational configuration changes with least privilege, staged validation, and rollback awareness. Use for pipelines, infrastructure as code, Kubernetes, containers, release automation, monitoring, and production-readiness work; do not use to perform destructive production actions without explicit authorization.
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Audit npm or pip dependencies for outdated packages and known vulnerabilities. Use when checking package health, preparing for a release, reviewing dependencies before merging a PR, or when asked about outdated packages or security advisories.
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。
Expert Clay platform consultant for B2B data enrichment and workflow automation. Use when the user asks about Clay tables, waterfall enrichment, Clay credits, Clay AI columns, Claygent, enrichment workflows, Clay integrations, Clay exports, Clay table design, lead scoring in Clay, or building data pipelines in Clay. Also triggers on "Clay table", "enrichment waterfall", "Clay credits", "Claygent", "Clay AI column", "Clay export", "Clay providers", "enrich in Clay", "Clay column", "Clay formulas", "find emails", "email waterfall", "phone waterfall", "lead scoring", "Clay debugging", "Clay troubleshoot". Do NOT use for general CRM questions without Clay context, cold email copy (use cold-email-copy-playbook), or signal routing (use buying-window-signal-workflow).
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。
Expert-level computer graphics covering the rendering pipeline, rasterization, ray tracing, shaders, transformations, lighting models, and GPU programming.
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。
Run an infrastructure-first security audit of a repository - secrets archaeology, dependency supply chain, CI/CD pipeline, LLM/AI attack surface, agent skill supply chain, OWASP Top 10, STRIDE threat model, and data classification - with a confidence gate and a pre-emit verification gate that suppress speculative findings. Use when asked for a security audit, threat model, pentest-style review, OWASP pass, or a pre-release security check. Not for reviewing a single diff - use requesting-code-review for that.
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。
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>]
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。
Conception pipeline. Détecte le mode (epic/task/bug) selon le type d'issue ou le prompt et invoque les agents appropriés. Usage: /analyse [<issue#>] [<description>]
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。
Review-fix pipeline for Codex. Equivalent to the repository's Claude skill: collect review feedback, apply fixes through the existing review workflow, and prepare replies. Usage: /review [<issue#>|<PR#>]
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。
Execution pipeline for Codex. Detect epic/task/bug mode and implement with Codex models only. Usage: /implement <issue#>
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。
Orchestrator for agent-flow. Runs one issue or task through Implementer, Reviewer and QA as separate processes, with mechanical risk classification, a review-round cap and escalation to Needs Me, ending in a PR. Use for /implement <issue> or when asked to take an issue end to end ("have an agent take issue
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。
Build AI agents with Hugging Face's SmolAgents framework. Use when creating code-executing agents, tool-calling agents, multi-agent systems, agentic RAG, text-to-SQL pipelines, web browsing agents, or any multi-step AI workflows. Covers CodeAgent, ToolCallingAgent, custom tools, MCP integration, memory management, secure code execution (E2B, Docker, Blaxel), and model configuration (HF Inference, LiteLLM, Transformers, Ollama).
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。
Practical security review and hardening guidance for application code in Python, JavaScript/TypeScript, and Go. Use this skill whenever the user asks for a security review or audit, wants to harden authentication (password hashing, sessions, JWT, OAuth2/OIDC, MFA), fix OWASP Top 10 issues (injection, XSS, IDOR, CSRF, SSRF, deserialization), threat-model with STRIDE, clean up secrets and .env handling, or set up dependency scanning (pip-audit, npm audit, osv-scanner, gitleaks, SBOM). Also trigger for "make this secure", "is this safe to deploy", bcrypt/argon2id, rate limiting logins, RBAC/ABAC, CSP and security headers, cookie flags, and secure-by-default coding help.
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。
Build AI agents with LangChain framework. Use when building agents, tools, memory, MCP integrations, RAG pipelines, multi-agent systems, or any LLM-powered applications using LangChain or LangGraph in Python or TypeScript.
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。
Use when the user asks to verify a story or ticket implementation against its spec - per-AC verdicts, code reuse and design conformance, dead code, then adversarial maintainer verification. Requires the qa/review agent roles registered by scripts/install-codex.sh. Keywords: story QA, acceptance criteria, spec conformance, AC coverage, QA this branch, verify story.
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。
Use when choosing .NET concurrency patterns for async I/O, queues, pipelines, or thread safety. Keywords: async/await, channels, dataflow, Rx, lock contention, producer consumer, parallel processing.
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。
Use when the user asks for a phase-gated refactoring or redesign loop - session-blind workers map and trace the area, empirical probes precede the design, an approval gate guards implementation, and a conformance audit re-checks the branch after any design change. State persists in .episteme/DESIGN-<slug>.md. Requires the refactor agent roles registered by scripts/install-codex.sh. Keywords: refactor loop, redesign, design gate, enumerate before design, conformance audit.
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。
Use when optimizing test suite performance — database setup, seeder optimization, parallel testing, CI pipeline efficiency, or RefreshDatabase alternatives.
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。
Use when the rule set is over the Augment budget, when a new rule would breach it, or when asked to audit / merge / prune rules — runs the audit pipeline and proposes a verdict per rule.
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。
Refine a persona from recent corrections — tightens its Unique Questions, governance-gated; explicit request only. Skill analog → skill-improvement-pipeline.
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。
Use when constructing the forecast call — commit / best-case / pipeline categorisation, deal-level evidence test, accuracy retro-loop. Triggers on 'build the forecast', 'why does our commit miss'.
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。
Three-round editorial review before publication.
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。