「guardrail」の検索結果

Safety guardrails for destructive commands. (gstack)

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。

Design structured perspective-taking activities with anti-projection guardrails. Develops genuine understanding of complexity across history, social sciences, and literature — not performed empathy.

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。

Register, activate, and test a custom detekt rule in :quality:detekt-rules. Use when adding a DI/privacy/suppression guardrail rule or debugging a false positive.

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。

Drafts professional services agreements for healthcare providers and clients, covering HIPAA/HITECH compliance, BAA requirements, Anti-Kickback and Stark Law guardrails, credentialing warranties, malpractice insurance mandates, and patient care continuity on termination. Use when drafting healthcare provider contracts, medical services agreements, physician independent contractor agreements, or healthcare consulting engagements.

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。

Drafts U.S. commercial real estate access and indemnity (right-of-entry) agreements for pre-closing due diligence. Covers license grants, non-invasive vs invasive testing gates, insurance/endorsement requirements, indemnity with discovery carve-outs, restoration and lien remedies, confidentiality, and anti-indemnity guardrails. Trigger: access agreement, right of entry, due diligence access, Phase I/II, invasive testing, pre-PSA site inspection.

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 guide for designing and orchestrating multi-agent systems, agent swarms, 2026 Anthropic agentic design patterns, graph-based workflows (LangGraph, OpenAI Agents SDK, Google ADK, Mastra.ai), shared state memory, and human-in-the-loop guardrails in English and Indonesian.

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。

Handle blocked destructive commands. Use when dcg blocks rm -rf, git reset --hard, DROP DATABASE, kubectl delete, or when configuring agent safety guardrails.

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。

Manages skill-creator integration with GSD workflows including skill loading, session observation, bounded learning guardrails, and pattern detection. Use this skill whenever: executing any GSD phase (to ensure relevant skills are loaded first), starting or resuming a work session (to check for pending suggestions), the user asks about skills, patterns, or skill-creator status, performing code changes that might represent repeating patterns, the user corrects Claude's output (highest-signal observation), or when skill refinement, creation, or suggestion review is discussed. Critical for maintaining the adaptive learning layer.

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 context window discipline enforcement. Prevents the orchestrator from reading source files it will not edit, running diagnostic commands that waste context, and rationalizing delegation bypasses. Use when setting up orchestrator guardrails, reviewing delegation discipline, or diagnosing context window waste in multi-agent workflows. Activates PreToolUse hooks that surface decision points before source file reads and diagnostic command execution.

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。

Create, improve, or audit Vapi voice agent and Squad system prompts for production phone and web based voice agents. Use when the user wants help designing a Vapi assistant prompt, multi-assistant Squad prompt set, refining an existing prompt, creating prompt sections, building an intake or handoff workflow, improving tool-use instructions, adding guardrails, or optimizing voice-agent behavior for brevity, turn-taking, error handling, caller data collection, escalation, handoffs, and spoken formatting.

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。

Reviews an existing conjoint study for threats to inference and returns severity-ranked findings on design integrity, estimation, measurement error, external validity, and interpretation, including the guardrail against reading an AMCE as majority preference. Use when the user asks whether a conjoint design or analysis holds up, has referee comments on a conjoint, or wants a second opinion on estimation or interpretation. New designs go to conjoint-design, reshaping to conjoint-cleaning.

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。

Ensure agent safety - guardrails, content filtering, monitoring, and compliance

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 operating ProjectClownfish cluster workflows in this repo: reviewing GitHub Actions run artifacts, tuning worker/applicator guardrails, importing ghcrawl clusters, dispatching canaries, scaling batches, or deciding whether autonomous write-mode cluster cleanup is safe to ramp.

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。

Uses the WordPress wp-rest-api skill to help an agent design, register, validate, and troubleshoot custom REST routes without skipping schema, auth, or permission_callback details. This is for agent-led endpoint work in plugins, themes, or core-adjacent codebases, not for browsing the WordPress REST API as a product catalog.

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 hard pre-execution guardrails to Claude Code so destructive shell commands are blocked before an agent can run them.

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 VoltAgent to intercept, validate, and enforce input/output policies in TypeScript agent workflows.

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。

PencilPlaybook is the UI Skills / Taste-Skill for Pencil.dev + Claude Code — a design playbook that gives Claude real perceptual psychology and senior-level guardrails so it stops producing averaged-out AI slop.

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。

First-run guided setup for a fresh gAIOS clone. Interviews the user (identity, role, priorities, voice, connections, team, pain, guardrails) and fills the templates — CLAUDE.md, context/, references/voice.md, connections.md — then introduces the WAT / wiki / workflows / experiments features. Trigger on "/setup", "set me up", "get started", "onboard me", or a fresh clone where CLAUDE.md still has {{placeholders}}.

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。

Rates any SKILL.md on a 0-100 scale across 10 dimensions with a SHIP / REWORK / SCRAP verdict. Evaluates trigger precision, instruction clarity, output predictability, edge case coverage, anti-hallucination guardrails, developer experience, composability, open-source readiness, wow factor, and real-world utility. No flattery — calibrated against Anthropic's own skill-creator rubric. Use this skill whenever someone says "score this skill", "rate my skill", "is this skill good", "skill review", "skill audit", "roast my SKILL.md", "grade this", "will this skill work", "evaluate my skill", "how good is this", or pastes a SKILL.md and asks for feedback. Also trigger when comparing two skills, benchmarking a skill collection, or asking "what's wrong with this skill" — even without the word "score".

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 to analyze correction trends, surface recurring patterns, and graduate repeat corrections to guardrails or anti-patterns.

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 .NET AI agents and multi-agent workflows with Microsoft Agent Framework using the right agent type, threads, tools, workflows, hosting protocols, and enterprise guardrails.

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。

Validate planned changes against local framework rules and policy guardrails before implementation or creation.

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。

Policy for the cross-model council: when to hand off to an installed sibling plugin's own slash command (`/codex:*`) versus dispatching our `delegation-runner` (backend: codex|agy|…), which backend to pick, what permission posture to use, and the fan-out/cost discipline that applies regardless of backend — plus the council layer built on that substrate: which play to run, how a cast gets picked from the project roster, budget guardrails, and where project policy/commission config lives. Consult before delegating out to a peer agentic CLI, before choosing between a sibling plugin's command and our runner, before choosing a permission posture, before fanning out more than one external delegation concurrently, or before running a council play (`/…:council-run`).

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。

Monitor, cap, and recover from context accumulation in agentic systems. Covers per-cycle cost tracking, context window auditing, budget caps with enforcement policies, emergency pruning when approaching limits, and progressive disclosure integration to minimize token spend on routing. Use when running long-lived agent loops (heartbeats, polling, autonomous workflows), when context windows are growing unpredictably between cycles, when API costs spike beyond expected baselines, when designing new agentic workflows that need cost guardrails from the start, or when post-mortem analysis reveals a cost incident caused by context accumulation.

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。