'loop' 검색 결과

Patterns and techniques for evaluating and improving AI agent outputs. Use this skill when: - Implementing self-critique and reflection loops - Building evaluator-optimizer pipelines for quality-critical generation - Creating test-driven code refinement workflows - Designing rubric-based or LLM-as-judge evaluation systems - Adding iterative improvement to agent outputs (code, reports, analysis) - Measuring and improving agent response quality

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Use when building a Python terminal UI inspired by Claude Code with Rich. Translates a detailed TypeScript/Ink-style visual reference into a staged Python architecture for logo, message stream, streaming Markdown, tools, diffs, prompt, footer, spinners, permissions, transcript mode, themes, accessibility, and tests. Separates Rich rendering from the input and widget responsibilities that require an application-owned event loop or an optional Textual layer.

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Also use for agentic data engineering pipelines, code generation agents, agent-powered CLI tools, MCP server development, or any system where an AI model calls tools, makes decisions, or loops

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Runs an autonomous experiment loop on any programming task: you define the goal, metric, and eval command; the agent edits code, measures, and keeps or discards each change until interrupted. Use when optimizing a measurable target (speed, accuracy, size, score) by iteration.

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Run an autonomous triage-resolve-review-merge loop to auto-pilot the GitHub issue backlog, resolving everything until done with zero prompts. Don't use for single-issue work (/issue-resolver), triage (/issue-triage), or PR review (/issue-pr-review).

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Normative sufficiency conditions for Initial Boundary Conditions (IBCs) and the SOP for the cheap-tier boundary refinement loop (/boundary). Trigger when: - Crafting, auditing, or refining a prompt/IBC destined for an expensive (architect-class) model or an autonomous worker dispatch. - Evaluating whether a task frame is sufficient to bound an agent walk. - Prompt contains: /boundary, IBC, initial boundary condition, boundary contract, sufficiency conditions, worker prompt, prompt refinement.

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Runnable driver for the deterministic campaign-execution protocol — the automaton that takes a validated campaign DAG to a correctly merged branch. Trigger when: - A campaign has a validated DAG + worker IBCs and the composer (or a cheap-tier runner) must DRIVE dispatch ⇄ reconcile as a loop rather than by hand. - Resuming a partially-executed campaign from its git history + sketch checkpoint after a halt or crash. - Prompt contains: /orchestrate, orchestration, drive the DAG, run the campaign, layer schedule, reconcile-and-merge, resume campaign.

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Bounded improvement loop: one artifact, fixed eval score, keep an edit only if strictly better. Use for AR_DESIGN/AR_FUNCTION/AR_ACCEPTANCE stages or standalone bounded iteration.

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Generate strategic-consultant-grade meeting minutes from transcripts or notes in Japanese OR English (matching the source language), then run a self-review loop (max 3 iterations) that checks for internal contradictions, action-item omissions, speaker-name errors, and date/day-of-week mistakes before reporting completion. Use this skill whenever the user asks to draft meeting minutes, summarize a transcript, or document a meeting discussion — including Japanese-language transcripts (議事録 / 会議メモ / 文字起こし) and English-language transcripts.

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Autonomous GAS development skill — code, deploy, test, and fix in a self-driving loop. Uses clasp for code management, Web App + gas-run.sh for auto-deploy/execution, and gws for spreadsheet read/write. Triggers on "GAS", "Apps Script", "spreadsheet automation", "clasp", "gws sheets".

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Use when diagnosing a repeated conceptual mistake and designing a targeted correction loop to replace the faulty mental model.

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生成スキルに knowledge/ を追加するとき読む。ナレッジ蓄積・検索・フィードバックループの設計を参照するとき読む。

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Analyze a project's harness maturity and guide staged adoption of Harness Engineering best practices (quality loops, safety gates, linters, CLAUDE.md optimization).

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自主Claude代码循环的模式与架构——从简单的顺序管道到基于RFC的多智能体有向无环图系统。

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You are an expert in the interface between LLMs and the outside world. You've seen tools that work beautifully and tools that cause agents to hallucinate, loop, or fail silently. The difference is almost always in the design, not the implementation.

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Build automated AI workflows combining multiple models and services. Patterns: batch processing, scheduled tasks, event-driven pipelines, agent loops. Tools: inference.sh CLI, bash scripting, Python SDK, webhook integration. Use for: content automation, data processing, monitoring, schedul...

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Inter-agent communication protocol for C-suite agent teams. Defines invocation syntax, loop prevention, isolation rules, and response formats. Use when C-suite agents need to query each other, coordinate cross-functional analysis, or run board meetings with multiple agent roles.

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Batteries-included agent component for React/Next.js from ui.inference.sh. One component with runtime, tools, streaming, approvals, and widgets built in. Capabilities: drop-in agent, human-in-the-loop, client-side tools, form filling. Use for: building AI chat interfaces, agentic UIs, SaaS...

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Find and fix WCAG 2.2 accessibility issues. Two modes — report (sweep a codebase or page, produce a prioritized written report, no edits) and fix (audit→edit→verify loop on a target). Prefers direct-CDP live-DOM auditing; falls back to a browser-MCP composition or HTML-string audits.

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Route agent work through AccInt's MCP memory loop: retrieve prior outcomes, resolve frames, and close commitments with evidence.

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Turn any domain folder of skills into a bounded agentic loop: compile a goal into a verifiable task plan, execute tasks with the domain's own tools, verify every task with machine-run checks, retry with caps, escalate to a human when budgets exhaust.

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Run a support investigation as a suggest-and-interpret loop, never executing anything yourself — orient to the product's support pack and follow the signal with judgment. Use when someone asks for help triaging, investigating, or resolving an operational or support issue on a deployment. Not for feature-development cards (see investigate-and-fix and implement-this).

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Educational single-threaded TypeScript vanity address generator for Solana using @solana/web3.js with async iteration, event-loop yielding, streaming generator API, and best-effort memory zeroization.

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Complete SolanaOS agent skill — install, configure, and operate the autonomous Solana trading runtime with Honcho v3 epistemological memory, multi-venue perp trading (Hyperliquid + Aster), on-chain intelligence with USD pricing, Telegram bot, gateway API, Tailscale mesh, hardware integration, and cross-session recall. Use when asked to install SolanaOS, query Solana blockchain data, manage wallets, run OODA trading loops, configure strategies, control BitAxe mining fleets, pair Seeker devices, or operate any SolanaOS runtime surface.

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