'code mode' 검색 결과

Build remote MCP servers, which let AI agents call external tools, on Cloudflare Workers. This skill covers server code, tool definitions, OAuth authentication, local testing, deployment, and connecting a Codex client.

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• Building a remote MCP server
• Adding OAuth authentication to MCP tools
• Exposing external APIs as tools for AI agents

Create a Markdown threat model grounded in a codebase. Identify valuable assets, boundaries between trusted and untrusted components, realistic attack paths, and mitigations, then prioritize risks using explicit assumptions about likelihood and impact.

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• Map attack paths across a codebase
• Assess threats within a specific project directory
• Prioritize risks to data and credentials

Apply a specific set of Rails conventions to design, implementation, and code review. It keeps business logic in models, represents state changes as records, limits dependencies, and uses Minitest with fixtures, or predefined test data.

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• Designing Rails models and database changes
• Representing state changes with separate records
• Reviewing code for consistent Rails conventions

Guides you through connecting external services to Claude Code plugins using MCP, a protocol for exposing services as tools. Covers connection types, configuration files, authentication, tool permissions, and testing.

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• Connecting a database to a Claude Code plugin
• Configuring OAuth or token authentication
• Building workflows across multiple MCP servers

Prepare coding tasks for delegation to an authorized agent’s AI command-line tool. Set up and synchronize the workspace, write precise change requests, then review returned changes and run relevant checks before reporting completion.

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• Delegating code implementation or bug fixes to an AI CLI
• Writing coding requests with clear acceptance criteria
• Reviewing and testing changes returned by a CLI

Fit regression and time series models in Python, then examine coefficients, uncertainty, and predictions. Check model assumptions, investigate unusual observations, and compare alternatives using detailed statistical summaries and diagnostic tests.

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• Interpret regression coefficients and confidence intervals
• Model binary outcomes or event counts
• Forecast time series with uncertainty intervals

Guides you through connecting external services to Claude Code plugins using MCP, a protocol for exposing services as tools. Covers connection types, configuration files, authentication, tool permissions, and testing.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Connecting a database to a Claude Code plugin
• Configuring OAuth or token authentication
• Building workflows across multiple MCP servers

Helps create specialized Claude Code agents for tasks such as code review and debugging. Covers custom instructions, tool access, model selection, configuration files, and ways to connect agents across tasks.

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• Creating a dedicated code review agent
• Configuring a debugging agent
• Choosing tools and models for each role

Analyze a codebase to identify valuable assets, attack entry points, and realistic abuse paths. Produce a concise Markdown threat model that explains risk priorities, distinguishes existing protections from proposed mitigations, and makes assumptions explicit.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Map attack entry points in a codebase
• Assess threats within a specific project directory
• Prioritize risks to sensitive data and credentials

Connect external services and databases to Claude Code plugins through MCP, a protocol for exposing tools to agents. The skill guides server configuration, connection choices, authentication, tool permissions, and testing so plugins can use those services.

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• Adding a local MCP server to a Claude Code plugin
• Configuring OAuth or token authentication for a service
• Building a plugin that uses multiple services

Find current official documentation for building with OpenAI products and APIs. Provides source-linked guidance on Codex, APIs, SDKs, and model capabilities or limits, using dedicated documentation tools before searching official OpenAI websites.

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• Check how to use the Responses API
• Look up Codex features and usage
• Research app development with Apps SDK or Agents SDK

Drive Codeman, the session manager this agent is running inside, over its HTTP API, from any agent CLI (Claude Code, Codex, Gemini CLI, OpenCode, Antigravity, Grok Build, DeepSeek Harness, OMP): list sessions, start worker sessions in any installed CLI, send them prompts, block until they finish (wait / wait-output / send-and-wait), read their output, and clean up; where available, message claude workers directly (Claude Code cross-session messaging). Use when asked to orchestrate or parallelize work across Codeman sessions, get a second opinion from another CLI or model, watch another session, or start and manage workers. Only usable inside a Codeman-managed session (CODEMAN_MUX=1); refuse to act otherwise.

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This skill should be used to spawn specialized OpenAI Codex CLI subagents for code review, debugging, architecture analysis, security audits, refactoring, documentation, comparative evidence adjudication, and autonomous /goal runs. It adds each persona through process-local developer instructions while preserving the project's AGENTS.md chain, including during parallel launches. Supports GPT-6-Astra across low, medium, high, xhigh, max, and ultra reasoning with default or priority service tiers, plus GPT-5.6 and GPT-5.5 models. Triggers on 'delegate to Codex', 'Codex Astra', 'Astra subagent', 'Codex subagent', 'code review agent', 'security audit', 'refactor with Codex', 'goal run', 'autonomous goal', 'have Codex weigh this'.

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Manage persistent coding sessions across Claude Code, Codex, Antigravity (agy), Grok Build, and OpenCode engines. Use when orchestrating multi-engine coding agents, starting/sending/stopping sessions, running multi-agent council collaborations, cross-session messaging, ultraplan deep planning, ultrareview parallel code review, autoloop autonomous workspace iteration, ultraapp building deployable web apps from a structured Q&A interview, switching models/tools at runtime, exposing the orchestrator's 78 tools as an MCP server to Hermes Agent / Claude Desktop / Cursor / Cline / Continue / Zed / Windsurf / Goose, or running as an Agent Client Protocol (ACP) agent that Zed / JetBrains / Neovim / Emacs / VS Code / dsh can drive directly. Triggers on "start a session", "send to session", "run council", "ultraplan", "ultrareview", "autoloop", "ultraapp", "Forge tab", "build a web app", "one-click app", "AppSpec", "autonomous iteration", "iterate until goal", "auto research", "switch model", "hand off a session", "session handoff", "switch engine", "continue on codex", "continue on claude", "move this session to another engine", "multi-agent coding", "coding session", "session inbox", "grok session", "grok build", "opencode", "mcp server", "clawo-mcp", "hermes mcp", "model context protocol", "ultracode", "dynamic workflow", "fanout", "fan-out", "best-of-N", "steer turn", "interrupt turn", "fork thread", "rollback turns", "acp", "agent client protocol", "clawo acp", "zed agent", "jetbrains agent", "external agent", "dsh subagent", "deepseek harness", "clawo runs", "run ledger", "session cost", "coding-agent token usage", "spend cap", "budget limit", "maxBudgetUsd", "durable workflow", "resume a run", "verify a coding run", "acceptance contract", "evidence bundle", "did the agent's tests actually pass", "protected tests", "agent edited the tests", "human gate", "repair loop", "clawo workflow", "clawo verify", "clawo solve", "clawo fanout", "fix and verify", "solve from the terminal".

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Evaluates code generation models across HumanEval, MBPP, MultiPL-E, and 15+ benchmarks with pass@k metrics. Use when benchmarking code models, comparing coding abilities, testing multi-language support, or measuring code generation quality. Industry standard from BigCode Project used by HuggingFace leaderboards.

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Claude Code의 로컬 사용 로그에서 토큰 사용량과 예상 비용을 집계합니다. 모델·세션·날짜별 비용을 확인하고 예산과 비교하며 CSV로 내보낼 수 있습니다.

• 오늘과 어제의 지출 비교
• 모델·세션별 비용 확인
• 예산과 지출 비교

여러 관점으로 정리한 중요한 의사결정 초안에 Codex의 외부 비평을 한 차례 추가합니다. 결론의 약점, 누락된 실패 가능성, 반대 의견의 반영 여부를 확인합니다.

• 판단이 어려운 중요 초안 검토
• 초안에 빠진 실패 가능성 확인
• 강한 반대 의견의 누락 확인

Claude Code에서 Odysseus의 작업, 메일, 일정, 기억, 문서를 관리합니다. 권한 범위가 정해진 API로 모델 서비스 시작, 로그 확인, 중지도 수행합니다.

• 시간을 지정한 알림 등록
• 메일을 읽고 답장 초안 작성
• 일정, 선호 사항, 문서 저장

Audit a Claude Code setup for installation problems, broken settings, unused extensions, and duplicated instructions. It reviews local usage evidence, recommends cleanup, and applies approved fixes, with separate confirmation for permission changes.

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• Diagnose installation and configuration problems
• Review unused skills, MCP servers, and plugins
• Trim duplicated or unnecessary CLAUDE.md guidance

Review Git changes with the ocr command-line tool and a configured AI model. Get line-level findings grouped by severity for working changes, commits, or branch comparisons, with code fixes applied when explicitly requested.

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• Reviewing changes before a commit
• Checking a pull request or branch comparison
• Inspecting a specific commit for issues

Check spreadsheet formulas for errors, broken references, inconsistent calculations, and unit mismatches. Review a selected range, one sheet, or an entire financial model, then receive findings ranked by severity with suggested fixes.

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• Checking formulas in a selected range
• Investigating a balance sheet that does not balance
• Reviewing a financial model before client delivery

Guide changes and reviews for SGLang’s Scheduler, TokenizerManager, and ModelRunner classes. Keep initialization in small, replaceable helpers and separate computation from coordination so large classes retain clear responsibilities and explicit dependencies.

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• Reviewing changes to SGLang’s three large classes
• Splitting initialization into replaceable helpers
• Moving computation out of ModelRunner

Run performance improvements as a measured workflow in OMX and Codex goal mode. Define an evaluation command and success criteria, make small reversible changes, and retain evidence before declaring the work complete.

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• Reducing CLI startup time against a defined target
• Repeating improvements with benchmarks and regression tests
• Recording evaluation results and blockers

Create a saved plan for multiple goals in a repository, then execute it step by step with Codex goal mode. Track progress, verification evidence, review results, and blockers before marking the plan complete.

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• Break a project brief into multiple goals
• Execute planned tasks in sequence
• Record progress and verification evidence