83 个 · 按相关度排序
Coordinate project delivery by routing requests to eight specialist skills or running a verified delivery workflow. Use live Jira data for progress analysis and completion forecasts, with recorded evidence and checks before tasks are closed.
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Route product questions to a specialist for prioritization, research, analytics, experiments, or implementation. Support recurring discovery by tracking interviews and assumption tests, checking how customer needs connect to proposed solutions, and returning results with a concise digest.
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Test how agent workflows recover from repeatable simulated failures, including tool timeouts, worker restarts, and lost memory. Produces a fault matrix, event timeline, and verdict showing whether state, safety boundaries, and retry budgets were preserved.
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Use when an agent workflow needs deterministic recovery evidence for sandbox, MCP/tool, worker, checkpoint, memory, or orchestration failures.
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Hooks and MCP server guide for dotnet-agent-harness. How hooks behave, how to disable them, MCP configuration and troubleshooting.
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AI-powered skill recommendation engine for dotnet-agent-harness. Analyzes project context and recommends relevant skills based on detected frameworks, packages, and patterns. Triggers on: recommend skill, suggest skills, what skill should I use, skill suggestion, project analysis recommendation.
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Skill manifest management for dotnet-agent-harness. Tracks skill dependencies, conflicts, version compatibility, and provides validation and resolution tools. Triggers on: skill manifest, dependency resolution, skill compatibility, version conflicts, build manifest, validate dependencies.
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在Claude Code中组合记忆、定时执行与任务队列，设计持续开展的工作流程，并指导配置外部运行环境及浏览器、桌面操作集成。
设计和调整AI智能体使用的工具、输入与返回格式，明确出错后的恢复、重试和停止条件，管理上下文信息量，并以完成率、重试次数和成功任务成本评估改进。
Automatically repair source code against a failing test while preserving the test itself. Set a spending limit and attempt count, then receive verification results and usage costs based on rerunning the test command.
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Design the operating layer around a coding agent so it can read and edit code, run checks, and correct errors. Define completion criteria, permission boundaries, feedback, and recovery methods, and assess which tasks suit autonomous execution.
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Check whether gbrain uses PGLite or Postgres, set up a Postgres-backed installation, or migrate existing PGLite data with its history. The workflow presents a migration plan for approval, verifies transferred tables, and supports interrupted migration recovery.
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Plan a Claude Managed Agent around one clear job, then route work through setup, launch preparation, evaluation, and scheduling. Produce execution plans and curl commands that users run with their own Anthropic API key.
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Design and optimize AI agent action spaces, tool definitions, and observation formatting for higher completion rates.
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Test and evaluation harness for AI agents — scenario suites, deterministic replay, regression diffing, cost and latency budgets. Use when agent quality is vibe-checked, before shipping a prompt or model change, or when evals drift.
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Routes DataChain operating guidance for Python SDK pipelines, query expressions, CLI and Studio commands, agent-harness knowledge workflows, and repository maintenance.
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Honey for plain Claude — the terse-prose core with no agent-harness features. Paste into a claude.ai Project's custom instructions, a Style, or an API system prompt. Strips filler, hedging, and pleasantries from every response while keeping facts, names, numbers, steps, and code exact. No tools required.
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Review whether a repository's coding-agent harness can reliably carry work from intent through controlled execution, verification, delivery, and learning. Use when asked to assess agent readiness, repeated agent failures, Rules/Skills/Hooks/Memory effectiveness, missing validation or recovery loops, or whether a harness repair improved later outcomes. Do not use for code-only audits, AGENTS-only audits, individual skill reliability reviews, or executing the task itself.
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Design and optimize AI agent action spaces, tool definitions, and observation formatting for higher completion rates.
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当用户想使用 HiAgent 观测(observe)能力（API Token、Trace Spans 查询）时，务必使用这个技能给出可直接执行的 cli-anything-hiagent observe 命令与排障步骤。尤其适用于用户提到 agent-harness、cli_anything、--json、workspace-id、custom-app-id、VOLC_ACCESSKEY/VOLC_SECRETKEY、observe token、observe trace，以及希望用命令行(cli-anything-hiagent / python -m cli_anything.hiagent_sdk)。trace-ai-process / trace-ai-history / alert-ai-process / RuleID / IsStream
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Design and optimize AI agent action spaces, tool definitions, and observation formatting for higher completion rates.
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Comprehensive security audit covering OWASP Top 10, secrets detection, supply chain security, threat modeling, and language-specific vulnerability patterns. Investigates actual code paths rather than grep-matching keywords. Generates a scored SECURITY_AUDIT.md with prioritized remediation. Use when assessing application security, preparing for a security review, or onboarding to a codebase with security concerns.
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Systematic technical debt analysis across architecture, testing, documentation, and infrastructure. Investigates the codebase, scores findings by impact and effort, and generates a prioritized TECH_DEBT.md remediation plan. Delegates to specialized skills for code quality (scout) and linting (lint-fix). Use when assessing overall project health, planning cleanup sprints, or onboarding to an unfamiliar codebase.
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Generates Spring Boot 3.x configurations, creates REST controllers, implements Spring Security 6 authentication flows, sets up Spring Data JPA repositories, and configures reactive WebFlux endpoints. Use when building Spring Boot 3.x applications, microservices, or reactive Java applications; invoke for Spring Data JPA, Spring Security 6, WebFlux, Spring Cloud integration, Java REST API design, or Microservices Java architecture.
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