.claude/skills/deep-researchRuntime, accounts, dependencies, permissions, network behavior and task quality remain untested.
深度调研的多Agent编排工作流:把一个调研目标拆成可并行子目标,用 Claude Code 非交互模式(`claude -p`)运行子进程;联网与采集优先使用已安装的 skills,其次使用 MCP 工具;用脚本聚合子结果并分章精修,最终交付"成品报告文件路径 + 关键结论/建议摘要"。用于:系统性网页/资料调...
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These checks parse the fixed package against dated platform rules. They do not execute the Skill or verify task behavior.
.claude/skills/deep-researchRuntime, accounts, dependencies, permissions, network behavior and task quality remain untested.
.agents/skills/deep-researchRuntime, accounts, dependencies, permissions, network behavior and task quality remain untested.
skills/deep-researchRuntime, accounts, dependencies, permissions, network behavior and task quality remain untested.
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clawhub install @feiskyer/deep-research-skillclawhub inspect @feiskyer/deep-research-skill --version 0.1.0This automated, non-executing scan is bound to this release hash. It is not a safety certification and may contain false positives or false negatives.
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sha256:f5323476603f4c0d8ac98892dcb55b785562e5ad605a754fc2d6378c871d3d86skill-card.mdSKILL.mddeep-research-skill v0.1.0 - Initial release of a multi-Agent workflow for in-depth research tasks, supporting automated goal decomposition and parallel execution using Claude Code's non-interactive mode. - Enforces a step-by-step process: goal clarification, parallel subgoal scheduling, data collection/aggregation, section-based refinement, and structured report delivery as files. - Prioritizes internet access through installed skills, then MCP (firecrawl > exa), with fallback to basic web fetch/search only if necessary. - Implements strict logging, permission control, and mandatory user confirmation before task execution. - Requires all outputs to be saved as files; does not post complete reports in chat. - Designed for reproducible, systematized research use cases such as web/material analysis, competitive/industry analysis, bulk retrieval, and long-form evidence-integrated writing.