Audit websites for accessibility issues and WCAG compliance. Use when checking accessibility, fixing a11y issues, or ensuring WCAG compliance.
中文简介正在准备中。当前显示原文说明。
Sweep a contracts folder and extract every renewal date, auto-renew clause, notice window, and price-escalation term into a renewal calendar -- then create calendar reminders ahead of each notice deadline via Cowork's calendar write tools. The skill that stops auto-renewals from ambushing you.
中文简介正在准备中。当前显示原文说明。
实测评分 未实测
查看安装方法安装前可以查看交给 AI 代理的指令内容。
Read a folder of contracts the way outside counsel prepping a renewal calendar does: find every date-driven obligation, compute the real decision deadline (notice deadline, not renewal date), and put it somewhere it will actually be seen. Complements contract-analyzer (deep single-contract review) -- this skill is the portfolio sweep.
renewal date minus notice period minus a 14-day decision buffer. That is the radar date. Contracts already inside their notice window get flagged URGENT at the top of the report.renewal-calendar.md: chronological table of radar dates for the next 24 months with counterparty, annual value (when stated), what happens if nothing is done, and the verbatim notice clause. Separately list contracts with no end date or missing signature pages as data-quality issues.Renewal decision: [counterparty], description containing the notice deadline, clause quote, and file path -- after showing the user the list of events to be created and getting approval.As a monthly Cowork scheduled task: re-sweep the folder for new/amended contracts, update the calendar, and deliver a digest leading with anything entering its decision window in the next 60 days.
还没有评价。欢迎分享你的使用感受。
无需登录即可发表。欢迎分享使用感受、提问,或说明在哪些环境下无法运行。
还没有评论。来写第一条吧。
Audit websites for accessibility issues and WCAG compliance. Use when checking accessibility, fixing a11y issues, or ensuring WCAG compliance.
中文简介正在准备中。当前显示原文说明。
Deploy a 2-layer parallel agent hierarchy for large, parallelizable work — big refactors, multi-file migrations, codebase-wide audits, bulk generation. A top-tier commander (Fable or Opus) orchestrates the swarms; the user picks a power level (Max Power / Heavy / Balanced / Economy) that sets the Opus/Sonnet/Haiku model mix per layer. Layer 1 is 3-50+ specialist agents, each with its own full context window; Layer 2 is 2+ sub-agents per member. Includes git safety, tiered sizing, a pre-deploy gate, phantom-completion checks, and multi-wave follow-up.
中文简介正在准备中。当前显示原文说明。
Use to test whether an AI agent, prompt, or skill actually works before or after it ships — build a small eval set, score runs, and catch regressions when the prompt or model changes. Trigger when the user asks whether a prompt is good, wants to compare models or versions, sees inconsistent agent output, or is about to put an agent in front of customers.
中文简介正在准备中。当前显示原文说明。
Deploys swarms of sub-agents for massive parallel data processing tasks. Unlike agent-army (which is for code changes), this is for DATA tasks -- processing 1000 documents, analyzing datasets, bulk content generation. Configurable swarm size, task distribution, result aggregation, progress tracking, and error recovery.
中文简介正在准备中。当前显示原文说明。
Designs and deploys custom agent teams for specific business workflows. Interactive discovery of business processes, then generates complete team configurations with specialized agent roles, tool access, communication protocols, and handoff rules.
中文简介正在准备中。当前显示原文说明。
Agent-to-Agent (A2A) communication protocol. Connect two or more Claude agents that pass messages, share context, delegate tasks, and collaborate. Implements structured handoffs, shared memory, and multi-agent conversations.
中文简介正在准备中。当前显示原文说明。