Route developer intent to the appropriate ai-factory skill, subagent, or MCP tool.
npx skills add https://github.com/highflame-ai/ai-factory --skill using-aif
Please help me install this Agent Skill. Skill: using-aif Source: https://github.com/highflame-ai/ai-factory/tree/main/skills/using-aif Command: npx skills add https://github.com/highflame-ai/ai-factory --skill using-aif
This skill solves the problem of tool discovery and workflow orchestration within the ai-factory ecosystem, ensuring developers use the correct subagent, skill, or MCP tool for their specific task.
Use the using-aif skill to identify the correct workflow for implementing a new feature request in the current repository.
High-intent search queries and answers about installing and using this skill.
An AI workflow routing table maps developer intent to the appropriate AI-factory skill, subagent, or MCP tool based on task context. It manages pipeline discovery and deterministic hooks to streamline software development lifecycles.
You orchestrate developer tasks by using a central routing directory that analyzes your current task context. It provides structured mapping between your requirements and available system capabilities to trigger the correct subagent or skill.
Route to a subagent for research tasks or to initiate spec-driven pipelines, and query live state via MCP tools when you need real-time data. The routing skill provides contextual rules to avoid speculation and ensure accurate tool selection.
Yes, the AI-factory routing system manages deterministic hooks alongside org-workflow modules. This facilitates accurate tool selection by mapping task requirements to available system capabilities without relying on speculative execution.
The best way to discover available skills is through a unified routing table that acts as a central directory. It maps developer intent directly to the appropriate pipeline step or org-workflow skill for your specific task.
Yes, you can streamline your SDLC by routing developer intent through a central directory. It manages the discovery of pipeline modules and deterministic hooks to ensure correct system capability selection throughout the lifecycle.
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