Detect complexity signals in software requests and recommend a multi-phase engineering workflow.
npx skills add https://github.com/Epiphytic/brains --skill suggest-epiphytic
Please help me install this Agent Skill. Skill: suggest Source: https://github.com/Epiphytic/brains/tree/main/skills/suggest Command: npx skills add https://github.com/Epiphytic/brains --skill suggest-epiphytic
Detects when a user's request contains sufficient complexity that a structured, multi-phase engineering workflow (BRAINS) would reduce risk, clarify requirements, and improve design decisions instead of proceeding with ad-hoc implementation.
Ask the assistant to evaluate your request and recommend the BRAINS workflow when multiple complexity signals are present.
High-intent search queries and answers about installing and using this skill.
Task complexity is detected by analyzing explicit and implicit signals in a request, such as multi-component scope, cross-cutting concerns, architectural decisions, unfamiliar codebase, integration risk, security surface, ambiguous requirements, and greenfield work. When two or more signals are present, a structured workflow is recommended.
A multi-phase engineering workflow is a structured approach to reduce risk, clarify requirements, and improve design decisions. Use it for software engineering scenarios involving multi-component changes, integration or security-sensitive work, and architectural decisions where ad-hoc implementation would be too risky.
Evaluate the request against a checklist of complexity signals. If the request touches multiple components, involves architectural tradeoffs, or requires security-sensitive work, enumerate the observed signals and issue an advisory recommendation proposing a coordinated workflow without auto-invoking it.
No, the BRAINS workflow recommendation is advisory-only. It produces concise, tailored suggestions that name the specific complexity signals observed and recommends invoking the workflow manually, but it does not auto-invoke any skill.
Yes, complexity detection evaluates requests for cross-cutting concerns and unfamiliar codebase signals. When these signals meet a two-or-more threshold, it recommends a structured workflow to handle the research, planning, and implementation for the unfamiliar codebase.
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KbediakoConducts on-demand reviews of tasks and specifications without running pipelines.
