ai-workflow
This skill should be used when explaining why Bee follows spec-first TDD workflows, or when teaching mode is on. Contains the reasoning behind spec → plan → test → code ordering.
Install
With your agent
Install OMGSkills skill "incubyte/ai-plugins:bee/skills/ai-workflow" into this agent's normal skills directory: call the OMGSkills MCP get_install_plan tool for your agent and run the script it returns (it installs only the pinned commit and verifies SKILL.md), and stop if MCP or the pin is unavailable. Do not overwrite or change existing skills without asking me.
Manual command
git clone https://github.com/incubyte/ai-plugins /tmp/ai-plugins && ln -s /tmp/ai-plugins/bee/skills/ai-workflow ~/.claude/skills/ai-workflowFrom README
AI-Assisted Development Workflow Why Specs Matter for AI The #1 reason AI-generated code misses the mark is ambiguous requirements. "Add authentication" forces the AI to guess 100 decisions — session vs JWT, cookie vs header, redirect vs 401, password rules, lockout policy. Each guess compounds. A spec with clear acceptance criteria eliminates guessing. The AI gets unambiguous targets and nails them on the first pass. The tradeoff: 10 minutes writing a spec saves hours of rework. Without a spec, you'll spend that time anyway — just spread across debugging, re-prompting, and rewriting. Why Tests Define "Done" for AI AI doesn't know when it's finished. It will keep generating code until you stop it. Tests give it a concrete finish line. A failing test is the clearest possible prompt: "Make this pass." The AI doesn't need to interpret requirements — the test IS the requirement in executable form. Red-green-refactor with AI: RED: Write a failing test. The AI now has a precise target.
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