skills/skill-design/SKILL.md
Design, strengthen, or audit an Agent Skill. Use before building any new skill — for a researched design brief that skill-creator can build from — and whenever an existing skill needs judgment or change: it over-triggers, under-triggers, bloats its context, drifts from its sources, or needs a quality check. Triggers: "design a skill", "plan a skill before building it", "audit this skill", "review my SKILL.md", "strengthen this skill", "refactor this skill", "is this skill well built", or any request to evaluate or improve how a skill routes, decides, or spends context. Packaging and eval mechanics stay with skill-creator; use this to decide what to build and to verify fit.
npx skillsauth add synapseradio/ai-skills skill-designInstall this skill globally with one command. Works with Claude Code, Cursor, and Windsurf.
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Work every mode the same way: pose a principle as a question about the skill in front of you — or the one taking shape — gather evidence from its files, and decide from the evidence. One question underlies all ten principles: can the executor close every decision delegated to it, using only what the skill provides? A decision closes when the executor can name the options on the table, the default included; tell the known facts from the assumed ones; rank the options by a stated rule; strike the options that fail a constraint; predict what follows from the option it favors; and see which act binds. Wherever the skill leaves one of those parts unsupplied, and gives the executor no way to find it, you have found work.
Building, testing, and packaging belong with skill-creator; deciding what a skill should be, and whether it holds up, belongs here. When the work turns to drafting a SKILL.md, running evals, tuning a description, or packaging, hand over to skill-creator.
Decide the mode from the state of the world, never from your own capability:
When a request straddles two modes ("audit this and fix what you find"), run Audit first and carry what you agreed on into Refactor as evidence. When the user asks for a refactor but states no misfit ("refine this", "strengthen this"), do the same: walk the principles over the whole skill first, and confirm with the user which findings to aim the refactor at. When you cannot tell which mode fits, ask the user one question rather than guessing. When a request fits no mode, say so — name what the work would take that no mode covers, and ask whether to stretch a mode or work outside this skill. Never force a fit.
Close a mode only when its exit artifact exists and satisfies its specification — never when the work feels done.
Read a mode's reference when you enter it, not before.
Ten principles anchor every mode's questions, from scheduling the workspace to making the skill observable. references/principles.md holds each in full — statement, reason, check — plus the vocabulary they share. Read it before design or refactor work; during an audit, walk it with the user as lenses.
Each mode's reference lists numbered moves. Walk them in order when unsure how to proceed. When you can see a better move than the listed one — one that fits this task better while still ending at the mode's exit artifact — take it, and tell the user what you changed and why.
Match evidence to stakes, never to your own sense of capability: how often the skill gets reused, what a wrong decision would cost to undo, and who reads the output. For one person's weekend project, less evidence per claim; for a team's marketplace, more. The moves stay the same; gather more evidence per move as stakes rise.
data-ai
Locate where a small change shifts the whole system
tools
Surface unstated assumptions at multiple levels and rank them
data-ai
Assess how well evidence supports claims
testing
Spot logical errors in reasoning