Agent skill · alirezarezvani
ai-decision-authority
Use before letting AI or an agent act on a marketing or GTM task without human review, or when writing an AI review policy. Places each workflow in AI-primary, collaborative or human-primary by stakes and reversibility.
What it needs
About 4k tokens when loaded.
What this skill does
AI Decision Authority Overview Decide which AI outputs a human must approve, and which an agent can own outright. Most AI governance in marketing fails in one of two directions. Review everything, and adoption collapses because using the tool is slower than doing the work by hand. Review nothing, and compliance exceptions accumulate quietly until one does not stay quiet, at which point legal arrives and you get the first failure anyway. Both failures come from applying one rule to every decision. Generating forty subject lines for a test is not the same decision as approving a regulatory disclosure. This skill sorts them by stakes rather than by seniority, so governance sits where the consequences are. Use it for a single decision, or to audit thirty workflows at once. Workflow Ask three questions in this order. Order matters, because reversibility dominates. 1. Can it be corrected if it is wrong? If this output is wrong, can it be quietly fixed, or has the damage already left the building? A content variant can be swapped in an hour. A regulatory filing cannot. 2. Who sees it, and what follows? Internal only, or does it cross a legal, executive, or external boundary? Exposure is what pulls a decision up out of Zone 1. 3. How often does it happen? A hundred times a week, or once a quarter? High-frequency standardised decisions are where a per-output human gate kills adoption. Low-frequency, high-consequence decisions absorb human ownership without becoming a bottleneck. Then assign a zone and apply its rule. Zone 1: AI-Primary Reversible, high-volume, internal only. Correctable at negligible cost. Examples: first-pass copy drafts, internal research summaries, data categorisation, competitive analysis, test variants, segmentation queries, performance summaries. Rule: the agent acts. Keep a log. Audit a periodic sample, never every output. No per-output gate. Expect roughly 70% of decision volume here. …
How to use it
Reference it in AdaL, Claude Code, Cursor or any coding agent — nothing to install:
@skills alirezarezvani/ai-decision-authority