Agent Protocol
Agent Protocol: Design or evaluate an AI workflow. Review the task, context sources, tools, budget, and failure modes and produce an AI workflow specification with evaluation cases.
--- name: c-level-advisor-agent-protocol description: Use for agent protocol when asked to design or evaluate an AI workflow; produce an AI workflow specification with evaluation cases. license: MIT metadata: author: Thrive category: c-level-advisor --- # Agent Protocol ## When to use Use this skill for agent protocol when you need to design or evaluate an AI workflow. The expected result is an AI workflow specification with evaluation cases. ## Boundaries Work within the requested task and its stated acceptance criteria. Drafting an artifact does not authorize publishing it, spending funds, changing a live system, or contacting another person. Identify any such action separately before taking it. ## Inputs Inspect the task, context sources, tools, budget, and failure modes. Resolve missing information that would change the method; state lesser assumptions in the result. ## Method 1. **Diagnose.** Frame the executive decision, available options, cost of delay, stakeholder effects, and assumptions behind the numbers. 2. **Decide.** Set measurable evaluation cases before changing prompts or agent behavior. 3. **Produce.** Build an AI workflow specification with evaluation cases from the inspected material; keep assumptions distinguishable from observed facts. ## Decision rules - Test the preferred option against downside, opportunity cost, execution capacity, and reversibility. - When sources or constraints conflict, record the conflict and choose the path supported by the user's goal and the strongest available evidence. If neither path can be supported, identify the missing decision before changing the artifact. ## Domain rules - Lead with the decision, alternatives, strategic trade-offs, and decision owner. - State the evidence that would change the recommendation at the next review. ## Verification Test representative successes, failures, and stop conditions. Compare the result with the user's acceptance criteria and record any unverified boundary. Write an answer-first decision memo with trade-offs, dissent, owner, and the signal that would change course. ## Stop conditions If a material input, required authorization, or a safe way to verify the result is absent, stop the affected action. Return the specific blocker and the smallest fact or decision needed to continue. Do not report an unrun check as passed. ## Output Provide an AI workflow specification with evaluation cases. Include the decisive evidence and actual verification result. Name any artifact location and unresolved issue that affects its use. <!-- MIT License Copyright (c) 2026 Thrive Permission is hereby granted, free of charge, to any person obtaining a copy of this software and associated documentation files (the "Software"), to deal in the Software without restriction, including without limitation the rights to use, copy, modify, merge, publish, distribute, sublicense, and/or sell copies of the Software, and to permit persons to whom the Software is furnished to do so, subject to the following conditions: The above copyright notice and this permission notice shall be included in all copies or substantial portions of the Software. THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE SOFTWARE. -->