Business
Risk Register and Control Mapping
Risk Register and Control Mapping turns business context into a structured commercial recommendation with clear constraints and an explicit output.
The prompt
Risk Register and Control Mapping guides the model through a defined task while preserving the source prompt's useful structure and constraints. Use it when planning strategy, operations, sales, or customer work and you want a response that is easier to evaluate and act on.
text prompt
You are a risk manager.
Model guidance (ChatGPT GPT-5.2):
- If available, use GPT-5.2 Thinking for planning and GPT-5.2 Pro for the hardest steps.
- If your environment supports a reasoning effort setting, use xhigh only for the most complex parts, otherwise use the default.
Task:
Build a risk register for the scope described. Map risks to existing or proposed controls, owners, and review cadence.
Inputs:
- Scope of system or initiative: {{scope}}
- Risk appetite and constraints: {{riskAppetite}}
- Existing controls (if any): {{currentControls}}
Output requirements:
- Return JSON only. Do not wrap in Markdown or code fences.
- Do not add keys beyond the schema.
- Populate clarifying_questions if any critical input is missing or ambiguous, but still produce a best-effort deliverable.
- Keep explanations brief. Put the main work in deliverable_markdown.
JSON schema (example values only, keep the same keys):
{
"title": "Risk Register and Control Mapping",
"deliverable_type": "Risk register with controls",
"clarifying_questions": [],
"assumptions": [],
"deliverable_markdown": "",
"quality_checks": [
"Risks are specific and not generic",
"Each risk has likelihood, impact, and owner",
"Controls map logically to risks",
"Includes monitoring and review cadence"
],
"next_steps": []
}
Tune the prompt, not the plumbing.
Every control comes from this prompt’s content schema. Changes stay in your browser and update instantly.
Customized prompt1322 characters
You are a risk manager.
Model guidance (ChatGPT GPT-5.2):
- If available, use GPT-5.2 Thinking for planning and GPT-5.2 Pro for the hardest steps.
- If your environment supports a reasoning effort setting, use xhigh only for the most complex parts, otherwise use the default.
Task:
Build a risk register for the scope described. Map risks to existing or proposed controls, owners, and review cadence.
Inputs:
- Scope of system or initiative: a specific scope
- Risk appetite and constraints: a specific risk appetite
- Existing controls (if any): a specific current controls
Output requirements:
- Return JSON only. Do not wrap in Markdown or code fences.
- Do not add keys beyond the schema.
- Populate clarifying_questions if any critical input is missing or ambiguous, but still produce a best-effort deliverable.
- Keep explanations brief. Put the main work in deliverable_markdown.
JSON schema (example values only, keep the same keys):
{
"title": "Risk Register and Control Mapping",
"deliverable_type": "Risk register with controls",
"clarifying_questions": [],
"assumptions": [],
"deliverable_markdown": "",
"quality_checks": [
"Risks are specific and not generic",
"Each risk has likelihood, impact, and owner",
"Controls map logically to risks",
"Includes monitoring and review cadence"
],
"next_steps": []
}
Useful structure, room to move.
Risk Register and Control Mapping guides the model through a defined task while preserving the source prompt's useful structure and constraints. Use it when planning strategy, operations, sales, or customer work and you want a response that is easier to evaluate and act on.
The prompt establishes the job first, then supplies concrete decisions a model can act on. The variables preserve that structure while letting you change the subject, context, or output.
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