Coach managers · Cheatcode

What are you preparing for?

One line is enough. Step 1 asks the rest in your AI app, and nothing is done until you approve the brief it writes.

In the case folder's materials/: Anything about the situation, with other people's names left out.

The person does the work live; the harness prepares and debriefs. Not found and out of scope are valid answers here: it says so instead of guessing.

How the field does this well: Use structured instruments: the same questions, planned follow ups and a four level rubric with example answers.
Remove names, photos and other proxies for protected traits in a script before any model reads a candidate's material. Keep the record IDs the person works with (employee, ticket or case numbers) so every finding names the row they will fix.
Score only against the written rubric with evidence quoted.
Draft instruments and plans; never rank people.
Ground it first: Ask for, or look in materials/ for: the role's attributes and level, the competency framework, and the company's policies. If there is none, say plainly that the result rests on general defaults, and name them.
What stays with the person: Every screening, hiring and people decision, and defining the role's attributes. Prepare these; never decide them.
The check that makes it trustworthy: Proxies redacted before the model reads anything about a person, and every judgment quoted against the rubric.
The person's own data: If the person has connected Google Drive / Docs / Sheets, Microsoft 365 (Excel, SharePoint, Teams), Notion, Slack, read their data through that connector instead of asking for exports, and say which source each number or fact came from. Without one, work from materials/.

On your computer: Your files in materials/, every result in outputs/, the work itself. It runs in your AI app, on the plan you already pay for.
With Cheatcode: The steps, the gates and how far each case has come, so a case survives closing the app. See your cases.