Hire an AI decision knowledge and advice reviewer

Everything it can hand back

Your task sets the actual outputs. The specialist picks the methods that cover them.

• A map of what you know, half know and don't, with the edge named
• Six hard questions, your answers marked real, partial or only talk, and the gaps as questions
• A check of whether your adviser gains or loses with the advice
• A choice of learn, borrow, start small or pass, with a first-week plan and a retest date

How it does the job well

• Pin down the exact question, scope and the standard of evidence needed before searching.
• Prefer primary sources, and say how strong each source is.
• Separate what is established, debated and unknown, with confidence levels.
• Cite specifically: author, work, date or page where possible.

Mistakes it avoids

• Presenting one source or a popular claim as settled.
• Inventing citations, quotes or page numbers.
• Over-generalising across places, periods or groups.

What a good result looks like

An example, not your task: You are about to act in a field you have mostly read about.

• outputs/step-01-circle-of-competence-mapper.md. Each part of the topic rated known, partly known or not known, with your edge named.
• outputs/step-02-real-knowledge-tester.md. Six hard questions, your answers marked real, partial or only talk, and the gaps as questions.
• outputs/step-03-advice-skin-in-the-game-checker.md. Who pays if your adviser is wrong, who gains, and how far to trust the advice.
• outputs/step-04-learn-borrow-or-pass-planner.md. Your path (learn, borrow, start small or pass), a first-week plan and a retest date.
• HAND-BACK SUMMARY. Each step's file, any step not run and why, and every MISSING line in one list.

How the work is checked

• Each step passed its own checks, or the run stopped at the step that failed and says why.
• The steps ran in order, and each one used the result of the one before.
• Nothing was invented to fill a gap. Every gap is a MISSING: line.
• Nothing was sent, published or paid for without a clear yes.
• States which checks passed, failed or could not run, and names missing inputs.

These checks have not been run against a model yet. Your AI uses them to check its own work.

A second opinion

Before it hands back, your AI reviews the draft the way Charlie Munger and Nassim Nicholas Taleb would. This is a way of reviewing the work. It does not mean they wrote or endorse it.

Capabilities

• Maps your circle. Splits the topic into parts, rates each by evidence and names the edge.
• Tests your knowledge. Asks six hard follow-up questions and marks each answer real, partial or only talk.
• Checks your adviser. Asks what the adviser gains if you say yes and loses if they are wrong, and how far to trust the advice.
• Picks the path. Chooses learn, borrow, start small or pass using the size of the decision, the deadline and who holds the edge.
• Plans the first week. Lists the few big ideas to learn, the checks on any helper and seven days of small tasks, with a retest date.

How the role works

1. Checks your task, context and available tools.
2. Picks the methods needed and prepares a work plan.
3. Carries out supported tasks, with each method's limits and review gates.
4. Checks the real deliverables and corrects supported faults.
5. Hands back files, evidence and unresolved gaps.

Your specialist's working setup

Download the base specialist without a task form or account. README.md and SETUP.md explain how to use the folder. SOUL.md defines its scope. INTAKE.md asks missing questions inside your AI. PLAYBOOK.md, SKILLS.md, BEST_PRACTICES.md, CHECKS.md and HANDOFF.md guide the work and its checked deliverables.

Complete associated skills, supporting files and licences are included. Choose only the methods needed for the actual task. Keep context, working files and accepted feedback in your AI project.

Use this specialist through MCP or the API

Call prepare_specialist with role_id enough-info-check only. No task is required to load it. Your AI asks what job you need done, what you want back and which relevant context it can use.

For task-led hiring, call find_specialist, explain the suggested specialists and let the user accept or change the team.

Complete ZIP: Download base specialist. API: GET /api/v1/specialists/enough-info-check/pack. The host AI supplies its own model, tools and execution; a pack does not connect accounts or run a task.

Inputs and helpful context

The specialist starts from the task brief. Only active methods require their inputs.

For the primary method, when used

• What you are about to do and the field it sits in
• What you have done, studied or read about it
• Your answers to the hard questions, from memory
• The adviser you would rely on and how they are paid (optional)

Tools and access

• Any good chat AI: This is text reasoning that any strong chat AI handles with the skill.
• A notes app or document: Keeps your answers and the result in one place you can come back to.
• Any good chat AI: Writing the questions and marking answers is text work. Claude, ChatGPT and Gemini all do it with this skill. It needs no files.
• Any good chat AI: Judging advice and asking sharp questions is text work any strong chat AI does well with this skill.

Functions and deliverables

• Decision knowledge and advice reviewer: Test what you know before a decision, review an adviser's incentives and choose whether to learn, get help, start small or pass.
  • A map of what you know, half know and don't, with the edge named
  • Six hard questions, your answers marked real, partial or only talk, and the gaps as questions
  • A check of whether your adviser gains or loses with the advice
  • A choice of learn, borrow, start small or pass, with a first-week plan and a retest date
• Knowledge gap reviewer: Describe a topic or decision. Get what you know, half know and don't, and a verdict: in, learn first or pass.
  • The parts you must understand to judge it
  • Your level in each part, with the evidence
  • The edge of what you know
  • A verdict: in, learn first or pass, with the rule for it
• Subject knowledge tester: Test how well you really know a topic. Get six hard expert questions, each answer marked real or only talk, and the gaps to close.
  • Six hard questions an expert would ask
  • Each answer marked real, partial or only talk, with where the knowledge came from
  • A score out of six and a one-line verdict on your claim
  • The places where you sounded surer than you were
  • Gap questions you can look up or ask an adviser, ranked by how much they could change your decision
• Advice credibility checker: Share advice and how the adviser is paid. Get who gains, who could lose and how much weight to give the advice.
  • What the adviser loses if wrong and gains if right, with the evidence
  • Hidden unevenness in fees, rewards or blame
  • A trust level with the reason
  • One question to put to the adviser
• Knowledge gap decision planner: Not sure whether to learn it, borrow help or pass? Paste your knowledge gaps and get a clear choice with a first-week plan and a test date.
  • A choice: learn, borrow, start small or pass, with reasons
  • The few big ideas to learn first, if learning
  • The checks for any helper you borrow
  • A first-week plan and a date to test yourself again
• Research paper and code note writer: Share a paper, repo or messy notes. Get claims, methods and evidence sorted into a clear research folder.
  • A research folder with claims, methods and results
  • Every claim linked to its supporting table or log
  • Results tables copied with exact numbers
  • A record of dead ends and decisions
  • A short report on what was filled in and what was missing
  Source: Orchestra Research.
• Charlie Munger: Stress-test a plan using Charlie Munger’s recorded approach. Turn it upside down, examine incentives and ask where your knowledge ends.
  • Your problem worked on the way Charlie Munger would: their questions, their method, their push-back
  • The answer or the work, in Charlie Munger's voice, using their ideas by name
  • Anything that goes beyond their public record, marked
  • One suggested next step
• Nassim Nicholas Taleb: Review a plan’s exposure to shocks using Nassim Taleb’s recorded ideas. Find possible ruin, inspect who bears losses and question a calm record.
  • Your problem worked on the way Nassim Nicholas Taleb would: their questions, their method, their push-back
  • The answer or the work, in Nassim Nicholas Taleb's voice, using their ideas by name
  • Anything that goes beyond their public record, marked
  • One suggested next step

Tasks you can use it for

• You are about to act in a field you have mostly read about.
• You are thinking of hiring an expert and want to do it safely.
• You want to know which areas are worth building real skill in over the next few years.

Limits to check before starting

• You face a routine choice with a clear precedent or a small choice you can undo: just check the fact directly or ask one expert.
• You only want to judge one adviser's advice: use the Advice credibility checker.
• You want to test a business idea with real people: use the Minimum experiment planner.

Best way to use this role

Give it one clear outcome, the actual files and a definition of done. Keep the work in one AI project so it can reuse checked context and earlier files.

• Download the handoff pack. It's a zip with HANDOFF.md plus one skill file for each step.
• Give the folder to Claude (in Claude Code, or as files in a Claude Project) and say "Follow HANDOFF.md".
• Answer the hard questions from memory. Say so when you are guessing.
• Do the first week of the plan and book the retest.

Read it as data

Read the complete role setup as JSON. Connect your AI to the AI Blocks MCP library and read aiblocks://roles/enough-info-check for its role instructions and pinned sources.

This is a prepared AI role. No task has run. Your AI carries out authorized work using its available tools and reports the actual deliverables and checks.